Modeling surgical tool selection patterns as a "traveling salesman problem" for optimizing a modular surgical tool system.

PubMed

Nelson, Carl A; Miller, David J; Oleynikov, Dmitry

2008-01-01

As modular systems come into the forefront of robotic telesurgery, streamlining the process of selecting surgical tools becomes an important consideration. This paper presents a method for optimal queuing of tools in modular surgical tool systems, based on patterns in tool-use sequences, in order to minimize time spent changing tools. The solution approach is to model the set of tools as a graph, with tool-change frequency expressed as edge weights in the graph, and to solve the Traveling Salesman Problem for the graph. In a set of simulations, this method has shown superior performance at optimizing tool arrangements for streamlining surgical procedures.

A Simulation of Readiness-Based Sparing Policies

DTIC Science & Technology

2017-06-01

variant of a greedy heuristic algorithm to set stock levels and estimate overall WS availability. Our discrete event simulation is then used to test the...available in the optimization tools. 14. SUBJECT TERMS readiness-based sparing, discrete event simulation, optimization, multi-indenture...variant of a greedy heuristic algorithm to set stock levels and estimate overall WS availability. Our discrete event simulation is then used to test the

Global Simulation of Aviation Operations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Sheth, Kapil; Ng, Hok Kwan; Morando, Alex; Li, Jinhua

2016-01-01

The simulation and analysis of global air traffic is limited due to a lack of simulation tools and the difficulty in accessing data sources. This paper provides a global simulation of aviation operations combining flight plans and real air traffic data with historical commercial city-pair aircraft type and schedule data and global atmospheric data. The resulting capability extends the simulation and optimization functions of NASA's Future Air Traffic Management Concept Evaluation Tool (FACET) to global scale. This new capability is used to present results on the evolution of global air traffic patterns from a concentration of traffic inside US, Europe and across the Atlantic Ocean to a more diverse traffic pattern across the globe with accelerated growth in Asia, Australia, Africa and South America. The simulation analyzes seasonal variation in the long-haul wind-optimal traffic patterns in six major regions of the world and provides potential time-savings of wind-optimal routes compared with either great circle routes or current flight-plans if available.

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.

Designs for Risk Evaluation and Management

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

The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO 2) under the U.S. Department of Energy's National Risk Assessment Partnership (NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first detection of CO 2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output from subsurface leakage simulations. While DREAM was developed for CO 2 leakage scenarios, it is applicable to any subsurface leakage simulation of the same output format.more » The DREAM tool is comprised of three main components: (1) a Java wizard used to configure and execute the simulations, (2) a visualization tool to view the domain space and optimization results, and (3) a plotting tool used to analyze the results. A secondary Java application is provided to aid users in converting common American Standard Code for Information Interchange (ASCII) output data to the standard DREAM hierarchical data format (HDF5). DREAM employs a simulated annealing approach that searches the solution space by iteratively mutating potential monitoring schemes built of various configurations of monitoring locations and leak detection parameters. This approach has proven to be orders of magnitude faster than an exhaustive search of the entire solution space. The user's manual illustrates the program graphical user interface (GUI), describes the tool inputs, and includes an example application.« less

Optimizing STEM Education with Advanced ICTs and Simulations

ERIC Educational Resources Information Center

Levin, Ilya, Ed.; Tsybulsky, Dina, Ed.

2017-01-01

The role of technology in educational settings has become increasingly prominent in recent years. When utilized effectively, these tools provide a higher quality of learning for students. "Optimizing STEM Education With Advanced ICTs and Simulations" is an innovative reference source for the latest scholarly research on the integration…

Assessment of Energy Storage Alternatives in the Puget Sound Energy System Volume 2: Energy Storage Evaluation Tool

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

Wu, Di; Jin, Chunlian; Balducci, Patrick J.

2013-12-01

This volume presents the battery storage evaluation tool developed at Pacific Northwest National Laboratory (PNNL), which is used to evaluate benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a look-ahead optimization is first formulated and solved to determine battery base operating point. The minute by minute simulation is then performed to simulate the actual battery operation. This volume provide backgroundmore » and manual for this evaluation tool.« less

Peter Graf | NREL

Science.gov Websites

-device simulation tool for organic photovoltaics research. Current research focuses are (1) optimization optimization in organic photovoltaics. Dr. Graf graduated Phi Beta Kappa, with distinction, from Stanford

Parameter identification and optimization of slide guide joint of CNC machine tools

NASA Astrophysics Data System (ADS)

Zhou, S.; Sun, B. B.

2017-11-01

The joint surface has an important influence on the performance of CNC machine tools. In order to identify the dynamic parameters of slide guide joint, the parametric finite element model of the joint is established and optimum design method is used based on the finite element simulation and modal test. Then the mode that has the most influence on the dynamics of slip joint is found through harmonic response analysis. Take the frequency of this mode as objective, the sensitivity analysis of the stiffness of each joint surface is carried out using Latin Hypercube Sampling and Monte Carlo Simulation. The result shows that the vertical stiffness of slip joint surface constituted by the bed and the slide plate has the most obvious influence on the structure. Therefore, this stiffness is taken as the optimization variable and the optimal value is obtained through studying the relationship between structural dynamic performance and stiffness. Take the stiffness values before and after optimization into the FEM of machine tool, and it is found that the dynamic performance of the machine tool is improved.

Development of a CSP plant energy yield calculation tool applying predictive models to analyze plant performance sensitivities

NASA Astrophysics Data System (ADS)

Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons

2017-06-01

At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.

Auto-DR and Pre-cooling of Buildings at Tri-City Corporate Center

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

Yin, Rongxin; Xu, Peng; Kiliccote, Sila

2008-11-01

Over the several past years, Lawrence Berkeley National Laboratory (LBNL) has conducted field tests for different pre-cooling strategies in different commercial buildings within California. The test results indicated that pre-cooling strategies were effective in reducing electric demand in these buildings during peak periods. This project studied how to optimize pre-cooling strategies for eleven buildings in the Tri-City Corporate Center, San Bernardino, California with the assistance of a building energy simulation tool -- the Demand Response Quick Assessment Tool (DRQAT) developed by LBNL's Demand Response Research Center funded by the California Energy Commission's Public Interest Energy Research (PIER) Program. From themore » simulation results of these eleven buildings, optimal pre-cooling and temperature reset strategies were developed. The study shows that after refining and calibrating initial models with measured data, the accuracy of the models can be greatly improved and the models can be used to predict load reductions for automated demand response (Auto-DR) events. This study summarizes the optimization experience of the procedure to develop and calibrate building models in DRQAT. In order to confirm the actual effect of demand response strategies, the simulation results were compared to the field test data. The results indicated that the optimal demand response strategies worked well for all buildings in the Tri-City Corporate Center. This study also compares DRQAT with other building energy simulation tools (eQUEST and BEST). The comparison indicate that eQUEST and BEST underestimate the actual demand shed of the pre-cooling strategies due to a flaw in DOE2's simulation engine for treating wall thermal mass. DRQAT is a more accurate tool in predicting thermal mass effects of DR events.« less

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.

Challenges of NDE Simulation Tool Challenges of NDE Simulation Tool

NASA Technical Reports Server (NTRS)

Leckey, Cara A. C.; Juarez, Peter D.; Seebo, Jeffrey P.; Frank, Ashley L.

2015-01-01

Realistic nondestructive evaluation (NDE) simulation tools enable inspection optimization and predictions of inspectability for new aerospace materials and designs. NDE simulation tools may someday aid in the design and certification of advanced aerospace components; potentially shortening the time from material development to implementation by industry and government. Furthermore, modeling and simulation are expected to play a significant future role in validating the capabilities and limitations of guided wave based structural health monitoring (SHM) systems. The current state-of-the-art in ultrasonic NDE/SHM simulation cannot rapidly simulate damage detection techniques for large scale, complex geometry composite components/vehicles with realistic damage types. This paper discusses some of the challenges of model development and validation for composites, such as the level of realism and scale of simulation needed for NASA' applications. Ongoing model development work is described along with examples of model validation studies. The paper will also discuss examples of the use of simulation tools at NASA to develop new damage characterization methods, and associated challenges of validating those methods.

Writing Technical Reports for Simulation in Education for Health Professionals: Suggested Guidelines.

PubMed

Dubrowski, Adam; Alani, Sabrina; Bankovic, Tina; Crowe, Andrea; Pollard, Megan

2015-11-02

Simulation is an important training tool used in a variety of influential fields. However, development of simulation scenarios - the key component of simulation - occurs in isolation; sharing of scenarios is almost non-existent. This can make simulation use a costly task in terms of the resources and time and the possible redundancy of efforts. To alleviate these issues, the goal is to strive for an open communication of practice (CoP) surrounding simulation. To facilitate this goal, this report describes a set of guidelines for writing technical reports about simulation use for educating health professionals. Using an accepted set of guidelines will allow for homogeneity when building simulation scenarios and facilitate open sharing among simulation users. In addition to optimizing simulation efforts in institutions that are currently using simulation as an educational tool, the development of such a repository may have direct implications on developing countries, where simulation is only starting to be used systematically. Our project facilitates equivalent and global access to information, knowledge, and highest-caliber education - in this context, simulation - collectively, the building blocks of optimal healthcare.

Writing Technical Reports for Simulation in Education for Health Professionals: Suggested Guidelines

PubMed Central

Alani, Sabrina; Bankovic, Tina; Crowe, Andrea; Pollard, Megan

2015-01-01

Simulation is an important training tool used in a variety of influential fields. However, development of simulation scenarios - the key component of simulation – occurs in isolation; sharing of scenarios is almost non-existent. This can make simulation use a costly task in terms of the resources and time and the possible redundancy of efforts. To alleviate these issues, the goal is to strive for an open communication of practice (CoP) surrounding simulation. To facilitate this goal, this report describes a set of guidelines for writing technical reports about simulation use for educating health professionals. Using an accepted set of guidelines will allow for homogeneity when building simulation scenarios and facilitate open sharing among simulation users. In addition to optimizing simulation efforts in institutions that are currently using simulation as an educational tool, the development of such a repository may have direct implications on developing countries, where simulation is only starting to be used systematically. Our project facilitates equivalent and global access to information, knowledge, and highest-caliber education - in this context, simulation – collectively, the building blocks of optimal healthcare.  PMID:26677421

A practical six-degree of freedom solar sail dynamics model for optimizing solar sail trajectories with torque constraints

NASA Technical Reports Server (NTRS)

Lisano, Michael E.

2004-01-01

Controlled flight of a solar sail-propelled spacecraft ('sailcraft') is a six-degree-of-freedom dynamics problem. Current state-of-the-art tools that simulate and optimize the trajectories flown by sailcraft do not treat the full kinetic (i.e. force and torque-constrained) motion, instead treating a discrete history of commanded sail attitudes, and either neglecting the sail attitude motion over an integration timestep, or treating the attitude evolution kinematically with a spline or similar treatment. The present paper discusses an aspect of developing a next generation sailcraf trajectory designing optimization tool JPL, for NASA's Solar Sail Spaceflight Simulation Software (SS). The aspect discussed in an experimental approach to modeling full six-degree-of-freedom kinetic motion of a solar sail in a trajectory propagator. Early results from implementing this approach in a new trajectory propagation tool are given.

Next-generation simulation and optimization platform for forest management and analysis

Treesearch

Antti Makinen; Jouni Kalliovirta; Jussi Rasinmaki

2009-01-01

Late developments in the objectives and the data collection methods of forestry create new challenges and possibilities in forest management planning. Tools in forest management and forest planning systems must be able to make good use of novel data sources, use new models, and solve complex forest planning tasks at different scales. The SIMulation and Optimization (...

CATO: a CAD tool for intelligent design of optical networks and interconnects

NASA Astrophysics Data System (ADS)

Chlamtac, Imrich; Ciesielski, Maciej; Fumagalli, Andrea F.; Ruszczyk, Chester; Wedzinga, Gosse

1997-10-01

Increasing communication speed requirements have created a great interest in very high speed optical and all-optical networks and interconnects. The design of these optical systems is a highly complex task, requiring the simultaneous optimization of various parts of the system, ranging from optical components' characteristics to access protocol techniques. Currently there are no computer aided design (CAD) tools on the market to support the interrelated design of all parts of optical communication systems, thus the designer has to rely on costly and time consuming testbed evaluations. The objective of the CATO (CAD tool for optical networks and interconnects) project is to develop a prototype of an intelligent CAD tool for the specification, design, simulation and optimization of optical communication networks. CATO allows the user to build an abstract, possible incomplete, model of the system, and determine its expected performance. Based on design constraints provided by the user, CATO will automatically complete an optimum design, using mathematical programming techniques, intelligent search methods and artificial intelligence (AI). Initial design and testing of a CATO prototype (CATO-1) has been completed recently. The objective was to prove the feasibility of combining AI techniques, simulation techniques, an optical device library and a graphical user interface into a flexible CAD tool for obtaining optimal communication network designs in terms of system cost and performance. CATO-1 is an experimental tool for designing packet-switching wavelength division multiplexing all-optical communication systems using a LAN/MAN ring topology as the underlying network. The two specific AI algorithms incorporated are simulated annealing and a genetic algorithm. CATO-1 finds the optimal number of transceivers for each network node, using an objective function that includes the cost of the devices and the overall system performance.

New Tooling System for Forming Aluminum Beverage Can End Shell

NASA Astrophysics Data System (ADS)

Yamazaki, Koetsu; Otsuka, Takayasu; Han, Jing; Hasegawa, Takashi; Shirasawa, Taketo

2011-08-01

This paper proposes a new tooling system for forming shells of aluminum beverage can ends. At first, forming process of a conversional tooling system has been simulated using three-dimensional finite element models. Simulation results have been confirmed to be consistent with those of axisymmetric models, so simulations for further study have been performed using axisymmetric models to save computational time. A comparison shows that thinning of the shell formed by the proposed tooling system has been improved about 3.6%. Influences of the tool upmost surface profiles and tool initial positions in the new tooling system have been investigated and the design optimization method based on the numerical simulations has been then applied to search optimum design points, in order to minimize thinning subjected to the constraints of the geometrical dimensions of the shell. At last, the performance of the shell subjected to internal pressure has been confirmed to meet design requirements.

Simulation of Medical Imaging Systems: Emission and Transmission Tomography

NASA Astrophysics Data System (ADS)

Harrison, Robert L.

Simulation is an important tool in medical imaging research. In patient scans the true underlying anatomy and physiology is unknown. We have no way of knowing in a given scan how various factors are confounding the data: statistical noise; biological variability; patient motion; scattered radiation, dead time, and other data contaminants. Simulation allows us to isolate a single factor of interest, for instance when researchers perform multiple simulations of the same imaging situation to determine the effect of statistical noise or biological variability. Simulations are also increasingly used as a design optimization tool for tomographic scanners. This article gives an overview of the mechanics of emission and transmission tomography simulation, reviews some of the publicly available simulation tools, and discusses trade-offs between the accuracy and efficiency of simulations.

Direct Method Transcription for a Human-Class Translunar Injection Trajectory Optimization

NASA Technical Reports Server (NTRS)

Witzberger, Kevin E.; Zeiler, Tom

2012-01-01

This paper presents a new trajectory optimization software package developed in the framework of a low-to-high fidelity 3 degrees-of-freedom (DOF)/6-DOF vehicle simulation program named Mission Analysis Simulation Tool in Fortran (MASTIF) and its application to a translunar trajectory optimization problem. The functionality of the developed optimization package is implemented as a new "mode" in generalized settings to make it applicable for a general trajectory optimization problem. In doing so, a direct optimization method using collocation is employed for solving the problem. Trajectory optimization problems in MASTIF are transcribed to a constrained nonlinear programming (NLP) problem and solved with SNOPT, a commercially available NLP solver. A detailed description of the optimization software developed is provided as well as the transcription specifics for the translunar injection (TLI) problem. The analysis includes a 3-DOF trajectory TLI optimization and a 3-DOF vehicle TLI simulation using closed-loop guidance.

A Robust Method to Integrate End-to-End Mission Architecture Optimization Tools

NASA Technical Reports Server (NTRS)

Lugo, Rafael; Litton, Daniel; Qu, Min; Shidner, Jeremy; Powell, Richard

2016-01-01

End-to-end mission simulations include multiple phases of flight. For example, an end-to-end Mars mission simulation may include launch from Earth, interplanetary transit to Mars and entry, descent and landing. Each phase of flight is optimized to meet specified constraints and often depend on and impact subsequent phases. The design and optimization tools and methodologies used to combine different aspects of end-to-end framework and their impact on mission planning are presented. This work focuses on a robust implementation of a Multidisciplinary Design Analysis and Optimization (MDAO) method that offers the flexibility to quickly adapt to changing mission design requirements. Different simulations tailored to the liftoff, ascent, and atmospheric entry phases of a trajectory are integrated and optimized in the MDAO program Isight, which provides the user a graphical interface to link simulation inputs and outputs. This approach provides many advantages to mission planners, as it is easily adapted to different mission scenarios and can improve the understanding of the integrated system performance within a particular mission configuration. A Mars direct entry mission using the Space Launch System (SLS) is presented as a generic end-to-end case study. For the given launch period, the SLS launch performance is traded for improved orbit geometry alignment, resulting in an optimized a net payload that is comparable to that in the SLS Mission Planner's Guide.

Using Two Simulation Tools to Teach Concepts in Introductory Astronomy: A Design-Based Research Approach

NASA Astrophysics Data System (ADS)

Maher, Pamela A.

Technology in college classrooms has gone from being an enhancement to the learning experience to being something expected by both instructors and students. This design-based research investigation takes technology one step further, putting the tools used to teach directly in the hands of students. The study examined the affordances and constraints of two simulation tools for use in introductory astronomy courses. The variety of experiences participants had using two tools; a virtual reality headset and fulldome immersive planetarium simulation, to manipulate a lunar surface flyby were identified using a multi-method research approach with N = 67 participants. Participants were recruited from classes of students taking astronomy over one academic year at a two-year college. Participants manipulated a lunar flyby using a virtual reality headset and a motion sensor device in the college fulldome planetarium. Data were collected in the form of two post-treatment questionnaires using Likert-type scales and one small group interview. The small group interview was intended to elicit various experiences participants had using the tools. Responses were analyzed quantitatively for optimal flyby speed and qualitatively for salient themes using data reduction informed by a methodological framework of phenomenography to identify the variety of experiences participants had using the tools. Findings for optimal flyby speed of the Moon based on analysis of data for both the Immersion Questionnaire and the Simulator Sickness Questionnaire done using SPSS software determine that the optimal flyby speed for college students to manipulate the Moon was calculated to be .04 x the radius of the Earth (3,959 miles) or 160 miles per second. A variety of different participant experiences were revealed using MAXQDA software to code positive and negative remarks participants had when engaged in the use of each tool. Both tools offer potential to actively engage students with astronomy content in college lecture and laboratory courses.

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

Simulation in production of open rotor propellers: from optimal surface geometry to automated control of mechanical treatment

NASA Astrophysics Data System (ADS)

Grinyok, A.; Boychuk, I.; Perelygin, D.; Dantsevich, I.

2018-03-01

A complex method of the simulation and production design of open rotor propellers was studied. An end-to-end diagram was proposed for the evaluating, designing and experimental testing the optimal geometry of the propeller surface, for the machine control path generation as well as for simulating the cutting zone force condition and its relationship with the treatment accuracy which was defined by the propeller elastic deformation. The simulation data provided the realization of the combined automated path control of the cutting tool.

An integrated modeling and design tool for advanced optical spacecraft

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

1992-01-01

Consideration is given to the design and status of the Integrated Modeling of Optical Systems (IMOS) tool and to critical design issues. A multidisciplinary spacecraft design and analysis tool with support for structural dynamics, controls, thermal analysis, and optics, IMOS provides rapid and accurate end-to-end performance analysis, simulations, and optimization of advanced space-based optical systems. The requirements for IMOS-supported numerical arrays, user defined data structures, and a hierarchical data base are outlined, and initial experience with the tool is summarized. A simulation of a flexible telescope illustrates the integrated nature of the tools.

Generalized DSS shell for developing simulation and optimization hydro-economic models of complex water resources systems

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, Manuel; Lopez-Nicolas, Antonio; Harou, Julien J.; Andreu, Joaquin

2013-04-01

Hydrologic-economic models allow integrated analysis of water supply, demand and infrastructure management at the river basin scale. These models simultaneously analyze engineering, hydrology and economic aspects of water resources management. Two new tools have been designed to develop models within this approach: a simulation tool (SIM_GAMS), for models in which water is allocated each month based on supply priorities to competing uses and system operating rules, and an optimization tool (OPT_GAMS), in which water resources are allocated optimally following economic criteria. The characterization of the water resource network system requires a connectivity matrix representing the topology of the elements, generated using HydroPlatform. HydroPlatform, an open-source software platform for network (node-link) models, allows to store, display and export all information needed to characterize the system. Two generic non-linear models have been programmed in GAMS to use the inputs from HydroPlatform in simulation and optimization models. The simulation model allocates water resources on a monthly basis, according to different targets (demands, storage, environmental flows, hydropower production, etc.), priorities and other system operating rules (such as reservoir operating rules). The optimization model's objective function is designed so that the system meets operational targets (ranked according to priorities) each month while following system operating rules. This function is analogous to the one used in the simulation module of the DSS AQUATOOL. Each element of the system has its own contribution to the objective function through unit cost coefficients that preserve the relative priority rank and the system operating rules. The model incorporates groundwater and stream-aquifer interaction (allowing conjunctive use simulation) with a wide range of modeling options, from lumped and analytical approaches to parameter-distributed models (eigenvalue approach). Such functionality is not typically included in other water DSS. Based on the resulting water resources allocation, the model calculates operating and water scarcity costs caused by supply deficits based on economic demand functions for each demand node. The optimization model allocates the available resource over time based on economic criteria (net benefits from demand curves and cost functions), minimizing the total water scarcity and operating cost of water use. This approach provides solutions that optimize the economic efficiency (as total net benefit) in water resources management over the optimization period. Both models must be used together in water resource planning and management. The optimization model provides an initial insight on economically efficient solutions, from which different operating rules can be further developed and tested using the simulation model. The hydro-economic simulation model allows assessing economic impacts of alternative policies or operating criteria, avoiding the perfect foresight issues associated with the optimization. The tools have been applied to the Jucar river basin (Spain) in order to assess the economic results corresponding to the current modus operandi of the system and compare them with the solution from the optimization that maximizes economic efficiency. Acknowledgments: The study has been partially supported by the European Community 7th Framework Project (GENESIS project, n. 226536) and the Plan Nacional I+D+I 2008-2011 of the Spanish Ministry of Science and Innovation (CGL2009-13238-C02-01 and CGL2009-13238-C02-02).

A computer simulator for development of engineering system design methodologies

NASA Technical Reports Server (NTRS)

Padula, S. L.; Sobieszczanski-Sobieski, J.

1987-01-01

A computer program designed to simulate and improve engineering system design methodology is described. The simulator mimics the qualitative behavior and data couplings occurring among the subsystems of a complex engineering system. It eliminates the engineering analyses in the subsystems by replacing them with judiciously chosen analytical functions. With the cost of analysis eliminated, the simulator is used for experimentation with a large variety of candidate algorithms for multilevel design optimization to choose the best ones for the actual application. Thus, the simulator serves as a development tool for multilevel design optimization strategy. The simulator concept, implementation, and status are described and illustrated with examples.

CONSOLE: A CAD tandem for optimization-based design interacting with user-supplied simulators

NASA Technical Reports Server (NTRS)

Fan, Michael K. H.; Wang, Li-Sheng; Koninckx, Jan; Tits, Andre L.

1989-01-01

CONSOLE employs a recently developed design methodology (International Journal of Control 43:1693-1721) which provides the designer with a congenial environment to express his problem as a multiple ojective constrained optimization problem and allows him to refine his characterization of optimality when a suboptimal design is approached. To this end, in CONSOLE, the designed formulates the design problem using a high-level language and performs design task and explores tradeoff through a few short and clearly defined commands. The range of problems that can be solved efficiently using a CAD tools depends very much on the ability of this tool to be interfaced with user-supplied simulators. For instance, when designing a control system one makes use of the characteristics of the plant, and therefore, a model of the plant under study has to be made available to the CAD tool. CONSOLE allows for an easy interfacing of almost any simulator the user has available. To date CONSOLE has already been used successfully in many applications, including the design of controllers for a flexible arm and for a robotic manipulator and the solution of a parameter selection problem for a neural network.

Dynamic optimization case studies in DYNOPT tool

NASA Astrophysics Data System (ADS)

Ozana, Stepan; Pies, Martin; Docekal, Tomas

2016-06-01

Dynamic programming is typically applied to optimization problems. As the analytical solutions are generally very difficult, chosen software tools are used widely. These software packages are often third-party products bound for standard simulation software tools on the market. As typical examples of such tools, TOMLAB and DYNOPT could be effectively applied for solution of problems of dynamic programming. DYNOPT will be presented in this paper due to its licensing policy (free product under GPL) and simplicity of use. DYNOPT is a set of MATLAB functions for determination of optimal control trajectory by given description of the process, the cost to be minimized, subject to equality and inequality constraints, using orthogonal collocation on finite elements method. The actual optimal control problem is solved by complete parameterization both the control and the state profile vector. It is assumed, that the optimized dynamic model may be described by a set of ordinary differential equations (ODEs) or differential-algebraic equations (DAEs). This collection of functions extends the capability of the MATLAB Optimization Tool-box. The paper will introduce use of DYNOPT in the field of dynamic optimization problems by means of case studies regarding chosen laboratory physical educational models.

Modeling the Environmental Impact of Air Traffic Operations

NASA Technical Reports Server (NTRS)

Chen, Neil

2011-01-01

There is increased interest to understand and mitigate the impacts of air traffic on the climate, since greenhouse gases, nitrogen oxides, and contrails generated by air traffic can have adverse impacts on the climate. The models described in this presentation are useful for quantifying these impacts and for studying alternative environmentally aware operational concepts. These models have been developed by leveraging and building upon existing simulation and optimization techniques developed for the design of efficient traffic flow management strategies. Specific enhancements to the existing simulation and optimization techniques include new models that simulate aircraft fuel flow, emissions and contrails. To ensure that these new models are beneficial to the larger climate research community, the outputs of these new models are compatible with existing global climate modeling tools like the FAA's Aviation Environmental Design Tool.

A tool for simulating parallel branch-and-bound methods

NASA Astrophysics Data System (ADS)

Golubeva, Yana; Orlov, Yury; Posypkin, Mikhail

2016-01-01

The Branch-and-Bound method is known as one of the most powerful but very resource consuming global optimization methods. Parallel and distributed computing can efficiently cope with this issue. The major difficulty in parallel B&B method is the need for dynamic load redistribution. Therefore design and study of load balancing algorithms is a separate and very important research topic. This paper presents a tool for simulating parallel Branchand-Bound method. The simulator allows one to run load balancing algorithms with various numbers of processors, sizes of the search tree, the characteristics of the supercomputer's interconnect thereby fostering deep study of load distribution strategies. The process of resolution of the optimization problem by B&B method is replaced by a stochastic branching process. Data exchanges are modeled using the concept of logical time. The user friendly graphical interface to the simulator provides efficient visualization and convenient performance analysis.

A Framework for Daylighting Optimization in Whole Buildings with OpenStudio

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

None

2016-08-12

We present a toolkit and workflow for leveraging the OpenStudio (Guglielmetti et al. 2010) platform to perform daylighting analysis and optimization in a whole building energy modeling (BEM) context. We have re-implemented OpenStudio's integrated Radiance and EnergyPlus functionality as an OpenStudio Measure. The OpenStudio Radiance Measure works within the OpenStudio Application and Parametric Analysis Tool, as well as the OpenStudio Server large scale analysis framework, allowing a rigorous daylighting simulation to be performed on a single building model or potentially an entire population of programmatically generated models. The Radiance simulation results can automatically inform the broader building energy model, andmore » provide dynamic daylight metrics as a basis for decision. Through introduction and example, this paper illustrates the utility of the OpenStudio building energy modeling platform to leverage existing simulation tools for integrated building energy performance simulation, daylighting analysis, and reportage.« less

Front panel engineering with CAD simulation tool

NASA Astrophysics Data System (ADS)

Delacour, Jacques; Ungar, Serge; Mathieu, Gilles; Hasna, Guenther; Martinez, Pascal; Roche, Jean-Christophe

1999-04-01

THe progress made recently in display technology covers many fields of application. The specification of radiance, colorimetry and lighting efficiency creates some new challenges for designers. Photometric design is limited by the capability of correctly predicting the result of a lighting system, to save on the costs and time taken to build multiple prototypes or bread board benches. The second step of the research carried out by company OPTIS is to propose an optimization method to be applied to the lighting system, developed in the software SPEOS. The main features of the tool requires include the CAD interface, to enable fast and efficient transfer between mechanical and light design software, the source modeling, the light transfer model and an optimization tool. The CAD interface is mainly a prototype of transfer, which is not the subjects here. Photometric simulation is efficiently achieved by using the measured source encoding and a simulation by the Monte Carlo method. Today, the advantages and the limitations of the Monte Carlo method are well known. The noise reduction requires a long calculation time, which increases with the complexity of the display panel. A successful optimization is difficult to achieve, due to the long calculation time required for each optimization pass including a Monte Carlo simulation. The problem was initially defined as an engineering method of study. The experience shows that good understanding and mastering of the phenomenon of light transfer is limited by the complexity of non sequential propagation. The engineer must call for the help of a simulation and optimization tool. The main point needed to be able to perform an efficient optimization is a quick method for simulating light transfer. Much work has been done in this area and some interesting results can be observed. It must be said that the Monte Carlo method wastes time calculating some results and information which are not required for the needs of the simulation. Low efficiency transfer system cost a lot of lost time. More generally, the light transfer simulation can be treated efficiently when the integrated result is composed of elementary sub results that include quick analytical calculated intersections. The first axis of research appear. The quick integration research and the quick calculation of geometric intersections. The first axis of research brings some general solutions also valid for multi-reflection systems. The second axis requires some deep thinking on the intersection calculation. An interesting way is the subdivision of space in VOXELS. This is an adapted method of 3D division of space according to the objects and their location. An experimental software has been developed to provide a validation of the method. The gain is particularly high in complex systems. An important reduction in the calculation time has been achieved.

Simulation of DKIST solar adaptive optics system

NASA Astrophysics Data System (ADS)

Marino, Jose; Carlisle, Elizabeth; Schmidt, Dirk

2016-07-01

Solar adaptive optics (AO) simulations are a valuable tool to guide the design and optimization process of current and future solar AO and multi-conjugate AO (MCAO) systems. Solar AO and MCAO systems rely on extended object cross-correlating Shack-Hartmann wavefront sensors to measure the wavefront. Accurate solar AO simulations require computationally intensive operations, which have until recently presented a prohibitive computational cost. We present an update on the status of a solar AO and MCAO simulation tool being developed at the National Solar Observatory. The simulation tool is a multi-threaded application written in the C++ language that takes advantage of current large multi-core CPU computer systems and fast ethernet connections to provide accurate full simulation of solar AO and MCAO systems. It interfaces with KAOS, a state of the art solar AO control software developed by the Kiepenheuer-Institut fuer Sonnenphysik, that provides reliable AO control. We report on the latest results produced by the solar AO simulation tool.

Effective Energy Simulation and Optimal Design of Side-lit Buildings with Venetian Blinds

NASA Astrophysics Data System (ADS)

Cheng, Tian

Venetian blinds are popularly used in buildings to control the amount of incoming daylight for improving visual comfort and reducing heat gains in air-conditioning systems. Studies have shown that the proper design and operation of window systems could result in significant energy savings in both lighting and cooling. However, there is no convenient computer tool that allows effective and efficient optimization of the envelope of side-lit buildings with blinds now. Three computer tools, Adeline, DOE2 and EnergyPlus widely used for the above-mentioned purpose have been experimentally examined in this study. Results indicate that the two former tools give unacceptable accuracy due to unrealistic assumptions adopted while the last one may generate large errors in certain conditions. Moreover, current computer tools have to conduct hourly energy simulations, which are not necessary for life-cycle energy analysis and optimal design, to provide annual cooling loads. This is not computationally efficient, particularly not suitable for optimal designing a building at initial stage because the impacts of many design variations and optional features have to be evaluated. A methodology is therefore developed for efficient and effective thermal and daylighting simulations and optimal design of buildings with blinds. Based on geometric optics and radiosity method, a mathematical model is developed to reasonably simulate the daylighting behaviors of venetian blinds. Indoor illuminance at any reference point can be directly and efficiently computed. They have been validated with both experiments and simulations with Radiance. Validation results show that indoor illuminances computed by the new models agree well with the measured data, and the accuracy provided by them is equivalent to that of Radiance. The computational efficiency of the new models is much higher than that of Radiance as well as EnergyPlus. Two new methods are developed for the thermal simulation of buildings. A fast Fourier transform (FFT) method is presented to avoid the root-searching process in the inverse Laplace transform of multilayered walls. Generalized explicit FFT formulae for calculating the discrete Fourier transform (DFT) are developed for the first time. They can largely facilitate the implementation of FFT. The new method also provides a basis for generating the symbolic response factors. Validation simulations show that it can generate the response factors as accurate as the analytical solutions. The second method is for direct estimation of annual or seasonal cooling loads without the need for tedious hourly energy simulations. It is validated by hourly simulation results with DOE2. Then symbolic long-term cooling load can be created by combining the two methods with thermal network analysis. The symbolic long-term cooling load can keep the design parameters of interest as symbols, which is particularly useful for the optimal design and sensitivity analysis. The methodology is applied to an office building in Hong Kong for the optimal design of building envelope. Design variables such as window-to-wall ratio, building orientation, and glazing optical and thermal properties are included in the study. Results show that the selected design values could significantly impact the energy performance of windows, and the optimal design of side-lit buildings could greatly enhance energy savings. The application example also demonstrates that the developed methodology significantly facilitates the optimal building design and sensitivity analysis, and leads to high computational efficiency.

Simulation based optimization on automated fibre placement process

NASA Astrophysics Data System (ADS)

Lei, Shi

2018-02-01

In this paper, a software simulation (Autodesk TruPlan & TruFiber) based method is proposed to optimize the automate fibre placement (AFP) process. Different types of manufacturability analysis are introduced to predict potential defects. Advanced fibre path generation algorithms are compared with respect to geometrically different parts. Major manufacturing data have been taken into consideration prior to the tool paths generation to achieve high success rate of manufacturing.

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

Response simulation and theoretical calibration of a dual-induction resistivity LWD tool

NASA Astrophysics Data System (ADS)

Xu, Wei; Ke, Shi-Zhen; Li, An-Zong; Chen, Peng; Zhu, Jun; Zhang, Wei

2014-03-01

In this paper, responses of a new dual-induction resistivity logging-while-drilling (LWD) tool in 3D inhomogeneous formation models are simulated by the vector finite element method (VFEM), the influences of the borehole, invaded zone, surrounding strata, and tool eccentricity are analyzed, and calibration loop parameters and calibration coefficients of the LWD tool are discussed. The results show that the tool has a greater depth of investigation than that of the existing electromagnetic propagation LWD tools and is more sensitive to azimuthal conductivity. Both deep and medium induction responses have linear relationships with the formation conductivity, considering optimal calibration loop parameters and calibration coefficients. Due to the different depths of investigation and resolution, deep induction and medium induction are affected differently by the formation model parameters, thereby having different correction factors. The simulation results can provide theoretical references for the research and interpretation of the dual-induction resistivity LWD tools.

On-orbit servicing system assessment and optimization methods based on lifecycle simulation under mixed aleatory and epistemic uncertainties

NASA Astrophysics Data System (ADS)

Yao, Wen; Chen, Xiaoqian; Huang, Yiyong; van Tooren, Michel

2013-06-01

To assess the on-orbit servicing (OOS) paradigm and optimize its utilities by taking advantage of its inherent flexibility and responsiveness, the OOS system assessment and optimization methods based on lifecycle simulation under uncertainties are studied. The uncertainty sources considered in this paper include both the aleatory (random launch/OOS operation failure and on-orbit component failure) and the epistemic (the unknown trend of the end-used market price) types. Firstly, the lifecycle simulation under uncertainties is discussed. The chronological flowchart is presented. The cost and benefit models are established, and the uncertainties thereof are modeled. The dynamic programming method to make optimal decision in face of the uncertain events is introduced. Secondly, the method to analyze the propagation effects of the uncertainties on the OOS utilities is studied. With combined probability and evidence theory, a Monte Carlo lifecycle Simulation based Unified Uncertainty Analysis (MCS-UUA) approach is proposed, based on which the OOS utility assessment tool under mixed uncertainties is developed. Thirdly, to further optimize the OOS system under mixed uncertainties, the reliability-based optimization (RBO) method is studied. To alleviate the computational burden of the traditional RBO method which involves nested optimum search and uncertainty analysis, the framework of Sequential Optimization and Mixed Uncertainty Analysis (SOMUA) is employed to integrate MCS-UUA, and the RBO algorithm SOMUA-MCS is developed. Fourthly, a case study on the OOS system for a hypothetical GEO commercial communication satellite is investigated with the proposed assessment tool. Furthermore, the OOS system is optimized with SOMUA-MCS. Lastly, some conclusions are given and future research prospects are highlighted.

Radiometry simulation within the end-to-end simulation tool SENSOR

NASA Astrophysics Data System (ADS)

Wiest, Lorenz; Boerner, Anko

2001-02-01

12 An end-to-end simulation is a valuable tool for sensor system design, development, optimization, testing, and calibration. This contribution describes the radiometry module of the end-to-end simulation tool SENSOR. It features MODTRAN 4.0-based look up tables in conjunction with a cache-based multilinear interpolation algorithm to speed up radiometry calculations. It employs a linear reflectance parameterization to reduce look up table size, considers effects due to the topology of a digital elevation model (surface slope, sky view factor) and uses a reflectance class feature map to assign Lambertian and BRDF reflectance properties to the digital elevation model. The overall consistency of the radiometry part is demonstrated by good agreement between ATCOR 4-retrieved reflectance spectra of a simulated digital image cube and the original reflectance spectra used to simulate this image data cube.

Structural Performance’s Optimally Analysing and Implementing Based on ANSYS Technology

NASA Astrophysics Data System (ADS)

Han, Na; Wang, Xuquan; Yue, Haifang; Sun, Jiandong; Wu, Yongchun

2017-06-01

Computer-aided Engineering (CAE) is a hotspot both in academic field and in modern engineering practice. Analysis System(ANSYS) simulation software for its excellent performance become outstanding one in CAE family, it is committed to the innovation of engineering simulation to help users to shorten the design process, improve product innovation and performance. Aimed to explore a structural performance’s optimally analyzing model for engineering enterprises, this paper introduced CAE and its development, analyzed the necessity for structural optimal analysis as well as the framework of structural optimal analysis on ANSYS Technology, used ANSYS to implement a reinforced concrete slab structural performance’s optimal analysis, which was display the chart of displacement vector and the chart of stress intensity. Finally, this paper compared ANSYS software simulation results with the measured results,expounded that ANSYS is indispensable engineering calculation tools.

Simulation Tool for Dielectric Barrier Discharge Plasma Actuators

NASA Technical Reports Server (NTRS)

Likhanskii, Alexander

2014-01-01

Traditional approaches for active flow separation control using dielectric barrier discharge (DBD) plasma actuators are limited to relatively low speed flows and atmospheric conditions. This results in low feasibility of the DBDs for aerospace applications. For active flow control at turbine blades, fixed wings, and rotary wings and on hypersonic vehicles, DBD plasma actuators must perform at a wide range of conditions, including rarified flows and combustion mixtures. An efficient, comprehensive, physically based DBD simulation tool can optimize DBD plasma actuators for different operation conditions. Researchers are developing a DBD plasma actuator simulation tool for a wide range of ambient gas pressures. The tool will treat DBD using either kinetic, fluid, or hybrid models, depending on the DBD operational condition.

Resolving Off-Nominal Situations in Schedule-Based Terminal Area Operations: Results from a Human-in-the-Loop Simulation

NASA Technical Reports Server (NTRS)

Mercer, Joey; Callantine, Todd; Martin, Lynne

2012-01-01

A recent human-in-the-loop simulation in the Airspace Operations Laboratory (AOL) at NASA's Ames Research Center investigated the robustness of Controller-Managed Spacing (CMS) operations. CMS refers to AOL-developed controller tools and procedures for enabling arrivals to conduct efficient Optimized Profile Descents with sustained high throughput. The simulation provided a rich data set for examining how a traffic management supervisor and terminal-area controller participants used the CMS tools and coordinated to respond to off-nominal events. This paper proposes quantitative measures for characterizing the participants responses. Case studies of go-around events, replicated during the simulation, provide insights into the strategies employed and the role the CMS tools played in supporting them.

Optimization as a Tool for Consistency Maintenance in Multi-Resolution Simulation

NASA Technical Reports Server (NTRS)

Drewry, Darren T; Reynolds, Jr , Paul F; Emanuel, William R

2006-01-01

The need for new approaches to the consistent simulation of related phenomena at multiple levels of resolution is great. While many fields of application would benefit from a complete and approachable solution to this problem, such solutions have proven extremely difficult. We present a multi-resolution simulation methodology that uses numerical optimization as a tool for maintaining external consistency between models of the same phenomena operating at different levels of temporal and/or spatial resolution. Our approach follows from previous work in the disparate fields of inverse modeling and spacetime constraint-based animation. As a case study, our methodology is applied to two environmental models of forest canopy processes that make overlapping predictions under unique sets of operating assumptions, and which execute at different temporal resolutions. Experimental results are presented and future directions are addressed.

Post-Flight Assessment of Low Density Supersonic Decelerator Flight Dynamics Test 2 Simulation

NASA Technical Reports Server (NTRS)

Dutta, Soumyo; Bowes, Angela L.; White, Joseph P.; Striepe, Scott A.; Queen, Eric M.; O'Farrel, Clara; Ivanov, Mark C.

2016-01-01

NASA's Low Density Supersonic Decelerator (LDSD) project conducted its second Supersonic Flight Dynamics Test (SFDT-2) on June 8, 2015. The Program to Optimize Simulated Trajectories II (POST2) was one of the flight dynamics tools used to simulate and predict the flight performance and was a major tool used in the post-flight assessment of the flight trajectory. This paper compares the simulation predictions with the reconstructed trajectory. Additionally, off-nominal conditions seen during flight are modeled in the simulation to reconcile the predictions with flight data. These analyses are beneficial to characterize the results of the flight test and to improve the simulation and targeting of the subsequent LDSD flights.

Optimized path planning for soft tissue resection via laser vaporization

NASA Astrophysics Data System (ADS)

Ross, Weston; Cornwell, Neil; Tucker, Matthew; Mann, Brian; Codd, Patrick

2018-02-01

Robotic and robotic-assisted surgeries are becoming more prevalent with the promise of improving surgical outcomes through increased precision, reduced operating times, and minimally invasive procedures. The handheld laser scalpel in neurosurgery has been shown to provide a more gentle approach to tissue manipulation on or near critical structures over classical tooling, though difficulties of control have prevented large scale adoption of the tool. This paper presents a novel approach to generating a cutting path for the volumetric resection of tissue using a computer-guided laser scalpel. A soft tissue ablation simulator is developed and used in conjunction with an optimization routine to select parameters which maximize the total resection of target tissue while minimizing the damage to surrounding tissue. The simulator predicts the ablative properties of tissue from an interrogation cut for tuning and simulates the removal of a tumorous tissue embedded on the surface of healthy tissue using a laser scalpel. We demonstrate the ability to control depth and smoothness of cut using genetic algorithms to optimize the ablation parameters and cutting path. The laser power level, cutting rate and spacing between cuts are optimized over multiple surface cuts to achieve the desired resection volumes.

Analysis and simulation tools for solar array power systems

NASA Astrophysics Data System (ADS)

Pongratananukul, Nattorn

This dissertation presents simulation tools developed specifically for the design of solar array power systems. Contributions are made in several aspects of the system design phases, including solar source modeling, system simulation, and controller verification. A tool to automate the study of solar array configurations using general purpose circuit simulators has been developed based on the modeling of individual solar cells. Hierarchical structure of solar cell elements, including semiconductor properties, allows simulation of electrical properties as well as the evaluation of the impact of environmental conditions. A second developed tool provides a co-simulation platform with the capability to verify the performance of an actual digital controller implemented in programmable hardware such as a DSP processor, while the entire solar array including the DC-DC power converter is modeled in software algorithms running on a computer. This "virtual plant" allows developing and debugging code for the digital controller, and also to improve the control algorithm. One important task in solar arrays is to track the maximum power point on the array in order to maximize the power that can be delivered. Digital controllers implemented with programmable processors are particularly attractive for this task because sophisticated tracking algorithms can be implemented and revised when needed to optimize their performance. The proposed co-simulation tools are thus very valuable in developing and optimizing the control algorithm, before the system is built. Examples that demonstrate the effectiveness of the proposed methodologies are presented. The proposed simulation tools are also valuable in the design of multi-channel arrays. In the specific system that we have designed and tested, the control algorithm is implemented on a single digital signal processor. In each of the channels the maximum power point is tracked individually. In the prototype we built, off-the-shelf commercial DC-DC converters were utilized. At the end, the overall performance of the entire system was evaluated using solar array simulators capable of simulating various I-V characteristics, and also by using an electronic load. Experimental results are presented.

An Overview of Importance Splitting for Rare Event Simulation

ERIC Educational Resources Information Center

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

2010-01-01

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

Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

NASA Astrophysics Data System (ADS)

Chiadamrong, N.; Piyathanavong, V.

2017-12-01

Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

Predictive optimal control of sewer networks using CORAL tool: application to Riera Blanca catchment in Barcelona.

PubMed

Puig, V; Cembrano, G; Romera, J; Quevedo, J; Aznar, B; Ramón, G; Cabot, J

2009-01-01

This paper deals with the global control of the Riera Blanca catchment in the Barcelona sewer network using a predictive optimal control approach. This catchment has been modelled using a conceptual modelling approach based on decomposing the catchments in subcatchments and representing them as virtual tanks. This conceptual modelling approach allows real-time model calibration and control of the sewer network. The global control problem of the Riera Blanca catchment is solved using a optimal/predictive control algorithm. To implement the predictive optimal control of the Riera Blanca catchment, a software tool named CORAL is used. The on-line control is simulated by interfacing CORAL with a high fidelity simulator of sewer networks (MOUSE). CORAL interchanges readings from the limnimeters and gate commands with MOUSE as if it was connected with the real SCADA system. Finally, the global control results obtained using the predictive optimal control are presented and compared against the results obtained using current local control system. The results obtained using the global control are very satisfactory compared to those obtained using the local control.

Mathematical simulation and optimization of cutting mode in turning of workpieces made of nickel-based heat-resistant alloy

NASA Astrophysics Data System (ADS)

Bogoljubova, M. N.; Afonasov, A. I.; Kozlov, B. N.; Shavdurov, D. E.

2018-05-01

A predictive simulation technique of optimal cutting modes in the turning of workpieces made of nickel-based heat-resistant alloys, different from the well-known ones, is proposed. The impact of various factors on the cutting process with the purpose of determining optimal parameters of machining in concordance with certain effectiveness criteria is analyzed in the paper. A mathematical model of optimization, algorithms and computer programmes, visual graphical forms reflecting dependences of the effectiveness criteria – productivity, net cost, and tool life on parameters of the technological process - have been worked out. A nonlinear model for multidimensional functions, “solution of the equation with multiple unknowns”, “a coordinate descent method” and heuristic algorithms are accepted to solve the problem of optimization of cutting mode parameters. Research shows that in machining of workpieces made from heat-resistant alloy AISI N07263, the highest possible productivity will be achieved with the following parameters: cutting speed v = 22.1 m/min., feed rate s=0.26 mm/rev; tool life T = 18 min.; net cost – 2.45 per hour.

Optimization of the MINERVA Exoplanet Search Strategy via Simulations

NASA Astrophysics Data System (ADS)

Nava, Chantell; Johnson, Samson; McCrady, Nate; Minerva

2015-01-01

Detection of low-mass exoplanets requires high spectroscopic precision and high observational cadence. MINERVA is a dedicated observatory capable of sub meter-per-second radial velocity precision. As a dedicated observatory, MINERVA can observe with every-clear-night cadence that is essential for low-mass exoplanet detection. However, this cadence complicates the determination of an optimal observing strategy. We simulate MINERVA observations to optimize our observing strategy and maximize exoplanet detections. A dispatch scheduling algorithm provides observations of MINERVA targets every day over a three-year observing campaign. An exoplanet population with a distribution informed by Kepler statistics is assigned to the targets, and radial velocity curves induced by the planets are constructed. We apply a correlated noise model that realistically simulates stellar astrophysical noise sources. The simulated radial velocity data is fed to the MINERVA planet detection code and the expected exoplanet yield is calculated. The full simulation provides a tool to test different strategies for scheduling observations of our targets and optimizing the MINERVA exoplanet search strategy.

Assessing the potential of economic instruments for managing drought risk at river basin scale

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, M.; Lopez-Nicolas, A.; Macian-Sorribes, H.

2015-12-01

Economic instruments work as incentives to adapt individual decisions to collectively agreed goals. Different types of economic instruments have been applied to manage water resources, such as water-related taxes and charges (water pricing, environmental taxes, etc.), subsidies, markets or voluntary agreements. Hydroeconomic models (HEM) provide useful insight on optimal strategies for coping with droughts by simultaneously analysing engineering, hydrology and economics of water resources management. We use HEMs for evaluating the potential of economic instruments on managing drought risk at river basin scale, considering three criteria for assessing drought risk: reliability, resilience and vulnerability. HEMs allow to calculate water scarcity costs as the economic losses due to water deliveries below the target demands, which can be used as a vulnerability descriptor of drought risk. Two generic hydroeconomic DSS tools, SIMGAMS and OPTIGAMS ( both programmed in GAMS) have been developed to evaluate water scarcity cost at river basin scale based on simulation and optimization approaches. The simulation tool SIMGAMS allocates water according to the system priorities and operating rules, and evaluate the scarcity costs using economic demand functions. The optimization tool allocates water resources for maximizing net benefits (minimizing total water scarcity plus operating cost of water use). SIMGAS allows to simulate incentive water pricing policies based on water availability in the system (scarcity pricing), while OPTIGAMS is used to simulate the effect of ideal water markets by economic optimization. These tools have been applied to the Jucar river system (Spain), highly regulated and with high share of water use for crop irrigation (greater than 80%), where water scarcity, irregular hydrology and groundwater overdraft cause droughts to have significant economic, social and environmental consequences. An econometric model was first used to explain the variation of the production value of irrigated agriculture during droughts, assessing revenue responses to varying crop prices and water availability. Hydroeconomic approaches were then used to show the potential of economic instruments in setting incentives for a more efficient management of water resources systems.

Optimization of a Nucleic Acids united-RESidue 2-Point model (NARES-2P) with a maximum-likelihood approach

NASA Astrophysics Data System (ADS)

He, Yi; Liwo, Adam; Scheraga, Harold A.

2015-12-01

Coarse-grained models are useful tools to investigate the structural and thermodynamic properties of biomolecules. They are obtained by merging several atoms into one interaction site. Such simplified models try to capture as much as possible information of the original biomolecular system in all-atom representation but the resulting parameters of these coarse-grained force fields still need further optimization. In this paper, a force field optimization method, which is based on maximum-likelihood fitting of the simulated to the experimental conformational ensembles and least-squares fitting of the simulated to the experimental heat-capacity curves, is applied to optimize the Nucleic Acid united-RESidue 2-point (NARES-2P) model for coarse-grained simulations of nucleic acids recently developed in our laboratory. The optimized NARES-2P force field reproduces the structural and thermodynamic data of small DNA molecules much better than the original force field.

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.

Optimization of IBF parameters based on adaptive tool-path algorithm

NASA Astrophysics Data System (ADS)

Deng, Wen Hui; Chen, Xian Hua; Jin, Hui Liang; Zhong, Bo; Hou, Jin; Li, An Qi

2018-03-01

As a kind of Computer Controlled Optical Surfacing(CCOS) technology. Ion Beam Figuring(IBF) has obvious advantages in the control of surface accuracy, surface roughness and subsurface damage. The superiority and characteristics of IBF in optical component processing are analyzed from the point of view of removal mechanism. For getting more effective and automatic tool path with the information of dwell time, a novel algorithm is proposed in this thesis. Based on the removal functions made through our IBF equipment and the adaptive tool-path, optimized parameters are obtained through analysis the residual error that would be created in the polishing process. A Φ600 mm plane reflector element was used to be a simulation instance. The simulation result shows that after four combinations of processing, the surface accuracy of PV (Peak Valley) value and the RMS (Root Mean Square) value was reduced to 4.81 nm and 0.495 nm from 110.22 nm and 13.998 nm respectively in the 98% aperture. The result shows that the algorithm and optimized parameters provide a good theoretical for high precision processing of IBF.

CAD tools for detector design

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

Womersley, J.; DiGiacomo, N.; Killian, K.

1990-04-01

Detailed detector design has traditionally been divided between engineering optimization for structural integrity and subsequent physicist evaluation. The availability of CAD systems for engineering design enables the tasks to be integrated by providing tools for particle simulation within the CAD system. We believe this will speed up detector design and avoid problems due to the late discovery of shortcomings in the detector. This could occur because of the slowness of traditional verification techniques (such as detailed simulation with GEANT). One such new particle simulation tool is described. It is being used with the I-DEAS CAD package for SSC detector designmore » at Martin-Marietta Astronautics and is to be released through the SSC Laboratory.« less

Planning Under Uncertainty: Methods and Applications

DTIC Science & Technology

2010-06-09

begun research into fundamental algorithms for optimization and re?optimization of continuous optimization problems (such as linear and quadratic... algorithm yields a 14.3% improvement over the original design while saving 68.2 % of the simulation evaluations compared to standard sample-path...They provide tools for building and justifying computational algorithms for such problems. Year. 2010 Month: 03 Final Research under this grant

Reconstruction of a piecewise constant conductivity on a polygonal partition via shape optimization in EIT

NASA Astrophysics Data System (ADS)

Beretta, Elena; Micheletti, Stefano; Perotto, Simona; Santacesaria, Matteo

2018-01-01

In this paper, we develop a shape optimization-based algorithm for the electrical impedance tomography (EIT) problem of determining a piecewise constant conductivity on a polygonal partition from boundary measurements. The key tool is to use a distributed shape derivative of a suitable cost functional with respect to movements of the partition. Numerical simulations showing the robustness and accuracy of the method are presented for simulated test cases in two dimensions.

Simulation-Based Evaluation of Learning Sequences for Instructional Technologies

ERIC Educational Resources Information Center

McEneaney, John E.

2016-01-01

Instructional technologies critically depend on systematic design, and learning hierarchies are a commonly advocated tool for designing instructional sequences. But hierarchies routinely allow numerous sequences and choosing an optimal sequence remains an unsolved problem. This study explores a simulation-based approach to modeling learning…

Grayscale Optical Correlator Workbench

NASA Technical Reports Server (NTRS)

Hanan, Jay; Zhou, Hanying; Chao, Tien-Hsin

2006-01-01

Grayscale Optical Correlator Workbench (GOCWB) is a computer program for use in automatic target recognition (ATR). GOCWB performs ATR with an accurate simulation of a hardware grayscale optical correlator (GOC). This simulation is performed to test filters that are created in GOCWB. Thus, GOCWB can be used as a stand-alone ATR software tool or in combination with GOC hardware for building (target training), testing, and optimization of filters. The software is divided into three main parts, denoted filter, testing, and training. The training part is used for assembling training images as input to a filter. The filter part is used for combining training images into a filter and optimizing that filter. The testing part is used for testing new filters and for general simulation of GOC output. The current version of GOCWB relies on the mathematical software tools from MATLAB binaries for performing matrix operations and fast Fourier transforms. Optimization of filters is based on an algorithm, known as OT-MACH, in which variables specified by the user are parameterized and the best filter is selected on the basis of an average result for correct identification of targets in multiple test images.

Recycling production designs: the value of coordination and flexibility in aluminum recycling operations

NASA Astrophysics Data System (ADS)

Brommer, Tracey H.

The growing motivation for aluminum recycling has prompted interest in recycling alternative and more challenging secondary materials. The nature of these alternative secondary materials necessitates the development of an intermediate recycling facility that can reprocess the secondary materials into a liquid product Two downstream aluminum remelters will incorporate the liquid products into their aluminum alloy production schedules. Energy and environmental benefits result from delivering the products as liquid but coordination challenges persist because of the energy cost to maintain the liquid. Further coordination challenges result from the necessity to establish a long term recycling production plan in the presence of long term downstream aluminum remelter production uncertainty and inherent variation in the daily order schedule of the downstream aluminum remelters. In this context a fundamental question arises, considering the metallurgical complexities of dross reprocessing, what is the value of operating a coordinated set of by-product reprocessing plants and remelting cast houses? A methodology is presented to calculate the optimal recycling center production parameters including 1) the number of recycled products, 2) the volume of recycled products, 3) allocation of recycled materials across recycled products, 4) allocation of recycled products across finished alloys, 4) the level of flexibility for the recycling center to operate. The methods implemented include, 1) an optimization model to describe the long term operations of the recycling center, 2) an uncertainty simulation tool, 3) a simulation optimization method, 4) a dynamic simulation tool with four embedded daily production optimization models of varying degrees of flexibility. This methodology is used to quantify the performance of several recycling center production designs of varying levels of coordination and flexibility. This analysis allowed the identification of the optimal recycling center production design based on maximizing liquid recycled product incorporation and minimizing cast sows. The long term production optimization model was used to evaluate the theoretical viability of the proposed two stage scrap and aluminum dross reprocessing operation including the impact of reducing coordination on model performance. Reducing the coordination between the recycling center and downstream remelters by reducing the number of recycled products from ten to five resulted in only 1.3% less secondary materials incorporated into downstream production. The dynamic simulation tool was used to evaluate the performance of the calculated recycling center production plan when resolved on a daily timeframe for varying levels of operational flexibility. The dynamic simulation revealed the optimal performance corresponded to the fixed recipe with flexible production daily optimization model formulation. Calculating recycled product characteristics using the proposed simulation optimization method increased profitability in cases of uncertain downstream remelter production and expensive aluminum dross and post-consumed secondary materials. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM (1,1) model.

PubMed

An, Yan; Zou, Zhihong; Zhao, Yanfei

2015-03-01

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet (China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting. Copyright © 2015. Published by Elsevier B.V.

Seasonal-Scale Optimization of Conventional Hydropower Operations in the Upper Colorado System

NASA Astrophysics Data System (ADS)

Bier, A.; Villa, D.; Sun, A.; Lowry, T. S.; Barco, J.

2011-12-01

Sandia National Laboratories is developing the Hydropower Seasonal Concurrent Optimization for Power and the Environment (Hydro-SCOPE) tool to examine basin-wide conventional hydropower operations at seasonal time scales. This tool is part of an integrated, multi-laboratory project designed to explore different aspects of optimizing conventional hydropower operations. The Hydro-SCOPE tool couples a one-dimensional reservoir model with a river routing model to simulate hydrology and water quality. An optimization engine wraps around this model framework to solve for long-term operational strategies that best meet the specific objectives of the hydrologic system while honoring operational and environmental constraints. The optimization routines are provided by Sandia's open source DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) software. Hydro-SCOPE allows for multi-objective optimization, which can be used to gain insight into the trade-offs that must be made between objectives. The Hydro-SCOPE tool is being applied to the Upper Colorado Basin hydrologic system. This system contains six reservoirs, each with its own set of objectives (such as maximizing revenue, optimizing environmental indicators, meeting water use needs, or other objectives) and constraints. This leads to a large optimization problem with strong connectedness between objectives. The systems-level approach used by the Hydro-SCOPE tool allows simultaneous analysis of these objectives, as well as understanding of potential trade-offs related to different objectives and operating strategies. The seasonal-scale tool will be tightly integrated with the other components of this project, which examine day-ahead and real-time planning, environmental performance, hydrologic forecasting, and plant efficiency.

Uncertainty-based simulation-optimization using Gaussian process emulation: Application to coastal groundwater management

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ketabchi, Hamed

2017-12-01

Combined simulation-optimization (S/O) schemes have long been recognized as a valuable tool in coastal groundwater management (CGM). However, previous applications have mostly relied on deterministic seawater intrusion (SWI) simulations. This is a questionable simplification, knowing that SWI models are inevitably prone to epistemic and aleatory uncertainty, and hence a management strategy obtained through S/O without consideration of uncertainty may result in significantly different real-world outcomes than expected. However, two key issues have hindered the use of uncertainty-based S/O schemes in CGM, which are addressed in this paper. The first issue is how to solve the computational challenges resulting from the need to perform massive numbers of simulations. The second issue is how the management problem is formulated in presence of uncertainty. We propose the use of Gaussian process (GP) emulation as a valuable tool in solving the computational challenges of uncertainty-based S/O in CGM. We apply GP emulation to the case study of Kish Island (located in the Persian Gulf) using an uncertainty-based S/O algorithm which relies on continuous ant colony optimization and Monte Carlo simulation. In doing so, we show that GP emulation can provide an acceptable level of accuracy, with no bias and low statistical dispersion, while tremendously reducing the computational time. Moreover, five new formulations for uncertainty-based S/O are presented based on concepts such as energy distances, prediction intervals and probabilities of SWI occurrence. We analyze the proposed formulations with respect to their resulting optimized solutions, the sensitivity of the solutions to the intended reliability levels, and the variations resulting from repeated optimization runs.

Data-Driven Modeling and Rendering of Force Responses from Elastic Tool Deformation

PubMed Central

Rakhmatov, Ruslan; Ogay, Tatyana; Jeon, Seokhee

2018-01-01

This article presents a new data-driven model design for rendering force responses from elastic tool deformation. The new design incorporates a six-dimensional input describing the initial position of the contact, as well as the state of the tool deformation. The input-output relationship of the model was represented by a radial basis functions network, which was optimized based on training data collected from real tool-surface contact. Since the input space of the model is represented in the local coordinate system of a tool, the model is independent of recording and rendering devices and can be easily deployed to an existing simulator. The model also supports complex interactions, such as self and multi-contact collisions. In order to assess the proposed data-driven model, we built a custom data acquisition setup and developed a proof-of-concept rendering simulator. The simulator was evaluated through numerical and psychophysical experiments with four different real tools. The numerical evaluation demonstrated the perceptual soundness of the proposed model, meanwhile the user study revealed the force feedback of the proposed simulator to be realistic. PMID:29342964

Optimal implementation of best management practices to improve agricultural hydrology and water quality

NASA Astrophysics Data System (ADS)

Liu, Y.; Engel, B.; Collingsworth, P.; Pijanowski, B. C.

2017-12-01

Nutrient loading from the Maumee River watershed is a significant reason for the harmful algal blooms (HABs) problem in Lake Erie. Strategies to reduce nutrient loading from agricultural areas in the Maumee River watershed need to be explored. Best management practices (BMPs) are popular approaches for improving hydrology and water quality. Various scenarios of BMP implementation were simulated in the AXL watershed (an agricultural watershed in Maumee River watershed) using Soil and Water Assessment Tool (SWAT) and a new BMP cost tool to explore the cost-effectiveness of the practices. BMPs of interest included vegetative filter strips, grassed waterways, blind inlets, grade stabilization structures, wetlands, no-till, nutrient management, residue management, and cover crops. The following environmental concerns were considered: streamflow, Total Phosphorous (TP), Dissolved Reactive Phosphorus (DRP), Total Kjeldahl Nitrogen (TKN), and Nitrate+Nitrite (NOx). To obtain maximum hydrological and water quality benefits with minimum cost, an optimization tool was developed to optimally select and place BMPs by connecting SWAT, the BMP cost tool, and optimization algorithms. The optimization tool was then applied in AXL watershed to explore optimization focusing on critical areas (top 25% of areas with highest runoff volume/pollutant loads per area) vs. all areas of the watershed, optimization using weather data for spring (March to July, due to the goal of reducing spring phosphorus in watershed management plan) vs. full year, and optimization results of implementing BMPs to achieve the watershed management plan goal (reducing 2008 TP levels by 40%). The optimization tool and BMP optimization results can be used by watershed groups and communities to solve hydrology and water quality problems.

A Novel Automatic Phase Selection Device: Design and Optimization

NASA Astrophysics Data System (ADS)

Zhang, Feng; Li, Haitao; Li, Na; Zhang, Nan; Lv, Wei; Cui, Xiaojiang

2018-01-01

At present, AICD completion is an effective way to slow down the bottom water cone. Effective extension of the period without water production. According on the basis of investigating the AICD both at home and abroad, this paper designed a new type of AICD, and with the help of fluid numerical simulation software, the internal flow field was analysed, and its structure is optimized. The simulation results show that the tool can restrict the flow of water well, and the flow of oil is less.

Adaptive smart simulator for characterization and MPPT construction of PV array

NASA Astrophysics Data System (ADS)

Ouada, Mehdi; Meridjet, Mohamed Salah; Dib, Djalel

2016-07-01

Partial shading conditions are among the most important problems in large photovoltaic array. Many works of literature are interested in modeling, control and optimization of photovoltaic conversion of solar energy under partial shading conditions, The aim of this study is to build a software simulator similar to hard simulator and to produce a shading pattern of the proposed photovoltaic array in order to use the delivered information to obtain an optimal configuration of the PV array and construct MPPT algorithm. Graphical user interfaces (Matlab GUI) are built using a developed script, this tool is easy to use, simple, and has a rapid of responsiveness, the simulator supports large array simulations that can be interfaced with MPPT and power electronic converters.

Chapter 8: Planning Tools to Simulate and Optimize Neighborhood Energy Systems

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

Zhivov, Alexander Michael; Case, Michael Patrick; Jank, Reinhard

This section introduces different energy modeling tools available in Europe and the USA for community energy master planning process varying from strategic Urban Energy Planning to more detailed Local Energy Planning. Two modeling tools used for Energy Master Planning of primarily residential communities, the 3D city model with CityGML, and the Net Zero Planner tool developed for the US Department of Defense installations are described in more details.

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

DOE PAGES

Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; ...

2015-11-09

Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here in this paper, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive.

A fast ultrasonic simulation tool based on massively parallel implementations

NASA Astrophysics Data System (ADS)

Lambert, Jason; Rougeron, Gilles; Lacassagne, Lionel; Chatillon, Sylvain

2014-02-01

This paper presents a CIVA optimized ultrasonic inspection simulation tool, which takes benefit of the power of massively parallel architectures: graphical processing units (GPU) and multi-core general purpose processors (GPP). This tool is based on the classical approach used in CIVA: the interaction model is based on Kirchoff, and the ultrasonic field around the defect is computed by the pencil method. The model has been adapted and parallelized for both architectures. At this stage, the configurations addressed by the tool are : multi and mono-element probes, planar specimens made of simple isotropic materials, planar rectangular defects or side drilled holes of small diameter. Validations on the model accuracy and performances measurements are presented.

Development of a multiobjective optimization tool for the selection and placement of best management practices for nonpoint source pollution control

NASA Astrophysics Data System (ADS)

Maringanti, Chetan; Chaubey, Indrajeet; Popp, Jennie

2009-06-01

Best management practices (BMPs) are effective in reducing the transport of agricultural nonpoint source pollutants to receiving water bodies. However, selection of BMPs for placement in a watershed requires optimization of the available resources to obtain maximum possible pollution reduction. In this study, an optimization methodology is developed to select and place BMPs in a watershed to provide solutions that are both economically and ecologically effective. This novel approach develops and utilizes a BMP tool, a database that stores the pollution reduction and cost information of different BMPs under consideration. The BMP tool replaces the dynamic linkage of the distributed parameter watershed model during optimization and therefore reduces the computation time considerably. Total pollutant load from the watershed, and net cost increase from the baseline, were the two objective functions minimized during the optimization process. The optimization model, consisting of a multiobjective genetic algorithm (NSGA-II) in combination with a watershed simulation tool (Soil Water and Assessment Tool (SWAT)), was developed and tested for nonpoint source pollution control in the L'Anguille River watershed located in eastern Arkansas. The optimized solutions provided a trade-off between the two objective functions for sediment, phosphorus, and nitrogen reduction. The results indicated that buffer strips were very effective in controlling the nonpoint source pollutants from leaving the croplands. The optimized BMP plans resulted in potential reductions of 33%, 32%, and 13% in sediment, phosphorus, and nitrogen loads, respectively, from the watershed.

Comparison of Low-Thrust Control Laws for Application in Planetocentric Space

NASA Technical Reports Server (NTRS)

Falck, Robert D.; Sjauw, Waldy K.; Smith, David A.

2014-01-01

Recent interest at NASA for the application of solar electric propulsion for the transfer of significant payloads in cislunar space has led to the development of high-fidelity simulations of such missions. With such transfers involving transfer times on the order of months, simulation time can be significant. In the past, the examination of such missions typically began with the use of lower-fidelity trajectory optimization tools such as SEPSPOT to develop and tune guidance laws which delivered optimal or near- optimal trajectories, where optimal is generally defined as minimizing propellant expenditure or time of flight. The transfer of these solutions to a high-fidelity simulation is typically an iterative process whereby the initial solution may nearly, but not precisely, meet mission objectives. Further tuning of the guidance algorithm is typically necessary when accounting for high-fidelity perturbations such as those due to more detailed gravity models, secondary-body effects, solar radiation pressure, etc. While trajectory optimization is a useful method for determining optimal performance metrics, algorithms which deliver nearly optimal performance with minimal tuning are an attractive alternative.

Optimization and validation of moving average quality control procedures using bias detection curves and moving average validation charts.

PubMed

van Rossum, Huub H; Kemperman, Hans

2017-02-01

To date, no practical tools are available to obtain optimal settings for moving average (MA) as a continuous analytical quality control instrument. Also, there is no knowledge of the true bias detection properties of applied MA. We describe the use of bias detection curves for MA optimization and MA validation charts for validation of MA. MA optimization was performed on a data set of previously obtained consecutive assay results. Bias introduction and MA bias detection were simulated for multiple MA procedures (combination of truncation limits, calculation algorithms and control limits) and performed for various biases. Bias detection curves were generated by plotting the median number of test results needed for bias detection against the simulated introduced bias. In MA validation charts the minimum, median, and maximum numbers of assay results required for MA bias detection are shown for various bias. Their use was demonstrated for sodium, potassium, and albumin. Bias detection curves allowed optimization of MA settings by graphical comparison of bias detection properties of multiple MA. The optimal MA was selected based on the bias detection characteristics obtained. MA validation charts were generated for selected optimal MA and provided insight into the range of results required for MA bias detection. Bias detection curves and MA validation charts are useful tools for optimization and validation of MA procedures.

A flexible, interactive software tool for fitting the parameters of neuronal models.

PubMed

Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs

2014-01-01

The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool.

A flexible, interactive software tool for fitting the parameters of neuronal models

PubMed Central

Friedrich, Péter; Vella, Michael; Gulyás, Attila I.; Freund, Tamás F.; Káli, Szabolcs

2014-01-01

The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool. PMID:25071540

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

NASA Astrophysics Data System (ADS)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU evaluate tradeoffs in a continually changing world.

Numerical Simulations of SCR DeNOx System for a 660MW coal-fired power station

NASA Astrophysics Data System (ADS)

Yongqiang, Deng; Zhongming, Mei; Yijun, Mao; Nianping, Liu; Guoming, Yin

2018-06-01

Aimed at the selective catalytic reduction (SCR) DeNOx system of a 660 MW coal-fired power station, which is limited by low denitrification efficiency, large ammonia consumption and over-high ammonia escape rate, numerical simulations were conducted by employing STAR-CCM+ (CFD tool). The simulations results revealed the problems existed in the SCR DeNOx system. Aimed at limitations of the target SCR DeNOx system, factors affecting the denitrification performance of SCR, including the structural parameters and ammonia injected by the ammonia nozzles, were optimized. Under the optimized operational conditions, the denitrification efficiency of the SCR system was enhanced, while the ammonia escape rate was reduced below 3ppm. This study serves as references for optimization and modification of SCR systems.

Performance analysis and optimization of an advanced pharmaceutical wastewater treatment plant through a visual basic software tool (PWWT.VB).

PubMed

Pal, Parimal; Thakura, Ritwik; Chakrabortty, Sankha

2016-05-01

A user-friendly, menu-driven simulation software tool has been developed for the first time to optimize and analyze the system performance of an advanced continuous membrane-integrated pharmaceutical wastewater treatment plant. The software allows pre-analysis and manipulation of input data which helps in optimization and shows the software performance visually on a graphical platform. Moreover, the software helps the user to "visualize" the effects of the operating parameters through its model-predicted output profiles. The software is based on a dynamic mathematical model, developed for a systematically integrated forward osmosis-nanofiltration process for removal of toxic organic compounds from pharmaceutical wastewater. The model-predicted values have been observed to corroborate well with the extensive experimental investigations which were found to be consistent under varying operating conditions like operating pressure, operating flow rate, and draw solute concentration. Low values of the relative error (RE = 0.09) and high values of Willmott-d-index (d will = 0.981) reflected a high degree of accuracy and reliability of the software. This software is likely to be a very efficient tool for system design or simulation of an advanced membrane-integrated treatment plant for hazardous wastewater.

Development and use of mathematical models and software frameworks for integrated analysis of agricultural systems and associated water use impacts

USGS Publications Warehouse

Fowler, K. R.; Jenkins, E.W.; Parno, M.; Chrispell, J.C.; Colón, A. I.; Hanson, Randall T.

2016-01-01

The development of appropriate water management strategies requires, in part, a methodology for quantifying and evaluating the impact of water policy decisions on regional stakeholders. In this work, we describe the framework we are developing to enhance the body of resources available to policy makers, farmers, and other community members in their e orts to understand, quantify, and assess the often competing objectives water consumers have with respect to usage. The foundation for the framework is the construction of a simulation-based optimization software tool using two existing software packages. In particular, we couple a robust optimization software suite (DAKOTA) with the USGS MF-OWHM water management simulation tool to provide a flexible software environment that will enable the evaluation of one or multiple (possibly competing) user-defined (or stakeholder) objectives. We introduce the individual software components and outline the communication strategy we defined for the coupled development. We present numerical results for case studies related to crop portfolio management with several defined objectives. The objectives are not optimally satisfied for any single user class, demonstrating the capability of the software tool to aid in the evaluation of a variety of competing interests.

Integrated solar energy system optimization

NASA Astrophysics Data System (ADS)

Young, S. K.

1982-11-01

The computer program SYSOPT, intended as a tool for optimizing the subsystem sizing, performance, and economics of integrated wind and solar energy systems, is presented. The modular structure of the methodology additionally allows simulations when the solar subsystems are combined with conventional technologies, e.g., a utility grid. Hourly energy/mass flow balances are computed for interconnection points, yielding optimized sizing and time-dependent operation of various subsystems. The program requires meteorological data, such as insolation, diurnal and seasonal variations, and wind speed at the hub height of a wind turbine, all of which can be taken from simulations like the TRNSYS program. Examples are provided for optimization of a solar-powered (wind turbine and parabolic trough-Rankine generator) desalinization plant, and a design analysis for a solar powered greenhouse.

Optimization of GATE and PHITS Monte Carlo code parameters for uniform scanning proton beam based on simulation with FLUKA general-purpose code

NASA Astrophysics Data System (ADS)

Kurosu, Keita; Takashina, Masaaki; Koizumi, Masahiko; Das, Indra J.; Moskvin, Vadim P.

2014-10-01

Although three general-purpose Monte Carlo (MC) simulation tools: Geant4, FLUKA and PHITS have been used extensively, differences in calculation results have been reported. The major causes are the implementation of the physical model, preset value of the ionization potential or definition of the maximum step size. In order to achieve artifact free MC simulation, an optimized parameters list for each simulation system is required. Several authors have already proposed the optimized lists, but those studies were performed with a simple system such as only a water phantom. Since particle beams have a transport, interaction and electromagnetic processes during beam delivery, establishment of an optimized parameters-list for whole beam delivery system is therefore of major importance. The purpose of this study was to determine the optimized parameters list for GATE and PHITS using proton treatment nozzle computational model. The simulation was performed with the broad scanning proton beam. The influences of the customizing parameters on the percentage depth dose (PDD) profile and the proton range were investigated by comparison with the result of FLUKA, and then the optimal parameters were determined. The PDD profile and the proton range obtained from our optimized parameters list showed different characteristics from the results obtained with simple system. This led to the conclusion that the physical model, particle transport mechanics and different geometry-based descriptions need accurate customization in planning computational experiments for artifact-free MC simulation.

SU-D-213-03: Towards An Optimized 3D Scintillation Dosimetry Tool for Quality Assurance of Dynamic Radiotherapy Techniques

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

Rilling, M; Centre de Recherche sur le Cancer, Hôtel-Dieu de Québec, Quebec City, QC; Département de radio-oncologie, CHU de Québec, Quebec City, QC

2015-06-15

Purpose: The purpose of this work is to simulate a multi-focus plenoptic camera used as the measuring device in a real-time three-dimensional scintillation dosimeter. Simulating and optimizing this realistic optical system will bridge the technological gap between concept validation and a clinically viable tool that can provide highly efficient, accurate and precise measurements for dynamic radiotherapy techniques. Methods: The experimental prototype, previously developed for proof of concept purposes, uses an off-the-shelf multi-focus plenoptic camera. With an array of interleaved microlenses of different focal lengths, this camera records spatial and angular information of light emitted by a plastic scintillator volume. Themore » three distinct microlens focal lengths were determined experimentally for use as baseline parameters by measuring image-to-object magnification for different distances in object space. A simulated plenoptic system was implemented using the non-sequential ray tracing software Zemax: this tool allows complete simulation of multiple optical paths by modeling interactions at interfaces such as scatter, diffraction, reflection and refraction. The active sensor was modeled based on the camera manufacturer specifications by a 2048×2048, 5 µm-pixel pitch sensor. Planar light sources, simulating the plastic scintillator volume, were employed for ray tracing simulations. Results: The microlens focal lengths were determined to be 384, 327 and 290 µm. A realistic multi-focus plenoptic system, with independently defined and optimizable specifications, was fully simulated. A f/2.9 and 54 mm-focal length Double Gauss objective was modeled as the system’s main lens. A three-focal length hexagonal microlens array of 250-µm thickness was designed, acting as an image-relay system between the main lens and sensor. Conclusion: Simulation of a fully modeled multi-focus plenoptic camera enables the decoupled optimization of the main lens and microlens specifications. This work leads the way to improving the 3D dosimeter’s achievable resolution, efficiency and build for providing a quality assurance tool fully meeting clinical needs. M.R. is financially supported by a Master’s Canada Graduate Scholarship from the NSERC. This research is also supported by the NSERC Industrial Research Chair in Optical Design.« less

Nonlinear Shaping Architecture Designed with Using Evolutionary Structural Optimization Tools

NASA Astrophysics Data System (ADS)

Januszkiewicz, Krystyna; Banachowicz, Marta

2017-10-01

The paper explores the possibilities of using Structural Optimization Tools (ESO) digital tools in an integrated structural and architectural design in response to the current needs geared towards sustainability, combining ecological and economic efficiency. The first part of the paper defines the Evolutionary Structural Optimization tools, which were developed specifically for engineering purposes using finite element analysis as a framework. The development of ESO has led to several incarnations, which are all briefly discussed (Additive ESO, Bi-directional ESO, Extended ESO). The second part presents result of using these tools in structural and architectural design. Actual building projects which involve optimization as a part of the original design process will be presented (Crematorium in Kakamigahara Gifu, Japan, 2006 SANAA“s Learning Centre, EPFL in Lausanne, Switzerland 2008 among others). The conclusion emphasizes that the structural engineering and architectural design mean directing attention to the solutions which are used by Nature, designing works optimally shaped and forming their own environments. Architectural forms never constitute the optimum shape derived through a form-finding process driven only by structural optimization, but rather embody and integrate a multitude of parameters. It might be assumed that there is a similarity between these processes in nature and the presented design methods. Contemporary digital methods make the simulation of such processes possible, and thus enable us to refer back to the empirical methods of previous generations.

Optimal Living Environments for the Elderly: A Design Simulation Approach.

ERIC Educational Resources Information Center

Hoffman, Stephanie B.; And Others

PLANNED AGE (Planned Alternatives for Gerontological Environments) is a consumer/advocate-oriented design simulation package that provides: (a) a medium for user-planner interaction in the design of living and service environments for the aged; (b) an educational, planning, design, and evaluation tool that can be used by the elderly, their…

Multi Infrastructure Control and Optimization Toolkit, Resilient Design Module (MICOT-RDT), version 2.X

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

Bent, Russell; Nagarajan, Harsha; Yamangil, Emre

2016-06-24

MICOT is a tool for optimizing and controlling infrastructure systems. In includes modules for optimizing the operations of an infrastructure structure (for example optimal dispatch), designing infrastructure systems, restoring infrastructures systems, resiliency, preparing for natural disasters, interdicting networks, state estimation, sensor placement, and simulation of infrastructure systems. It implements algorithms developed at LANL that have been published in the academic community. This is a release of the of resilient design module of the MICOT.

Object-Oriented MDAO Tool with Aeroservoelastic Model Tuning Capability

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Li, Wesley; Lung, Shun-fat

2008-01-01

An object-oriented multi-disciplinary analysis and optimization (MDAO) tool has been developed at the NASA Dryden Flight Research Center to automate the design and analysis process and leverage existing commercial as well as in-house codes to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic and hypersonic aircraft. Once the structural analysis discipline is finalized and integrated completely into the MDAO process, other disciplines such as aerodynamics and flight controls will be integrated as well. Simple and efficient model tuning capabilities based on optimization problem are successfully integrated with the MDAO tool. More synchronized all phases of experimental testing (ground and flight), analytical model updating, high-fidelity simulations for model validation, and integrated design may result in reduction of uncertainties in the aeroservoelastic model and increase the flight safety.

Adaptive smart simulator for characterization and MPPT construction of PV array

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

Ouada, Mehdi, E-mail: mehdi.ouada@univ-annaba.org; Meridjet, Mohamed Salah; Dib, Djalel

2016-07-25

Partial shading conditions are among the most important problems in large photovoltaic array. Many works of literature are interested in modeling, control and optimization of photovoltaic conversion of solar energy under partial shading conditions, The aim of this study is to build a software simulator similar to hard simulator and to produce a shading pattern of the proposed photovoltaic array in order to use the delivered information to obtain an optimal configuration of the PV array and construct MPPT algorithm. Graphical user interfaces (Matlab GUI) are built using a developed script, this tool is easy to use, simple, and hasmore » a rapid of responsiveness, the simulator supports large array simulations that can be interfaced with MPPT and power electronic converters.« less

Optimized radiation-hardened erbium doped fiber amplifiers for long space missions

NASA Astrophysics Data System (ADS)

Ladaci, A.; Girard, S.; Mescia, L.; Robin, T.; Laurent, A.; Cadier, B.; Boutillier, M.; Ouerdane, Y.; Boukenter, A.

2017-04-01

In this work, we developed and exploited simulation tools to optimize the performances of rare earth doped fiber amplifiers (REDFAs) for space missions. To describe these systems, a state-of-the-art model based on the rate equations and the particle swarm optimization technique is developed in which we also consider the main radiation effect on REDFA: the radiation induced attenuation (RIA). After the validation of this tool set by confrontation between theoretical and experimental results, we investigate how the deleterious radiation effects on the amplifier performance can be mitigated following adequate strategies to conceive the REDFA architecture. The tool set was validated by comparing the calculated Erbium-doped fiber amplifier (EDFA) gain degradation under X-rays at ˜300 krad(SiO2) with the corresponding experimental results. Two versions of the same fibers were used in this work, a standard optical fiber and a radiation hardened fiber, obtained by loading the previous fiber with hydrogen gas. Based on these fibers, standard and radiation hardened EDFAs were manufactured and tested in different operating configurations, and the obtained data were compared with simulation data done considering the same EDFA structure and fiber properties. This comparison reveals a good agreement between simulated gain and experimental data (<10% as the maximum error for the highest doses). Compared to our previous results obtained on Er/Yb-amplifiers, these results reveal the importance of the photo-bleaching mechanism competing with the RIA that cannot be neglected for the modeling of the radiation-induced gain degradation of EDFAs. This implies to measure in representative conditions the RIA at the pump and signal wavelengths that are used as input parameters for the simulation. The validated numerical codes have then been used to evaluate the potential of some EDFA architecture evolutions in the amplifier performance during the space mission. Optimization of both the fiber length and the EDFA pumping scheme allows us to strongly reduce its radiation vulnerability in terms of gain. The presented approach is a complementary and effective tool for hardening by device techniques and opens new perspectives for the applications of REDFAs and lasers in harsh environments.

Monte Carlo simulations of neutron-scattering instruments using McStas

NASA Astrophysics Data System (ADS)

Nielsen, K.; Lefmann, K.

2000-06-01

Monte Carlo simulations have become an essential tool for improving the performance of neutron-scattering instruments, since the level of sophistication in the design of instruments is defeating purely analytical methods. The program McStas, being developed at Risø National Laboratory, includes an extension language that makes it easy to adapt it to the particular requirements of individual instruments, and thus provides a powerful and flexible tool for constructing such simulations. McStas has been successfully applied in such areas as neutron guide design, flux optimization, non-Gaussian resolution functions of triple-axis spectrometers, and time-focusing in time-of-flight instruments.

A Lunar Surface Operations Simulator

NASA Technical Reports Server (NTRS)

Nayar, H.; Balaram, J.; Cameron, J.; Jain, A.; Lim, C.; Mukherjee, R.; Peters, S.; Pomerantz, M.; Reder, L.; Shakkottai, P.;

Free web-based modelling platform for managed aquifer recharge (MAR) applications

NASA Astrophysics Data System (ADS)

Stefan, Catalin; Junghanns, Ralf; Glaß, Jana; Sallwey, Jana; Fatkhutdinov, Aybulat; Fichtner, Thomas; Barquero, Felix; Moreno, Miguel; Bonilla, José; Kwoyiga, Lydia

2017-04-01

Managed aquifer recharge represents a valuable instrument for sustainable water resources management. The concept implies purposeful infiltration of surface water into underground for later recovery or environmental benefits. Over decades, MAR schemes were successfully installed worldwide for a variety of reasons: to maximize the natural storage capacity of aquifers, physical aquifer management, water quality management, and ecological benefits. The INOWAS-DSS platform provides a collection of free web-based tools for planning, management and optimization of main components of MAR schemes. The tools are grouped into 13 specific applications that cover most relevant challenges encountered at MAR sites, both from quantitative and qualitative perspectives. The applications include among others the optimization of MAR site location, the assessment of saltwater intrusion, the restoration of groundwater levels in overexploited aquifers, the maximization of natural storage capacity of aquifers, the improvement of water quality, the design and operational optimization of MAR schemes, clogging development and risk assessment. The platform contains a collection of about 35 web-based tools of various degrees of complexity, which are either included in application specific workflows or used as standalone modelling instruments. Among them are simple tools derived from data mining and empirical equations, analytical groundwater related equations, as well as complex numerical flow and transport models (MODFLOW, MT3DMS and SEAWAT). Up to now, the simulation core of the INOWAS-DSS, which is based on the finite differences groundwater flow model MODFLOW, is implemented and runs on the web. A scenario analyser helps to easily set up and evaluate new management options as well as future development such as land use and climate change and compare them to previous scenarios. Additionally simple tools such as analytical equations to assess saltwater intrusion are already running online. Besides the simulation tools, a web-based data base is under development where geospatial and time series data can be stored, managed, and processed. Furthermore, a web-based information system containing user guides for the various developed tools and applications as well as basic information on MAR and related topics is published and will be regularly expanded as new tools are getting implemented. The INOWAS-DSS including its simulation tools, data base and information system provides an extensive framework to manage, plan and optimize MAR facilities. As the INOWAS-DSS is an open-source software accessible via the internet using standard web browsers, it offers new ways for data sharing and collaboration among various partners and decision makers.

Open source Modeling and optimization tools for Planning

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

Peles, S.

Open source modeling and optimization tools for planning The existing tools and software used for planning and analysis in California are either expensive, difficult to use, or not generally accessible to a large number of participants. These limitations restrict the availability of participants for larger scale energy and grid studies in the state. The proposed initiative would build upon federal and state investments in open source software, and create and improve open source tools for use in the state planning and analysis activities. Computational analysis and simulation frameworks in development at national labs and universities can be brought forward tomore » complement existing tools. An open source platform would provide a path for novel techniques and strategies to be brought into the larger community and reviewed by a broad set of stakeholders.« less

Ground Contact Model for Mars Science Laboratory Mission Simulations

NASA Technical Reports Server (NTRS)

Raiszadeh, Behzad; Way, David

2012-01-01

The Program to Optimize Simulated Trajectories II (POST 2) has been successful in simulating the flight of launch vehicles and entry bodies on earth and other planets. POST 2 has been the primary simulation tool for the Entry Descent, and Landing (EDL) phase of numerous Mars lander missions such as Mars Pathfinder in 1997, the twin Mars Exploration Rovers (MER-A and MER-B) in 2004, Mars Phoenix lander in 2007, and it is now the main trajectory simulation tool for Mars Science Laboratory (MSL) in 2012. In all previous missions, the POST 2 simulation ended before ground impact, and a tool other than POST 2 simulated landing dynamics. It would be ideal for one tool to simulate the entire EDL sequence, thus avoiding errors that could be introduced by handing off position, velocity, or other fight parameters from one simulation to the other. The desire to have one continuous end-to-end simulation was the motivation for developing the ground interaction model in POST 2. Rover landing, including the detection of the postlanding state, is a very critical part of the MSL mission, as the EDL landing sequence continues for a few seconds after landing. The method explained in this paper illustrates how a simple ground force interaction model has been added to POST 2, which allows simulation of the entire EDL from atmospheric entry through touchdown.

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.

Stimulation of a turbofan engine for evaluation of multivariable optimal control concepts. [(computerized simulation)

NASA Technical Reports Server (NTRS)

Seldner, K.

1976-01-01

The development of control systems for jet engines requires a real-time computer simulation. The simulation provides an effective tool for evaluating control concepts and problem areas prior to actual engine testing. The development and use of a real-time simulation of the Pratt and Whitney F100-PW100 turbofan engine is described. The simulation was used in a multi-variable optimal controls research program using linear quadratic regulator theory. The simulation is used to generate linear engine models at selected operating points and evaluate the control algorithm. To reduce the complexity of the design, it is desirable to reduce the order of the linear model. A technique to reduce the order of the model; is discussed. Selected results between high and low order models are compared. The LQR control algorithms can be programmed on digital computer. This computer will control the engine simulation over the desired flight envelope.

The technique of entropy optimization in motor current signature analysis and its application in the fault diagnosis of gear transmission

NASA Astrophysics Data System (ADS)

Chen, Xiaoguang; Liang, Lin; Liu, Fei; Xu, Guanghua; Luo, Ailing; Zhang, Sicong

2012-05-01

Nowadays, Motor Current Signature Analysis (MCSA) is widely used in the fault diagnosis and condition monitoring of machine tools. However, although the current signal has lower SNR (Signal Noise Ratio), it is difficult to identify the feature frequencies of machine tools from complex current spectrum that the feature frequencies are often dense and overlapping by traditional signal processing method such as FFT transformation. With the study in the Motor Current Signature Analysis (MCSA), it is found that the entropy is of importance for frequency identification, which is associated with the probability distribution of any random variable. Therefore, it plays an important role in the signal processing. In order to solve the problem that the feature frequencies are difficult to be identified, an entropy optimization technique based on motor current signal is presented in this paper for extracting the typical feature frequencies of machine tools which can effectively suppress the disturbances. Some simulated current signals were made by MATLAB, and a current signal was obtained from a complex gearbox of an iron works made in Luxembourg. In diagnosis the MCSA is combined with entropy optimization. Both simulated and experimental results show that this technique is efficient, accurate and reliable enough to extract the feature frequencies of current signal, which provides a new strategy for the fault diagnosis and the condition monitoring of machine tools.

Modeling and Simulation of Phased Array Antennas to Support Next-Generation Satellite Design

NASA Technical Reports Server (NTRS)

Tchorowski, Nicole; Murawski, Robert; Manning, Robert; Fuentes, Michael

2016-01-01

Developing enhanced simulation capabilities has become a significant priority for the Space Communications and Navigation (SCaN) project at NASA as new space communications technologies are proposed to replace aging NASA communications assets, such as the Tracking and Data Relay Satellite System (TDRSS). When developing the architecture for these new space communications assets, it is important to develop updated modeling and simulation methodologies, such that competing architectures can be weighed against one another and the optimal path forward can be determined. There have been many simulation tools developed here at NASA for the simulation of single RF link budgets, or for the modeling and simulation of an entire network of spacecraft and their supporting SCaN network elements. However, the modeling capabilities are never fully complete and as new technologies are proposed, gaps are identified. One such gap is the ability to rapidly develop high fidelity simulation models of electronically steerable phased array systems. As future relay satellite architectures are proposed that include optical communications links, electronically steerable antennas will become more desirable due to the reduction in platform vibration introduced by mechanically steerable devices. In this research, we investigate how modeling of these antennas can be introduced into out overall simulation and modeling structure. The ultimate goal of this research is two-fold. First, to enable NASA engineers to model various proposed simulation architectures and determine which proposed architecture meets the given architectural requirements. Second, given a set of communications link requirements for a proposed satellite architecture, determine the optimal configuration for a phased array antenna. There is a variety of tools available that can be used to model phased array antennas. To meet our stated goals, the first objective of this research is to compare the subset of tools available to us, trading-off modeling fidelity of the tool with simulation performance. When comparing several proposed architectures, higher- fidelity modeling may be desirable, however, when iterating a proposed set of communication link requirements across ranges of phased array configuration parameters, the practicality of performance becomes a significant requirement. In either case, a minimum simulation - fidelity must be met, regardless of performance considerations, which will be discussed in this research. Given a suitable set of phased array modeling tools, this research then focuses on integration with current SCaN modeling and simulation tools. While properly modeling the antenna elements of a system are vital, this is only a small part of the end-to-end communication path between a satellite and the supporting ground station and/or relay satellite assets. To properly model a proposed simulation architecture, this toolset must be integrated with other commercial and government development tools, such that the overall architecture can be examined in terms of communications, reliability, and cost. In this research, integration with previously developed communication tools is investigated.

Automatic optimization of well locations in a North Sea fractured chalk reservoir using a front tracking reservoir simulator

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

Rian, D.T.; Hage, A.

1994-12-31

A numerical simulator is often used as a reservoir management tool. One of its main purposes is to aid in the evaluation of number of wells, well locations and start time for wells. Traditionally, the optimization of a field development is done by a manual trial and error process. In this paper, an example of an automated technique is given. The core in the automization process is the reservoir simulator Frontline. Frontline is based on front tracking techniques, which makes it fast and accurate compared to traditional finite difference simulators. Due to its CPU-efficiency the simulator has been coupled withmore » an optimization module, which enables automatic optimization of location of wells, number of wells and start-up times. The simulator was used as an alternative method in the evaluation of waterflooding in a North Sea fractured chalk reservoir. Since Frontline, in principle, is 2D, Buckley-Leverett pseudo functions were used to represent the 3rd dimension. The area full field simulation model was run with up to 25 wells for 20 years in less than one minute of Vax 9000 CPU-time. The automatic Frontline evaluation indicated that a peripheral waterflood could double incremental recovery compared to a central pattern drive.« less

The Future of Sustainable Transportation | Transportation Research | NREL

Science.gov Websites

lithium-ion batteries need to be dramatically cut for electric vehicles (EVs) to reach a wider audience pledge to provide workplace charging. New Tool Helps Optimize Battery Lifespan While upfront costs of . NREL's new Battery Lifetime Analysis and Simulation Tool (BLAST) suite makes it possible to predict long

MITHRA 1.0: A full-wave simulation tool for free electron lasers

NASA Astrophysics Data System (ADS)

Fallahi, Arya; Yahaghi, Alireza; Kärtner, Franz X.

2018-07-01

Free Electron Lasers (FELs) are a solution for providing intense, coherent and bright radiation in the hard X-ray regime. Due to the low wall-plug efficiency of FEL facilities, it is crucial and additionally very useful to develop complete and accurate simulation tools for better optimizing a FEL interaction. The highly sophisticated dynamics involved in a FEL process was the main obstacle hindering the development of general simulation tools for this problem. We present a numerical algorithm based on finite difference time domain/Particle in cell (FDTD/PIC) in a Lorentz boosted coordinate system which is able to fulfill a full-wave simulation of a FEL process. The developed software offers a suitable tool for the analysis of FEL interactions without considering any of the usual approximations. A coordinate transformation to bunch rest frame makes the very different length scales of bunch size, optical wavelengths and the undulator period transform to values with the same order. Consequently, FDTD/PIC simulations in conjunction with efficient parallelization techniques make the full-wave simulation feasible using the available computational resources. Several examples of free electron lasers are analyzed using the developed software, the results are benchmarked based on standard FEL codes and discussed in detail.

ASTRID© - Advanced Solar Tubular ReceIver Design: A powerful tool for receiver design and optimization

NASA Astrophysics Data System (ADS)

Frantz, Cathy; Fritsch, Andreas; Uhlig, Ralf

2017-06-01

In solar tower power plants the receiver is one of the critical components. It converts the solar radiation into heat and must withstand high heat flux densities and high daily or even hourly gradients (due to passage of clouds). For this reason, the challenge during receiver design is to find a reasonable compromise between receiver efficiency, reliability, lifetime and cost. There is a strong interaction between the heliostat field, the receiver and the heat transfer fluid. Therefore, a proper receiver design needs to consider these components within the receiver optimization. There are several design and optimization tools for receivers, but most of them focus only on the receiver, ignoring the heliostat field and other parts of the plant. During the last years DLR developed the ASTRIDcode for tubular receiver concept simulation. The code comprises both a high and a low-detail model. The low-detail model utilizes a number of simplifications which allow the user to screen a high number of receiver concepts for optimization purposes. The high-detail model uses a FE model and is able to compute local absorber and salt temperatures with high accuracy. One key strength of the ASTRIDcode is its interface to a ray tracing software which simulates a realistic heat flux distributions on the receiver surface. The results generated by the ASTRIDcode have been validated by CFD simulations and measurement data.

Airplane numerical simulation for the rapid prototyping process

NASA Astrophysics Data System (ADS)

Roysdon, Paul F.

Airplane Numerical Simulation for the Rapid Prototyping Process is a comprehensive research investigation into the most up-to-date methods for airplane development and design. Uses of modern engineering software tools, like MatLab and Excel, are presented with examples of batch and optimization algorithms which combine the computing power of MatLab with robust aerodynamic tools like XFOIL and AVL. The resulting data is demonstrated in the development and use of a full non-linear six-degrees-of-freedom simulator. The applications for this numerical tool-box vary from un-manned aerial vehicles to first-order analysis of manned aircraft. A Blended-Wing-Body airplane is used for the analysis to demonstrate the flexibility of the code from classic wing-and-tail configurations to less common configurations like the blended-wing-body. This configuration has been shown to have superior aerodynamic performance -- in contrast to their classic wing-and-tube fuselage counterparts -- and have reduced sensitivity to aerodynamic flutter as well as potential for increased engine noise abatement. Of course without a classic tail elevator to damp the nose up pitching moment, and the vertical tail rudder to damp the yaw and possible rolling aerodynamics, the challenges in lateral roll and yaw stability, as well as pitching moment are not insignificant. This thesis work applies the tools necessary to perform the airplane development and optimization on a rapid basis, demonstrating the strength of this tool through examples and comparison of the results to similar airplane performance characteristics published in literature.

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

Zitney, S.E.; McCorkle, D.; Yang, C.

Process modeling and simulation tools are widely used for the design and operation of advanced power generation systems. These tools enable engineers to solve the critical process systems engineering problems that arise throughout the lifecycle of a power plant, such as designing a new process, troubleshooting a process unit or optimizing operations of the full process. To analyze the impact of complex thermal and fluid flow phenomena on overall power plant performance, the Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) has developed the Advanced Process Engineering Co-Simulator (APECS). The APECS system is an integrated software suite that combinesmore » process simulation (e.g., Aspen Plus) and high-fidelity equipment simulations such as those based on computational fluid dynamics (CFD), together with advanced analysis capabilities including case studies, sensitivity analysis, stochastic simulation for risk/uncertainty analysis, and multi-objective optimization. In this paper we discuss the initial phases of the integration of the APECS system with the immersive and interactive virtual engineering software, VE-Suite, developed at Iowa State University and Ames Laboratory. VE-Suite uses the ActiveX (OLE Automation) controls in the Aspen Plus process simulator wrapped by the CASI library developed by Reaction Engineering International to run process/CFD co-simulations and query for results. This integration represents a necessary step in the development of virtual power plant co-simulations that will ultimately reduce the time, cost, and technical risk of developing advanced power generation systems.« less

A Queue Simulation Tool for a High Performance Scientific Computing Center

NASA Technical Reports Server (NTRS)

Spear, Carrie; McGalliard, James

2007-01-01

The NASA Center for Computational Sciences (NCCS) at the Goddard Space Flight Center provides high performance highly parallel processors, mass storage, and supporting infrastructure to a community of computational Earth and space scientists. Long running (days) and highly parallel (hundreds of CPUs) jobs are common in the workload. NCCS management structures batch queues and allocates resources to optimize system use and prioritize workloads. NCCS technical staff use a locally developed discrete event simulation tool to model the impacts of evolving workloads, potential system upgrades, alternative queue structures and resource allocation policies.

Simulation of the Simbol-X telescope: imaging performance of a deformable x-ray telescope

NASA Astrophysics Data System (ADS)

Chauvin, Maxime; Roques, Jean-Pierre

2009-08-01

We have developed a simulation tool for a Wolter I telescope subject to deformations. The aim is to understand and predict the behavior of Simbol-X and other future missions (NuSTAR, Astro-H, IXO, ...). Our code, based on Monte-Carlo ray-tracing, computes the full photon trajectories up to the detector plane, along with the deformations. The degradation of the imaging system is corrected using metrology. This tool allows to perform many analyzes in order to optimize the configuration of any of these telescopes.

Efficient dispatching in a terminal city network

DOT National Transportation Integrated Search

2001-01-01

This report describes new optimization and simulation tools to address several problems in transportation, specifically driver dispatching and tour formation in full truckload trucking. In this segment of transportation industry, one of the problems ...

Comparison of Numerically Simulated and Experimentally Measured Performance of a Rotating Detonation Engine

NASA Technical Reports Server (NTRS)

Paxson, Daniel E.; Fotia, Matthew L.; Hoke, John; Schauer, Fred

2015-01-01

A quasi-two-dimensional, computational fluid dynamic (CFD) simulation of a rotating detonation engine (RDE) is described. The simulation operates in the detonation frame of reference and utilizes a relatively coarse grid such that only the essential primary flow field structure is captured. This construction and other simplifications yield rapidly converging, steady solutions. Viscous effects, and heat transfer effects are modeled using source terms. The effects of potential inlet flow reversals are modeled using boundary conditions. Results from the simulation are compared to measured data from an experimental RDE rig with a converging-diverging nozzle added. The comparison is favorable for the two operating points examined. The utility of the code as a performance optimization tool and a diagnostic tool are discussed.

Optimization of droplets for UV-NIL using coarse-grain simulation of resist flow

NASA Astrophysics Data System (ADS)

Sirotkin, Vadim; Svintsov, Alexander; Zaitsev, Sergey

2009-03-01

A mathematical model and numerical method are described, which make it possible to simulate ultraviolet ("step and flash") nanoimprint lithography (UV-NIL) process adequately even using standard Personal Computers. The model is derived from 3D Navier-Stokes equations with the understanding that the resist motion is largely directed along the substrate surface and characterized by ultra-low values of the Reynolds number. By the numerical approximation of the model, a special finite difference method is applied (a coarse-grain method). A coarse-grain modeling tool for detailed analysis of resist spreading in UV-NIL at the structure-scale level is tested. The obtained results demonstrate the high ability of the tool to calculate optimal dispensing for given stamp design and process parameters. This dispensing provides uniform filled areas and a homogeneous residual layer thickness in UV-NIL.

Constraint Force Equation Methodology for Modeling Multi-Body Stage Separation Dynamics

NASA Technical Reports Server (NTRS)

Toniolo, Matthew D.; Tartabini, Paul V.; Pamadi, Bandu N.; Hotchko, Nathaniel

2008-01-01

This paper discusses a generalized approach to the multi-body separation problems in a launch vehicle staging environment based on constraint force methodology and its implementation into the Program to Optimize Simulated Trajectories II (POST2), a widely used trajectory design and optimization tool. This development facilitates the inclusion of stage separation analysis into POST2 for seamless end-to-end simulations of launch vehicle trajectories, thus simplifying the overall implementation and providing a range of modeling and optimization capabilities that are standard features in POST2. Analysis and results are presented for two test cases that validate the constraint force equation methodology in a stand-alone mode and its implementation in POST2.

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2012)

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

Miller, David C.; Syamlal, Madhava; Cottrell, Roger

2012-09-30

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools asmore » necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is organized into 8 technical elements that fall under two focus areas. The first focus area (Physicochemical Models and Data) addresses the steps necessary to model and simulate the various technologies and processes needed to bring a new Carbon Capture and Storage (CCS) technology into production. The second focus area (Analysis & Software) is developing the software infrastructure to integrate the various components and implement the tools that are needed to make quantifiable decisions regarding the viability of new CCS technologies. CCSI also has an Industry Advisory Board (IAB). By working closely with industry from the inception of the project to identify industrial challenge problems, CCSI ensures that the simulation tools are developed for the carbon capture technologies of most relevance to industry. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories' core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI's industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI's academic participants (Carnegie Mellon University, Princeton University, West Virginia University, and Boston University) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 12, CCSI released its first set of computational tools and models. This pre-release, a year ahead of the originally planned first release, is the result of intense industry interest in getting early access to the tools and the phenomenal progress of the CCSI technical team. These initial components of the CCSI Toolset provide new models and computational capabilities that will accelerate the commercial development of carbon capture technologies as well as related technologies, such as those found in the power, refining, chemicals, and gas production industries. The release consists of new tools for process synthesis and optimization to help identify promising concepts more quickly, new physics-based models of potential capture equipment and processes that will reduce the time to design and troubleshoot new systems, a framework to quantify the uncertainty of model predictions, and various enabling tools that provide new capabilities such as creating reduced order models (ROMs) from reacting multiphase flow simulations and running thousands of process simulations concurrently for optimization and UQ.« less

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)

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

Miller, David C.; Syamlal, Madhava; Cottrell, Roger

2013-09-30

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools asmore » necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format.« less

Simulation platform of LEO satellite communication system based on OPNET

NASA Astrophysics Data System (ADS)

Zhang, Yu; Zhang, Yong; Li, Xiaozhuo; Wang, Chuqiao; Li, Haihao

2018-02-01

For the purpose of verifying communication protocol in the low earth orbit (LEO) satellite communication system, an Optimized Network Engineering Tool (OPNET) based simulation platform is built. Using the three-layer modeling mechanism, the network model, the node model and the process model of the satellite communication system are built respectively from top to bottom, and the protocol will be implemented by finite state machine and Proto-C language. According to satellite orbit parameters, orbit files are generated via Satellite Tool Kit (STK) and imported into OPNET, and the satellite nodes move along their orbits. The simulation platform adopts time-slot-driven mode, divides simulation time into continuous time slots, and allocates slot number for each time slot. A resource allocation strategy is simulated on this platform, and the simulation results such as resource utilization rate, system throughput and packet delay are analyzed, which indicate that this simulation platform has outstanding versatility.

VirSSPA- a virtual reality tool for surgical planning workflow.

PubMed

Suárez, C; Acha, B; Serrano, C; Parra, C; Gómez, T

2009-03-01

A virtual reality tool, called VirSSPA, was developed to optimize the planning of surgical processes. Segmentation algorithms for Computed Tomography (CT) images: a region growing procedure was used for soft tissues and a thresholding algorithm was implemented to segment bones. The algorithms operate semiautomati- cally since they only need seed selection with the mouse on each tissue segmented by the user. The novelty of the paper is the adaptation of an enhancement method based on histogram thresholding applied to CT images for surgical planning, which simplifies subsequent segmentation. A substantial improvement of the virtual reality tool VirSSPA was obtained with these algorithms. VirSSPA was used to optimize surgical planning, to decrease the time spent on surgical planning and to improve operative results. The success rate increases due to surgeons being able to see the exact extent of the patient's ailment. This tool can decrease operating room time, thus resulting in reduced costs. Virtual simulation was effective for optimizing surgical planning, which could, consequently, result in improved outcomes with reduced costs.

BASIMO - Borehole Heat Exchanger Array Simulation and Optimization Tool

NASA Astrophysics Data System (ADS)

Schulte, Daniel O.; Bastian, Welsch; Wolfram, Rühaak; Kristian, Bär; Ingo, Sass

2017-04-01

Arrays of borehole heat exchangers are an increasingly popular source for renewable energy. Furthermore, they can serve as borehole thermal energy storage (BTES) systems for seasonally fluctuating heat sources like solar thermal energy or district heating grids. The high temperature level of these heat sources prohibits the use of the shallow subsurface for environmental reasons. Therefore, deeper reservoirs have to be accessed instead. The increased depth of the systems results in high investment costs and has hindered the implementation of this technology until now. Therefore, research of medium deep BTES systems relies on numerical simulation models. Current simulation tools cannot - or only to some extent - describe key features like partly insulated boreholes unless they run fully discretized models of the borehole heat exchangers. However, fully discretized models often come at a high computational cost, especially for large arrays of borehole heat exchangers. We give an update on the development of BASIMO: a tool, which uses one dimensional thermal resistance and capacity models for the borehole heat exchangers coupled with a numerical finite element model for the subsurface heat transport in a dual-continuum approach. An unstructured tetrahedral mesh bypasses the limitations of structured grids for borehole path geometries, while the thermal resistance and capacity model is improved to account for borehole heat exchanger properties changing with depth. Thereby, partly insulated boreholes can be considered in the model. Furthermore, BASIMO can be used to improve the design of BTES systems: the tool allows for automated parameter variations and is readily coupled to other code like mathematical optimization algorithms. Optimization can be used to determine the required minimum system size or to increase the system performance.

T.R.I.C.K.-Tire/Road Interaction Characterization & Knowledge - A tool for the evaluation of tire and vehicle performances in outdoor test sessions

NASA Astrophysics Data System (ADS)

Farroni, Flavio

2016-05-01

The most powerful engine, the most sophisticated aerodynamic devices or the most complex control systems will not improve vehicle performances if the forces exchanged with the road are not optimized by proper employment and knowledge of tires. The vehicle interface with the ground is constituted by the sum of small surfaces, wide about as one of our palms, in which tire/road interaction forces are exchanged. From this it is clear to see how the optimization of tire behavior represents a key-factor in the definition of the best setup of the whole vehicle. Nowadays, people and companies playing a role in automotive sector are looking for the optimal solution to model and understand tire's behavior both in experimental and simulation environments. The studies carried out and the tool developed herein demonstrate a new approach in tire characterization and in vehicle simulation procedures. This enables the reproduction of the dynamic response of a tire through the use of specific track sessions, carried out with the aim to employ the vehicle as a moving lab. The final product, named TRICK tool (Tire/Road Interaction Characterization and Knowledge), comprises of a vehicle model which processes experimental signals acquired from vehicle CAN bus and from sideslip angle estimation additional instrumentation. The output of the tool is several extra "virtual telemetry" channels, based on the time history of the acquired signals and containing force and slip estimations, useful to provide tire interaction characteristics. TRICK results can be integrated with the physical models developed by the Vehicle Dynamics UniNa research group, providing a multitude of working solutions and constituting an ideal instrument for the prediction and the simulation of the real tire dynamics.

Optimization in Cardiovascular Modeling

NASA Astrophysics Data System (ADS)

Marsden, Alison L.

2014-01-01

Fluid mechanics plays a key role in the development, progression, and treatment of cardiovascular disease. Advances in imaging methods and patient-specific modeling now reveal increasingly detailed information about blood flow patterns in health and disease. Building on these tools, there is now an opportunity to couple blood flow simulation with optimization algorithms to improve the design of surgeries and devices, incorporating more information about the flow physics in the design process to augment current medical knowledge. In doing so, a major challenge is the need for efficient optimization tools that are appropriate for unsteady fluid mechanics problems, particularly for the optimization of complex patient-specific models in the presence of uncertainty. This article reviews the state of the art in optimization tools for virtual surgery, device design, and model parameter identification in cardiovascular flow and mechanobiology applications. In particular, it reviews trade-offs between traditional gradient-based methods and derivative-free approaches, as well as the need to incorporate uncertainties. Key future challenges are outlined, which extend to the incorporation of biological response and the customization of surgeries and devices for individual patients.

Orbit design and optimization based on global telecommunication performance metrics

NASA Technical Reports Server (NTRS)

Lee, Seungwon; Lee, Charles H.; Kerridge, Stuart; Cheung, Kar-Ming; Edwards, Charles D.

2006-01-01

The orbit selection of telecommunications orbiters is one of the critical design processes and should be guided by global telecom performance metrics and mission-specific constraints. In order to aid the orbit selection, we have coupled the Telecom Orbit Analysis and Simulation Tool (TOAST) with genetic optimization algorithms. As a demonstration, we have applied the developed tool to select an optimal orbit for general Mars telecommunications orbiters with the constraint of being a frozen orbit. While a typical optimization goal is to minimize tele-communications down time, several relevant performance metrics are examined: 1) area-weighted average gap time, 2) global maximum of local maximum gap time, 3) global maximum of local minimum gap time. Optimal solutions are found with each of the metrics. Common and different features among the optimal solutions as well as the advantage and disadvantage of each metric are presented. The optimal solutions are compared with several candidate orbits that were considered during the development of Mars Telecommunications Orbiter.

Simulation-optimization of large agro-hydrosystems using a decomposition approach

NASA Astrophysics Data System (ADS)

Schuetze, Niels; Grundmann, Jens

2014-05-01

In this contribution a stochastic simulation-optimization framework for decision support for optimal planning and operation of water supply of large agro-hydrosystems is presented. It is based on a decomposition solution strategy which allows for (i) the usage of numerical process models together with efficient Monte Carlo simulations for a reliable estimation of higher quantiles of the minimum agricultural water demand for full and deficit irrigation strategies at small scale (farm level), and (ii) the utilization of the optimization results at small scale for solving water resources management problems at regional scale. As a secondary result of several simulation-optimization runs at the smaller scale stochastic crop-water production functions (SCWPF) for different crops are derived which can be used as a basic tool for assessing the impact of climate variability on risk for potential yield. In addition, microeconomic impacts of climate change and the vulnerability of the agro-ecological systems are evaluated. The developed methodology is demonstrated through its application on a real-world case study for the South Al-Batinah region in the Sultanate of Oman where a coastal aquifer is affected by saltwater intrusion due to excessive groundwater withdrawal for irrigated agriculture.

The Effects of a Concept Map-Based Support Tool on Simulation-Based Inquiry Learning

ERIC Educational Resources Information Center

Hagemans, Mieke G.; van der Meij, Hans; de Jong, Ton

2013-01-01

Students often need support to optimize their learning in inquiry learning environments. In 2 studies, we investigated the effects of adding concept-map-based support to a simulation-based inquiry environment on kinematics. The concept map displayed the main domain concepts and their relations, while dynamic color coding of the concepts displayed…

Validation of the ROMI-RIP rough mill simulator

Treesearch

Edward R. Thomas; Urs Buehlmann

2002-01-01

The USDA Forest Service's ROMI-RIP rough mill rip-first simulation program is a popular tool for analyzing rough mill conditions, determining more efficient rough mill practices, and finding optimal lumber board cut-up patterns. However, until now, the results generated by ROMI-RIP have not been rigorously compared to those of an actual rough mill. Validating the...

Simulation and statistical analysis for the optimization of nitrogen liquefaction plant with cryogenic Claude cycle using process modeling tool: ASPEN HYSYS

NASA Astrophysics Data System (ADS)

Joshi, D. M.

2017-09-01

Cryogenic technology is used for liquefaction of many gases and it has several applications in food process engineering. Temperatures below 123 K are considered to be in the field of cryogenics. Extreme low temperatures are a basic need for many industrial processes and have several applications, such as superconductivity of magnets, space, medicine and gas industries. Several methods can be used to obtain the low temperatures required for liquefaction of gases. The process of cooling or refrigerating a gas to a temperature below its critical temperature so that liquid can be formed at some suitable pressure, which is below the critical pressure, is the basic liquefaction process. Different cryogenic cycle configurations are designed for getting the liquefied form of gases at different temperatures. Each of the cryogenic cycles like Linde cycle, Claude cycle, Kapitza cycle or modified Claude cycle has its own advantages and disadvantages. The placement of heat exchangers, Joule-Thompson valve and turboexpander decides the configuration of a cryogenic cycle. Each configuration has its own efficiency according to the application. Here, a nitrogen liquefaction plant is used for the analysis purpose. The process modeling tool ASPEN HYSYS can provide a software simulation approach before the actual implementation of the plant in the field. This paper presents the simulation and statistical analysis of the Claude cycle with the process modeling tool ASPEN HYSYS. It covers the technique used to optimize the liquefaction of the plant. The simulation results so obtained can be used as a reference for the design and optimization of the nitrogen liquefaction plant. Efficient liquefaction will give the best performance and productivity to the plant.

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

Janjusic, Tommy; Kartsaklis, Christos

Application analysis is facilitated through a number of program profiling tools. The tools vary in their complexity, ease of deployment, design, and profiling detail. Specifically, understand- ing, analyzing, and optimizing is of particular importance for scientific applications where minor changes in code paths and data-structure layout can have profound effects. Understanding how intricate data-structures are accessed and how a given memory system responds is a complex task. In this paper we describe a trace profiling tool, Glprof, specifically aimed to lessen the burden of the programmer to pin-point heavily involved data-structures during an application's run-time, and understand data-structure run-time usage.more » Moreover, we showcase the tool's modularity using additional cache simulation components. We elaborate on the tool's design, and features. Finally we demonstrate the application of our tool in the context of Spec bench- marks using the Glprof profiler and two concurrently running cache simulators, PPC440 and AMD Interlagos.« less

Optimization and throughput estimation of optical ground networks for LEO-downlinks, GEO-feeder links and GEO-relays

NASA Astrophysics Data System (ADS)

Fuchs, Christian; Poulenard, Sylvain; Perlot, Nicolas; Riedi, Jerome; Perdigues, Josep

2017-02-01

Optical satellite communications play an increasingly important role in a number of space applications. However, if the system concept includes optical links to the surface of the Earth, the limited availability due to clouds and other atmospheric impacts need to be considered to give a reliable estimate of the system performance. An OGS network is required for increasing the availability to acceptable figures. In order to realistically estimate the performance and achievable throughput in various scenarios, a simulation tool has been developed under ESA contract. The tool is based on a database of 5 years of cloud data with global coverage and can thus easily simulate different optical ground station network topologies for LEO- and GEO-to-ground links. Further parameters, like e.g. limited availability due to sun blinding and atmospheric turbulence, are considered as well. This paper gives an overview about the simulation tool, the cloud database, as well as the modelling behind the simulation scheme. Several scenarios have been investigated: LEO-to-ground links, GEO feeder links, and GEO relay links. The key results of the optical ground station network optimization and throughput estimations will be presented. The implications of key technical parameters, as e.g. memory size aboard the satellite, will be discussed. Finally, potential system designs for LEO- and GEO-systems will be presented.

Optimization of the production process using virtual model of a workspace

NASA Astrophysics Data System (ADS)

Monica, Z.

2015-11-01

Optimization of the production process is an element of the design cycle consisting of: problem definition, modelling, simulation, optimization and implementation. Without the use of simulation techniques, the only thing which could be achieved is larger or smaller improvement of the process, not the optimization (i.e., the best result it is possible to get for the conditions under which the process works). Optimization is generally management actions that are ultimately bring savings in time, resources, and raw materials and improve the performance of a specific process. It does not matter whether it is a service or manufacturing process. Optimizing the savings generated by improving and increasing the efficiency of the processes. Optimization consists primarily of organizational activities that require very little investment, or rely solely on the changing organization of work. Modern companies operating in a market economy shows a significant increase in interest in modern methods of production management and services. This trend is due to the high competitiveness among companies that want to achieve success are forced to continually modify the ways to manage and flexible response to changing demand. Modern methods of production management, not only imply a stable position of the company in the sector, but also influence the improvement of health and safety within the company and contribute to the implementation of more efficient rules for standardization work in the company. This is why in the paper is presented the application of such developed environment like Siemens NX to create the virtual model of a production system and to simulate as well as optimize its work. The analyzed system is the robotized workcell consisting of: machine tools, industrial robots, conveyors, auxiliary equipment and buffers. In the program could be defined the control program realizing the main task in the virtual workcell. It is possible, using this tool, to optimize both the object trajectory and the cooperation process.

Method for Vibration Response Simulation and Sensor Placement Optimization of a Machine Tool Spindle System with a Bearing Defect

PubMed Central

Cao, Hongrui; Niu, Linkai; He, Zhengjia

2012-01-01

Bearing defects are one of the most important mechanical sources for vibration and noise generation in machine tool spindles. In this study, an integrated finite element (FE) model is proposed to predict the vibration responses of a spindle bearing system with localized bearing defects and then the sensor placement for better detection of bearing faults is optimized. A nonlinear bearing model is developed based on Jones' bearing theory, while the drawbar, shaft and housing are modeled as Timoshenko's beam. The bearing model is then integrated into the FE model of drawbar/shaft/housing by assembling equations of motion. The Newmark time integration method is used to solve the vibration responses numerically. The FE model of the spindle-bearing system was verified by conducting dynamic tests. Then, the localized bearing defects were modeled and vibration responses generated by the outer ring defect were simulated as an illustration. The optimization scheme of the sensor placement was carried out on the test spindle. The results proved that, the optimal sensor placement depends on the vibration modes under different boundary conditions and the transfer path between the excitation and the response. PMID:23012514

Simple Example of Backtest Overfitting (SEBO)

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

In the field of mathematical finance, a "backtest" is the usage of historical market data to assess the performance of a proposed trading strategy. It is a relatively simple matter for a present-day computer system to explore thousands, millions or even billions of variations of a proposed strategy, and pick the best performing variant as the "optimal" strategy "in sample" (i.e., on the input dataset). Unfortunately, such an "optimal" strategy often performs very poorly "out of sample" (i.e. on another dataset), because the parameters of the invest strategy have been oversit to the in-sample data, a situation known as "backtestmore » overfitting". While the mathematics of backtest overfitting has been examined in several recent theoretical studies, here we pursue a more tangible analysis of this problem, in the form of an online simulator tool. Given a input random walk time series, the tool develops an "optimal" variant of a simple strategy by exhaustively exploring all integer parameter values among a handful of parameters. That "optimal" strategy is overfit, since by definition a random walk is unpredictable. Then the tool tests the resulting "optimal" strategy on a second random walk time series. In most runs using our online tool, the "optimal" strategy derived from the first time series performs poorly on the second time series, demonstrating how hard it is not to overfit a backtest. We offer this online tool, "Simple Example of Backtest Overfitting (SEBO)", to facilitate further research in this area.« less

Optimal design of green and grey stormwater infrastructure for small urban catchment based on life-cycle cost-effectiveness analysis

NASA Astrophysics Data System (ADS)

Yang, Y.; Chui, T. F. M.

2016-12-01

Green infrastructure (GI) is identified as sustainable and environmentally friendly alternatives to the conventional grey stormwater infrastructure. Commonly used GI (e.g. green roof, bioretention, porous pavement) can provide multifunctional benefits, e.g. mitigation of urban heat island effects, improvements in air quality. Therefore, to optimize the design of GI and grey drainage infrastructure, it is essential to account for their benefits together with the costs. In this study, a comprehensive simulation-optimization modelling framework that considers the economic and hydro-environmental aspects of GI and grey infrastructure for small urban catchment applications is developed. Several modelling tools (i.e., EPA SWMM model, the WERF BMP and LID Whole Life Cycle Cost Modelling Tools) and optimization solvers are coupled together to assess the life-cycle cost-effectiveness of GI and grey infrastructure, and to further develop optimal stormwater drainage solutions. A typical residential lot in New York City is examined as a case study. The life-cycle cost-effectiveness of various GI and grey infrastructure are first examined at different investment levels. The results together with the catchment parameters are then provided to the optimization solvers, to derive the optimal investment and contributing area of each type of the stormwater controls. The relationship between the investment and optimized environmental benefit is found to be nonlinear. The optimized drainage solutions demonstrate that grey infrastructure is preferred at low total investments while more GI should be adopted at high investments. The sensitivity of the optimized solutions to the prices the stormwater controls is evaluated and is found to be highly associated with their utilizations in the base optimization case. The overall simulation-optimization framework can be easily applied to other sites world-wide, and to be further developed into powerful decision support systems.

Monte Carlo simulations in Nuclear Medicine

NASA Astrophysics Data System (ADS)

Loudos, George K.

2007-11-01

Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.

Clinical Outcome Metrics for Optimization of Robust Training

NASA Technical Reports Server (NTRS)

Ebert, Doug; Byrne, Vicky; Cole, Richard; Dulchavsky, Scott; Foy, Millennia; Garcia, Kathleen; Gibson, Robert; Ham, David; Hurst, Victor; Kerstman, Eric;

Evaluation of NASA's end-to-end data systems using DSDS+

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Davenport, William; Message, Philip

1994-01-01

The Data Systems Dynamic Simulator (DSDS+) is a software tool being developed by the authors to evaluate candidate architectures for NASA's end-to-end data systems. Via modeling and simulation, we are able to quickly predict the performance characteristics of each architecture, to evaluate 'what-if' scenarios, and to perform sensitivity analyses. As such, we are using modeling and simulation to help NASA select the optimal system configuration, and to quantify the performance characteristics of this system prior to its delivery. This paper is divided into the following six sections: (1) The role of modeling and simulation in the systems engineering process. In this section, we briefly describe the different types of results obtained by modeling each phase of the systems engineering life cycle, from concept definition through operations and maintenance; (2) Recent applications of DSDS+. In this section, we describe ongoing applications of DSDS+ in support of the Earth Observing System (EOS), and we present some of the simulation results generated of candidate system designs. So far, we have modeled individual EOS subsystems (e.g. the Solid State Recorders used onboard the spacecraft), and we have also developed an integrated model of the EOS end-to-end data processing and data communications systems (from the payloads onboard to the principle investigator facilities on the ground); (3) Overview of DSDS+. In this section we define what a discrete-event model is, and how it works. The discussion is presented relative to the DSDS+ simulation tool that we have developed, including it's run-time optimization algorithms that enables DSDS+ to execute substantially faster than comparable discrete-event simulation tools; (4) Summary. In this section, we summarize our findings and 'lessons learned' during the development and application of DSDS+ to model NASA's data systems; (5) Further Information; and (6) Acknowledgements.

Light extraction efficiency analysis of GaN-based light-emitting diodes with nanopatterned sapphire substrates.

PubMed

Pan, Jui-Wen; Tsai, Pei-Jung; Chang, Kao-Der; Chang, Yung-Yuan

2013-03-01

In this paper, we propose a method to analyze the light extraction efficiency (LEE) enhancement of a nanopatterned sapphire substrates (NPSS) light-emitting diode (LED) by comparing wave optics software with ray optics software. Finite-difference time-domain (FDTD) simulations represent the wave optics software and Light Tools (LTs) simulations represent the ray optics software. First, we find the trends of and an optimal solution for the LEE enhancement when the 2D-FDTD simulations are used to save on simulation time and computational memory. The rigorous coupled-wave analysis method is utilized to explain the trend we get from the 2D-FDTD algorithm. The optimal solution is then applied in 3D-FDTD and LTs simulations. The results are similar and the difference in LEE enhancement between the two simulations does not exceed 8.5% in the small LED chip area. More than 10(4) times computational memory is saved during the LTs simulation in comparison to the 3D-FDTD simulation. Moreover, LEE enhancement from the side of the LED can be obtained in the LTs simulation. An actual-size NPSS LED is simulated using the LTs. The results show a more than 307% improvement in the total LEE enhancement of the NPSS LED with the optimal solution compared to the conventional LED.

Rigorous ILT optimization for advanced patterning and design-process co-optimization

NASA Astrophysics Data System (ADS)

Selinidis, Kosta; Kuechler, Bernd; Cai, Howard; Braam, Kyle; Hoppe, Wolfgang; Domnenko, Vitaly; Poonawala, Amyn; Xiao, Guangming

2018-03-01

Despite the large difficulties involved in extending 193i multiple patterning and the slow ramp of EUV lithography to full manufacturing readiness, the pace of development for new technology node variations has been accelerating. Multiple new variations of new and existing technology nodes have been introduced for a range of device applications; each variation with at least a few new process integration methods, layout constructs and/or design rules. This had led to a strong increase in the demand for predictive technology tools which can be used to quickly guide important patterning and design co-optimization decisions. In this paper, we introduce a novel hybrid predictive patterning method combining two patterning technologies which have each individually been widely used for process tuning, mask correction and process-design cooptimization. These technologies are rigorous lithography simulation and inverse lithography technology (ILT). Rigorous lithography simulation has been extensively used for process development/tuning, lithography tool user setup, photoresist hot-spot detection, photoresist-etch interaction analysis, lithography-TCAD interactions/sensitivities, source optimization and basic lithography design rule exploration. ILT has been extensively used in a range of lithographic areas including logic hot-spot fixing, memory layout correction, dense memory cell optimization, assist feature (AF) optimization, source optimization, complex patterning design rules and design-technology co-optimization (DTCO). The combined optimization capability of these two technologies will therefore have a wide range of useful applications. We investigate the benefits of the new functionality for a few of these advanced applications including correction for photoresist top loss and resist scumming hotspots.

Optimization of vascular-targeting drugs in a computational model of tumor growth

NASA Astrophysics Data System (ADS)

Gevertz, Jana

2012-04-01

A biophysical tool is introduced that seeks to provide a theoretical basis for helping drug design teams assess the most promising drug targets and design optimal treatment strategies. The tool is grounded in a previously validated computational model of the feedback that occurs between a growing tumor and the evolving vasculature. In this paper, the model is particularly used to explore the therapeutic effectiveness of two drugs that target the tumor vasculature: angiogenesis inhibitors (AIs) and vascular disrupting agents (VDAs). Using sensitivity analyses, the impact of VDA dosing parameters is explored, as is the effects of administering a VDA with an AI. Further, a stochastic optimization scheme is utilized to identify an optimal dosing schedule for treatment with an AI and a chemotherapeutic. The treatment regimen identified can successfully halt simulated tumor growth, even after the cessation of therapy.

Hyper-X Stage Separation Trajectory Validation Studies

NASA Technical Reports Server (NTRS)

Tartabini, Paul V.; Bose, David M.; McMinn, John D.; Martin, John G.; Strovers, Brian K.

2003-01-01

An independent twelve degree-of-freedom simulation of the X-43A separation trajectory was created with the Program to Optimize Simulated trajectories (POST II). This simulation modeled the multi-body dynamics of the X-43A and its booster and included the effect of two pyrotechnically actuated pistons used to push the vehicles apart as well as aerodynamic interaction forces and moments between the two vehicles. The simulation was developed to validate trajectory studies conducted with a 14 degree-of-freedom simulation created early in the program using the Automatic Dynamic Analysis of Mechanics Systems (ADAMS) simulation software. The POST simulation was less detailed than the official ADAMS-based simulation used by the Project, but was simpler, more concise and ran faster, while providing similar results. The increase in speed provided by the POST simulation provided the Project with an alternate analysis tool. This tool was ideal for performing separation control logic trade studies that required the running of numerous Monte Carlo trajectories.

Design of the VISITOR Tool: A Versatile ImpulSive Interplanetary Trajectory OptimizeR

NASA Technical Reports Server (NTRS)

Corpaccioli, Luca; Linskens, Harry; Komar, David R.

2014-01-01

The design of trajectories for interplanetary missions represents one of the most complex and important problems to solve during conceptual space mission design. To facilitate conceptual mission sizing activities, it is essential to obtain sufficiently accurate trajectories in a fast and repeatable manner. To this end, the VISITOR tool was developed. This tool modularly augments a patched conic MGA-1DSM model with a mass model, launch window analysis, and the ability to simulate more realistic arrival and departure operations. This was implemented in MATLAB, exploiting the built-in optimization tools and vector analysis routines. The chosen optimization strategy uses a grid search and pattern search, an iterative variable grid method. A genetic algorithm can be selectively used to improve search space pruning, at the cost of losing the repeatability of the results and increased computation time. The tool was validated against seven flown missions: the average total mission (Delta)V offset from the nominal trajectory was 9.1%, which was reduced to 7.3% when using the genetic algorithm at the cost of an increase in computation time by a factor 5.7. It was found that VISITOR was well-suited for the conceptual design of interplanetary trajectories, while also facilitating future improvements due to its modular structure.

Improving Building Energy Simulation Programs Through Diagnostic Testing (Fact Sheet)

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

Not Available

2012-02-01

New test procedure evaluates quality and accuracy of energy analysis tools for the residential building retrofit market. Reducing the energy use of existing homes in the United States offers significant energy-saving opportunities, which can be identified through building simulation software tools that calculate optimal packages of efficiency measures. To improve the accuracy of energy analysis for residential buildings, the National Renewable Energy Laboratory's (NREL) Buildings Research team developed the Building Energy Simulation Test for Existing Homes (BESTEST-EX), a method for diagnosing and correcting errors in building energy audit software and calibration procedures. BESTEST-EX consists of building physics and utility billmore » calibration test cases, which software developers can use to compare their tools simulation findings to reference results generated with state-of-the-art simulation tools. Overall, the BESTEST-EX methodology: (1) Tests software predictions of retrofit energy savings in existing homes; (2) Ensures building physics calculations and utility bill calibration procedures perform to a minimum standard; and (3) Quantifies impacts of uncertainties in input audit data and occupant behavior. BESTEST-EX is helping software developers identify and correct bugs in their software, as well as develop and test utility bill calibration procedures.« less

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.

Micro-Vibration Performance Prediction of SEPTA24 Using SMeSim (RUAG Space Mechanism Simulator Tool)

NASA Astrophysics Data System (ADS)

Omiciuolo, Manolo; Lang, Andreas; Wismer, Stefan; Barth, Stephan; Szekely, Gerhard

2013-09-01

Scientific space missions are currently challenging the performances of their payloads. The performances can be dramatically restricted by micro-vibration loads generated by any moving parts of the satellites, thus by Solar Array Drive Assemblies too. Micro-vibration prediction of SADAs is therefore very important to support their design and optimization in the early stages of a programme. The Space Mechanism Simulator (SMeSim) tool, developed by RUAG, enhances the capability of analysing the micro-vibration emissivity of a Solar Array Drive Assembly (SADA) under a specified set of boundary conditions. The tool is developed in the Matlab/Simulink® environment throughout a library of blocks simulating the different components a SADA is made of. The modular architecture of the blocks, assembled by the user, and the set up of the boundary conditions allow time-domain and frequency-domain analyses of a rigid multi-body model with concentrated flexibilities and coupled- electronic control of the mechanism. SMeSim is used to model the SEPTA24 Solar Array Drive Mechanism and predict its micro-vibration emissivity. SMeSim and the return of experience earned throughout its development and use can now support activities like verification by analysis of micro-vibration emissivity requirements and/or design optimization to minimize the micro- vibration emissivity of a SADA.

Robust multi-site MR data processing: iterative optimization of bias correction, tissue classification, and registration.

PubMed

Young Kim, Eun; Johnson, Hans J

2013-01-01

A robust multi-modal tool, for automated registration, bias correction, and tissue classification, has been implemented for large-scale heterogeneous multi-site longitudinal MR data analysis. This work focused on improving the an iterative optimization framework between bias-correction, registration, and tissue classification inspired from previous work. The primary contributions are robustness improvements from incorporation of following four elements: (1) utilize multi-modal and repeated scans, (2) incorporate high-deformable registration, (3) use extended set of tissue definitions, and (4) use of multi-modal aware intensity-context priors. The benefits of these enhancements were investigated by a series of experiments with both simulated brain data set (BrainWeb) and by applying to highly-heterogeneous data from a 32 site imaging study with quality assessments through the expert visual inspection. The implementation of this tool is tailored for, but not limited to, large-scale data processing with great data variation with a flexible interface. In this paper, we describe enhancements to a joint registration, bias correction, and the tissue classification, that improve the generalizability and robustness for processing multi-modal longitudinal MR scans collected at multi-sites. The tool was evaluated by using both simulated and simulated and human subject MRI images. With these enhancements, the results showed improved robustness for large-scale heterogeneous MRI processing.

Application Of Moldex3D For Thin-wall Injection Moulding Simulation

NASA Astrophysics Data System (ADS)

Šercer, Mladen; Godec, Damir; Bujanić, Božo

2007-05-01

The benefits associated with decreasing wall thicknesses below their current values are still measurable and desired even if the final wall thickness is nowhere near those of the aggressive portable electronics industry. It is important to note that gains in wall section reduction do not always occur without investment, in this case, in tooling and machinery upgrades. Equally important is the fact that productivity and performance benefits of reduced material usage, fast cycle times, and lighter weight can often outweigh most of the added costs. In order to eliminate unnecessary mould trials, minimize product development cycle, reduce overall costs and improve product quality, polymeric engineers use new CAE technology (Computer Aided Engineering). This technology is a simulation tool, which combines proven theories, material properties and process conditions to generate realistic simulations and produce valuable recommendations. Based on these recommendations, an optional combination of product design, material and process conditions can be identified. In this work, Moldex3D software was used for simulation of injection moulding in order to avoid potential moulding problems. The results gained from the simulation were used for the optimization of an existing product design, for mould development and for optimization of processing parameters, e.g. injection pressure, mould cavity temperature, etc.

The mechanisms of labor division from the perspective of individual optimization

NASA Astrophysics Data System (ADS)

Zhu, Lirong; Chen, Jiawei; Di, Zengru; Chen, Liujun; Liu, Yan; Stanley, H. Eugene

2017-12-01

Although the tools of complexity research have been applied to the phenomenon of labor division, its underlying mechanisms are still unclear. Researchers have used evolutionary models to study labor division in terms of global optimization, but focusing on individual optimization is a more realistic, real-world approach. We do this by first developing a multi-agent model that takes into account information-sharing and learning-by-doing and by using simulations to demonstrate the emergence of labor division. We then use a master equation method and find that the computational results are consistent with the results of the simulation. Finally we find that the core underlying mechanisms that cause labor division are learning-by-doing, information cost, and random fluctuation.

TestSTORM: Simulator for optimizing sample labeling and image acquisition in localization based super-resolution microscopy

PubMed Central

Sinkó, József; Kákonyi, Róbert; Rees, Eric; Metcalf, Daniel; Knight, Alex E.; Kaminski, Clemens F.; Szabó, Gábor; Erdélyi, Miklós

2014-01-01

Localization-based super-resolution microscopy image quality depends on several factors such as dye choice and labeling strategy, microscope quality and user-defined parameters such as frame rate and number as well as the image processing algorithm. Experimental optimization of these parameters can be time-consuming and expensive so we present TestSTORM, a simulator that can be used to optimize these steps. TestSTORM users can select from among four different structures with specific patterns, dye and acquisition parameters. Example results are shown and the results of the vesicle pattern are compared with experimental data. Moreover, image stacks can be generated for further evaluation using localization algorithms, offering a tool for further software developments. PMID:24688813

Launch Vehicle Propulsion Parameter Design Multiple Selection Criteria

NASA Technical Reports Server (NTRS)

Shelton, Joey Dewayne

2004-01-01

The optimization tool described herein addresses and emphasizes the use of computer tools to model a system and focuses on a concept development approach for a liquid hydrogen/liquid oxygen single-stage-to-orbit system, but more particularly the development of the optimized system using new techniques. This methodology uses new and innovative tools to run Monte Carlo simulations, genetic algorithm solvers, and statistical models in order to optimize a design concept. The concept launch vehicle and propulsion system were modeled and optimized to determine the best design for weight and cost by varying design and technology parameters. Uncertainty levels were applied using Monte Carlo Simulations and the model output was compared to the National Aeronautics and Space Administration Space Shuttle Main Engine. Several key conclusions are summarized here for the model results. First, the Gross Liftoff Weight and Dry Weight were 67% higher for the design case for minimization of Design, Development, Test and Evaluation cost when compared to the weights determined by the minimization of Gross Liftoff Weight case. In turn, the Design, Development, Test and Evaluation cost was 53% higher for optimized Gross Liftoff Weight case when compared to the cost determined by case for minimization of Design, Development, Test and Evaluation cost. Therefore, a 53% increase in Design, Development, Test and Evaluation cost results in a 67% reduction in Gross Liftoff Weight. Secondly, the tool outputs define the sensitivity of propulsion parameters, technology and cost factors and how these parameters differ when cost and weight are optimized separately. A key finding was that for a Space Shuttle Main Engine thrust level the oxidizer/fuel ratio of 6.6 resulted in the lowest Gross Liftoff Weight rather than at 5.2 for the maximum specific impulse, demonstrating the relationships between specific impulse, engine weight, tank volume and tank weight. Lastly, the optimum chamber pressure for Gross Liftoff Weight minimization was 2713 pounds per square inch as compared to 3162 for the Design, Development, Test and Evaluation cost optimization case. This chamber pressure range is close to 3000 pounds per square inch for the Space Shuttle Main Engine.

Development of a Groundwater Transport Simulation Tool for Remedial Process Optimization

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

Ivarson, Kristine A.; Hanson, James P.; Tonkin, M.

2015-01-14

The groundwater remedy for hexavalent chromium at the Hanford Site includes operation of five large pump-and-treat systems along the Columbia River. The systems at the 100-HR-3 and 100-KR-4 groundwater operable units treat a total of about 9,840 liters per minute (2,600 gallons per minute) of groundwater to remove hexavalent chromium, and cover an area of nearly 26 square kilometers (10 square miles). The pump-and-treat systems result in large scale manipulation of groundwater flow direction, velocities, and most importantly, the contaminant plumes. Tracking of the plumes and predicting needed system modifications is part of the remedial process optimization, and is amore » continual process with the goal of reducing costs and shortening the timeframe to achieve the cleanup goals. While most of the initial system evaluations are conducted by assessing performance (e.g., reduction in contaminant concentration in groundwater and changes in inferred plume size), changes to the well field are often recommended. To determine the placement for new wells, well realignments, and modifications to pumping rates, it is important to be able to predict resultant plume changes. In smaller systems, it may be effective to make small scale changes periodically and adjust modifications based on groundwater monitoring results. Due to the expansive nature of the remediation systems at Hanford, however, additional tools were needed to predict the plume reactions to system changes. A computer simulation tool was developed to support pumping rate recommendations for optimization of large pump-and-treat groundwater remedy systems. This tool, called the Pumping Optimization Model, or POM, is based on a 1-layer derivation of a multi-layer contaminant transport model using MODFLOW and MT3D.« less

Radio Frequency Ablation Registration, Segmentation, and Fusion Tool

PubMed Central

McCreedy, Evan S.; Cheng, Ruida; Hemler, Paul F.; Viswanathan, Anand; Wood, Bradford J.; McAuliffe, Matthew J.

2008-01-01

The Radio Frequency Ablation Segmentation Tool (RFAST) is a software application developed using NIH's Medical Image Processing Analysis and Visualization (MIPAV) API for the specific purpose of assisting physicians in the planning of radio frequency ablation (RFA) procedures. The RFAST application sequentially leads the physician through the steps necessary to register, fuse, segment, visualize and plan the RFA treatment. Three-dimensional volume visualization of the CT dataset with segmented 3D surface models enables the physician to interactively position the ablation probe to simulate burns and to semi-manually simulate sphere packing in an attempt to optimize probe placement. PMID:16871716

A coarse-grained model for DNA origami.

PubMed

Reshetnikov, Roman V; Stolyarova, Anastasia V; Zalevsky, Arthur O; Panteleev, Dmitry Y; Pavlova, Galina V; Klinov, Dmitry V; Golovin, Andrey V; Protopopova, Anna D

2018-02-16

Modeling tools provide a valuable support for DNA origami design. However, current solutions have limited application for conformational analysis of the designs. In this work we present a tool for a thorough study of DNA origami structure and dynamics. The tool is based on a novel coarse-grained model dedicated to geometry optimization and conformational analysis of DNA origami. We explored the ability of the model to predict dynamic behavior, global shapes, and fine details of two single-layer systems designed in hexagonal and square lattices using atomic force microscopy, Förster resonance energy transfer spectroscopy, and all-atom molecular dynamic simulations for validation of the results. We also examined the performance of the model for multilayer systems by simulation of DNA origami with published cryo-electron microscopy and atomic force microscopy structures. A good agreement between the simulated and experimental data makes the model suitable for conformational analysis of DNA origami objects. The tool is available at http://vsb.fbb.msu.ru/cosm as a web-service and as a standalone version.

A coarse-grained model for DNA origami

PubMed Central

Stolyarova, Anastasia V; Zalevsky, Arthur O; Panteleev, Dmitry Y; Pavlova, Galina V; Klinov, Dmitry V; Golovin, Andrey V; Protopopova, Anna D

2018-01-01

Abstract Modeling tools provide a valuable support for DNA origami design. However, current solutions have limited application for conformational analysis of the designs. In this work we present a tool for a thorough study of DNA origami structure and dynamics. The tool is based on a novel coarse-grained model dedicated to geometry optimization and conformational analysis of DNA origami. We explored the ability of the model to predict dynamic behavior, global shapes, and fine details of two single-layer systems designed in hexagonal and square lattices using atomic force microscopy, Förster resonance energy transfer spectroscopy, and all-atom molecular dynamic simulations for validation of the results. We also examined the performance of the model for multilayer systems by simulation of DNA origami with published cryo-electron microscopy and atomic force microscopy structures. A good agreement between the simulated and experimental data makes the model suitable for conformational analysis of DNA origami objects. The tool is available at http://vsb.fbb.msu.ru/cosm as a web-service and as a standalone version. PMID:29267876

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 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.)

Edge control in CNC polishing, paper 2: simulation and validation of tool influence functions on edges.

PubMed

Li, Hongyu; Walker, David; Yu, Guoyu; Sayle, Andrew; Messelink, Wilhelmus; Evans, Rob; Beaucamp, Anthony

2013-01-14

Edge mis-figure is regarded as one of the most difficult technical issues for manufacturing the segments of extremely large telescopes, which can dominate key aspects of performance. A novel edge-control technique has been developed, based on 'Precessions' polishing technique and for which accurate and stable edge tool influence functions (TIFs) are crucial. In the first paper in this series [D. Walker Opt. Express 20, 19787-19798 (2012)], multiple parameters were experimentally optimized using an extended set of experiments. The first purpose of this new work is to 'short circuit' this procedure through modeling. This also gives the prospect of optimizing local (as distinct from global) polishing for edge mis-figure, now under separate development. This paper presents a model that can predict edge TIFs based on surface-speed profiles and pressure distributions over the polishing spot at the edge of the part, the latter calculated by finite element analysis and verified by direct force measurement. This paper also presents a hybrid-measurement method for edge TIFs to verify the simulation results. Experimental and simulation results show good agreement.

Simulative design and process optimization of the two-stage stretch-blow molding process

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

Hopmann, Ch.; Rasche, S.; Windeck, C.

2015-05-22

The total production costs of PET bottles are significantly affected by the costs of raw material. Approximately 70 % of the total costs are spent for the raw material. Therefore, stretch-blow molding industry intends to reduce the total production costs by an optimized material efficiency. However, there is often a trade-off between an optimized material efficiency and required product properties. Due to a multitude of complex boundary conditions, the design process of new stretch-blow molded products is still a challenging task and is often based on empirical knowledge. Application of current CAE-tools supports the design process by reducing development timemore » and costs. This paper describes an approach to determine optimized preform geometry and corresponding process parameters iteratively. The wall thickness distribution and the local stretch ratios of the blown bottle are calculated in a three-dimensional process simulation. Thereby, the wall thickness distribution is correlated with an objective function and preform geometry as well as process parameters are varied by an optimization algorithm. Taking into account the correlation between material usage, process history and resulting product properties, integrative coupled simulation steps, e.g. structural analyses or barrier simulations, are performed. The approach is applied on a 0.5 liter PET bottle of Krones AG, Neutraubling, Germany. The investigations point out that the design process can be supported by applying this simulative optimization approach. In an optimization study the total bottle weight is reduced from 18.5 g to 15.5 g. The validation of the computed results is in progress.« less

Simulative design and process optimization of the two-stage stretch-blow molding process

NASA Astrophysics Data System (ADS)

Hopmann, Ch.; Rasche, S.; Windeck, C.

2015-05-01

The total production costs of PET bottles are significantly affected by the costs of raw material. Approximately 70 % of the total costs are spent for the raw material. Therefore, stretch-blow molding industry intends to reduce the total production costs by an optimized material efficiency. However, there is often a trade-off between an optimized material efficiency and required product properties. Due to a multitude of complex boundary conditions, the design process of new stretch-blow molded products is still a challenging task and is often based on empirical knowledge. Application of current CAE-tools supports the design process by reducing development time and costs. This paper describes an approach to determine optimized preform geometry and corresponding process parameters iteratively. The wall thickness distribution and the local stretch ratios of the blown bottle are calculated in a three-dimensional process simulation. Thereby, the wall thickness distribution is correlated with an objective function and preform geometry as well as process parameters are varied by an optimization algorithm. Taking into account the correlation between material usage, process history and resulting product properties, integrative coupled simulation steps, e.g. structural analyses or barrier simulations, are performed. The approach is applied on a 0.5 liter PET bottle of Krones AG, Neutraubling, Germany. The investigations point out that the design process can be supported by applying this simulative optimization approach. In an optimization study the total bottle weight is reduced from 18.5 g to 15.5 g. The validation of the computed results is in progress.

StagBL : A Scalable, Portable, High-Performance Discretization and Solver Layer for Geodynamic Simulation

NASA Astrophysics Data System (ADS)

Sanan, P.; Tackley, P. J.; Gerya, T.; Kaus, B. J. P.; May, D.

2017-12-01

StagBL is an open-source parallel solver and discretization library for geodynamic simulation,encapsulating and optimizing operations essential to staggered-grid finite volume Stokes flow solvers.It provides a parallel staggered-grid abstraction with a high-level interface in C and Fortran.On top of this abstraction, tools are available to define boundary conditions and interact with particle systems.Tools and examples to efficiently solve Stokes systems defined on the grid are provided in small (direct solver), medium (simple preconditioners), and large (block factorization and multigrid) model regimes.By working directly with leading application codes (StagYY, I3ELVIS, and LaMEM) and providing an API and examples to integrate with others, StagBL aims to become a community tool supplying scalable, portable, reproducible performance toward novel science in regional- and planet-scale geodynamics and planetary science.By implementing kernels used by many research groups beneath a uniform abstraction layer, the library will enable optimization for modern hardware, thus reducing community barriers to large- or extreme-scale parallel simulation on modern architectures. In particular, the library will include CPU-, Manycore-, and GPU-optimized variants of matrix-free operators and multigrid components.The common layer provides a framework upon which to introduce innovative new tools.StagBL will leverage p4est to provide distributed adaptive meshes, and incorporate a multigrid convergence analysis tool.These options, in addition to a wealth of solver options provided by an interface to PETSc, will make the most modern solution techniques available from a common interface. StagBL in turn provides a PETSc interface, DMStag, to its central staggered grid abstraction.We present public version 0.5 of StagBL, including preliminary integration with application codes and demonstrations with its own demonstration application, StagBLDemo. Central to StagBL is the notion of an uninterrupted pipeline from toy/teaching codes to high-performance, extreme-scale solves. StagBLDemo replicates the functionality of an advanced MATLAB-style regional geodynamics code, thus providing users with a concrete procedure to exceed the performance and scalability limitations of smaller-scale tools.

PENTrack - a versatile Monte Carlo tool for ultracold neutron sources and experiments

NASA Astrophysics Data System (ADS)

Picker, Ruediger; Chahal, Sanmeet; Christopher, Nicolas; Losekamm, Martin; Marcellin, James; Paul, Stephan; Schreyer, Wolfgang; Yapa, Pramodh

2016-09-01

Ultracold neutrons have energies in the hundred nano eV region. They can be stored in traps for hundreds of seconds. This makes them the ideal tool to study the neutron itself. Measurements of neutron decay correlations, lifetime or electric dipole moment are ideally suited for ultracold neutrons, as well as experiments probing the neutron's gravitational levels in the earth's field. We have developed a Monte Carlo simulation tool that can serve to design and optimize these experiments, and possibly correct results: PENTrack is a C++ based simulation code that tracks neutrons, protons and electrons or atoms, as well as their spins, in gravitational and electromagnetic fields. In addition wall interactions of neutrons due to strong interaction are modeled with a Fermi-potential formalism and take surface roughness into account. The presentation will introduce the physics behind the simulation and provide examples of its application.

OPTIMIZING THROUGH CO-EVOLUTIONARY AVALANCHES

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

S. BOETTCHER; A. PERCUS

2000-08-01

We explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problems. The method, called extremal optimization, is inspired by ''self-organized critically,'' a concept introduced to describe emergent complexity in many physical systems. In contrast to Genetic Algorithms which operate on an entire ''gene-pool'' of possible solutions, extremal optimization successively replaces extremely undesirable elements of a sub-optimal solution with new, random ones. Large fluctuations, called ''avalanches,'' ensue that efficiently explore many local optima. Drawing upon models used to simulate far-from-equilibrium dynamics, extremal optimization complements approximation methods inspired by equilibrium statistical physics, such as simulated annealing. With only onemore » adjustable parameter, its performance has proved competitive with more elaborate methods, especially near phase transitions. Those phase transitions are found in the parameter space of most optimization problems, and have recently been conjectured to be the origin of some of the hardest instances in computational complexity. We will demonstrate how extremal optimization can be implemented for a variety of combinatorial optimization problems. We believe that extremal optimization will be a useful tool in the investigation of phase transitions in combinatorial optimization problems, hence valuable in elucidating the origin of computational complexity.« less

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.

Judicious use of simulation technology in continuing medical education.

PubMed

Curtis, Michael T; DiazGranados, Deborah; Feldman, Moshe

2012-01-01

Use of simulation-based training is fast becoming a vital source of experiential learning in medical education. Although simulation is a common tool for undergraduate and graduate medical education curricula, the utilization of simulation in continuing medical education (CME) is still an area of growth. As more CME programs turn to simulation to address their training needs, it is important to highlight concepts of simulation technology that can help to optimize learning outcomes. This article discusses the role of fidelity in medical simulation. It provides support from a cross section of simulation training domains for determining the appropriate levels of fidelity, and it offers guidelines for creating an optimal balance of skill practice and realism for efficient training outcomes. After defining fidelity, 3 dimensions of fidelity, drawn from the human factors literature, are discussed in terms of their relevance to medical simulation. From this, research-based guidelines are provided to inform CME providers regarding the use of simulation in CME training. Copyright © 2012 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on CME, Association for Hospital Medical Education.

Optimization of metabolite detection by quantum mechanics simulations in magnetic resonance spectroscopy.

PubMed

Gambarota, Giulio

2017-07-15

Magnetic resonance spectroscopy (MRS) is a well established modality for investigating tissue metabolism in vivo. In recent years, many efforts by the scientific community have been directed towards the improvement of metabolite detection and quantitation. Quantum mechanics simulations allow for investigations of the MR signal behaviour of metabolites; thus, they provide an essential tool in the optimization of metabolite detection. In this review, we will examine quantum mechanics simulations based on the density matrix formalism. The density matrix was introduced by von Neumann in 1927 to take into account statistical effects within the theory of quantum mechanics. We will discuss the main steps of the density matrix simulation of an arbitrary spin system and show some examples for the strongly coupled two spin system. Copyright © 2016 Elsevier Inc. All rights reserved.

Optimized FPGA Implementation of the Thyroid Hormone Secretion Mechanism Using CAD Tools.

PubMed

Alghazo, Jaafar M

2017-02-01

The goal of this paper is to implement the secretion mechanism of the Thyroid Hormone (TH) based on bio-mathematical differential eqs. (DE) on an FPGA chip. Hardware Descriptive Language (HDL) is used to develop a behavioral model of the mechanism derived from the DE. The Thyroid Hormone secretion mechanism is simulated with the interaction of the related stimulating and inhibiting hormones. Synthesis of the simulation is done with the aid of CAD tools and downloaded on a Field Programmable Gate Arrays (FPGAs) Chip. The chip output shows identical behavior to that of the designed algorithm through simulation. It is concluded that the chip mimics the Thyroid Hormone secretion mechanism. The chip, operating in real-time, is computer-independent stand-alone system.

Simulation of an Asynchronous Machine by using a Pseudo Bond Graph

NASA Astrophysics Data System (ADS)

Romero, Gregorio; Felez, Jesus; Maroto, Joaquin; Martinez, M. Luisa

2008-11-01

For engineers, computer simulation, is a basic tool since it enables them to understand how systems work without actually needing to see them. They can learn how they work in different circumstances and optimize their design with considerably less cost in terms of time and money than if they had to carry out tests on a physical system. However, if computer simulation is to be reliable it is essential for the simulation model to be validated. There is a wide range of commercial brands on the market offering products for electrical domain simulation (SPICE, LabVIEW PSCAD,Dymola, Simulink, Simplorer,...). These are powerful tools, but require the engineer to have a perfect knowledge of the electrical field. This paper shows an alternative methodology to can simulate an asynchronous machine using the multidomain Bond Graph technique and apply it in any program that permit the simulation of models based in this technique; no extraordinary knowledge of this technique and electric field are required to understand the process .

DISCRETE EVENT SIMULATION OF OPTICAL SWITCH MATRIX PERFORMANCE IN COMPUTER NETWORKS

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

Imam, Neena; Poole, Stephen W

2013-01-01

In this paper, we present application of a Discrete Event Simulator (DES) for performance modeling of optical switching devices in computer networks. Network simulators are valuable tools in situations where one cannot investigate the system directly. This situation may arise if the system under study does not exist yet or the cost of studying the system directly is prohibitive. Most available network simulators are based on the paradigm of discrete-event-based simulation. As computer networks become increasingly larger and more complex, sophisticated DES tool chains have become available for both commercial and academic research. Some well-known simulators are NS2, NS3, OPNET,more » and OMNEST. For this research, we have applied OMNEST for the purpose of simulating multi-wavelength performance of optical switch matrices in computer interconnection networks. Our results suggest that the application of DES to computer interconnection networks provides valuable insight in device performance and aids in topology and system optimization.« less

Design-Optimization Of Cylindrical, Layered Composite Structures Using Efficient Laminate Parameterization

NASA Astrophysics Data System (ADS)

Monicke, A.; Katajisto, H.; Leroy, M.; Petermann, N.; Kere, P.; Perillo, M.

2012-07-01

For many years, layered composites have proven essential for the successful design of high-performance space structures, such as launchers or satellites. A generic cylindrical composite structure for a launcher application was optimized with respect to objectives and constraints typical for space applications. The studies included the structural stability, laminate load response and failure analyses. Several types of cylinders (with and without stiffeners) were considered and optimized using different lay-up parameterizations. Results for the best designs are presented and discussed. The simulation tools, ESAComp [1] and modeFRONTIER [2], employed in the optimization loop are elucidated and their value for the optimization process is explained.

SeGRAm - A practical and versatile tool for spacecraft trajectory optimization

NASA Technical Reports Server (NTRS)

Rishikof, Brian H.; Mccormick, Bernell R.; Pritchard, Robert E.; Sponaugle, Steven J.

1991-01-01

An implementation of the Sequential Gradient/Restoration Algorithm, SeGRAm, is presented along with selected examples. This spacecraft trajectory optimization and simulation program uses variational calculus to solve problems of spacecraft flying under the influence of one or more gravitational bodies. It produces a series of feasible solutions to problems involving a wide range of vehicles, environments and optimization functions, until an optimal solution is found. The examples included highlight the various capabilities of the program and emphasize in particular its versatility over a wide spectrum of applications from ascent to interplanetary trajectories.

Assessment of COTS IR image simulation tools for ATR development

NASA Astrophysics Data System (ADS)

Seidel, Heiko; Stahl, Christoph; Bjerkeli, Frode; Skaaren-Fystro, Paal

2005-05-01

Following the tendency of increased use of imaging sensors in military aircraft, future fighter pilots will need onboard artificial intelligence e.g. ATR for aiding them in image interpretation and target designation. The European Aeronautic Defence and Space Company (EADS) in Germany has developed an advanced method for automatic target recognition (ATR) which is based on adaptive neural networks. This ATR method can assist the crew of military aircraft like the Eurofighter in sensor image monitoring and thereby reduce the workload in the cockpit and increase the mission efficiency. The EADS ATR approach can be adapted for imagery of visual, infrared and SAR sensors because of the training-based classifiers of the ATR method. For the optimal adaptation of these classifiers they have to be trained with appropriate and sufficient image data. The training images must show the target objects from different aspect angles, ranges, environmental conditions, etc. Incomplete training sets lead to a degradation of classifier performance. Additionally, ground truth information i.e. scenario conditions like class type and position of targets is necessary for the optimal adaptation of the ATR method. In Summer 2003, EADS started a cooperation with Kongsberg Defence & Aerospace (KDA) from Norway. The EADS/KDA approach is to provide additional image data sets for training-based ATR through IR image simulation. The joint study aims to investigate the benefits of enhancing incomplete training sets for classifier adaptation by simulated synthetic imagery. EADS/KDA identified the requirements of a commercial-off-the-shelf IR simulation tool capable of delivering appropriate synthetic imagery for ATR development. A market study of available IR simulation tools and suppliers was performed. After that the most promising tool was benchmarked according to several criteria e.g. thermal emission model, sensor model, targets model, non-radiometric image features etc., resulting in a recommendation. The synthetic image data that are used for the investigation are generated using the recommended tool. Within the scope of this study, ATR performance on IR imagery using classifiers trained on real, synthetic and mixed image sets was evaluated. The performance of the adapted classifiers is assessed using recorded IR imagery with known ground-truth and recommendations are given for the use of COTS IR image simulation tools for ATR development.

Structural Optimization for Reliability Using Nonlinear Goal Programming

NASA Technical Reports Server (NTRS)

El-Sayed, Mohamed E.

1999-01-01

This report details the development of a reliability based multi-objective design tool for solving structural optimization problems. Based on two different optimization techniques, namely sequential unconstrained minimization and nonlinear goal programming, the developed design method has the capability to take into account the effects of variability on the proposed design through a user specified reliability design criterion. In its sequential unconstrained minimization mode, the developed design tool uses a composite objective function, in conjunction with weight ordered design objectives, in order to take into account conflicting and multiple design criteria. Multiple design criteria of interest including structural weight, load induced stress and deflection, and mechanical reliability. The nonlinear goal programming mode, on the other hand, provides for a design method that eliminates the difficulty of having to define an objective function and constraints, while at the same time has the capability of handling rank ordered design objectives or goals. For simulation purposes the design of a pressure vessel cover plate was undertaken as a test bed for the newly developed design tool. The formulation of this structural optimization problem into sequential unconstrained minimization and goal programming form is presented. The resulting optimization problem was solved using: (i) the linear extended interior penalty function method algorithm; and (ii) Powell's conjugate directions method. Both single and multi-objective numerical test cases are included demonstrating the design tool's capabilities as it applies to this design problem.

Optimization of Microelectronic Devices for Sensor Applications

NASA Technical Reports Server (NTRS)

Cwik, Tom; Klimeck, Gerhard

2000-01-01

The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization of active and passive sensors, analytical instruments and communication systems among others. Currently, typical system requirements include the detection of particular spectral lines, associated data processing, and communication of the acquired data to other systems. Advances in lithography and deposition methods result in more advanced devices for space application, while the sub-micron resolution currently available opens a vast design space. Though an experimental exploration of this widening design space-searching for optimized performance by repeated fabrication efforts-is unfeasible, it does motivate the development of reliable software design tools. These tools necessitate models based on fundamental physics and mathematics of the device to accurately model effects such as diffraction and scattering in opto-electronic devices, or bandstructure and scattering in heterostructure devices. The software tools must have convenient turn-around times and interfaces that allow effective usage. The first issue is addressed by the application of high-performance computers and the second by the development of graphical user interfaces driven by properly developed data structures. These tools can then be integrated into an optimization environment, and with the available memory capacity and computational speed of high performance parallel platforms, simulation of optimized components can proceed. In this paper, specific applications of the electromagnetic modeling of infrared filtering, as well as heterostructure device design will be presented using genetic algorithm global optimization methods.

Searching for the optimal synthesis parameters of InP/CdxZn1-xSe quantum dots when combined with a broad band phosphor to optimize color rendering and efficacy of a hybrid remote phosphor white LED

NASA Astrophysics Data System (ADS)

Ryckaert, Jana; Correia, António; Smet, Kevin; Tessier, Mickael D.; Dupont, Dorian; Hens, Zeger; Hanselaer, Peter; Meuret, Youri

2017-09-01

Combining traditional phosphors with a broad emission spectrum and non-scattering quantum dots with a narrow emission spectrum can have multiple advantages for white LEDs. It allows to reduce the amount of scattering in the wavelength conversion element, increasing the efficiency of the complete system. Furthermore, the unique possibility to tune the emission spectrum of quantum dots allows to optimize the resulting LED spectrum in order to achieve optimal color rendering properties for the light source. However, finding the optimal quantum dot properties to achieve optimal efficacy and color rendering is a non-trivial task. Instead of simply summing up the emission spectra of the blue LED, phosphor and quantum dots, we propose a complete simulation tool that allows an accurate analysis of the final performance for a range of different quantum dot synthesis parameters. The recycling of the reflected light from the wavelength conversion element by the LED package is taken into account, as well as the re-absorption and the associated red-shift. This simulation tool is used to vary two synthesis parameters (core size and cadmium fraction) of InP/CdxZn1-xSe quantum dots. We find general trends for the ideal quantum dot that should be combined with a specific YAG:Ce broad band phosphor to obtain optimal efficiency and color rendering for a white LED with a specific pumping LED and recycling cavity, with a desired CCT of 3500K.

Frameworks and Tools for High-Confidence Design of Adaptive, Distributed Embedded Control Systems. Multi-University Research Initiative on High-Confidence Design for Distributed Embedded Systems

DTIC Science & Technology

2009-01-01

controllers (currently using the Robostix+Gumstix pair ). The interface between the plant simulator and the controller is ‘hard real-time’, and the xPC box... simulation ) on aerobatic maneuver design for the STARMAC quadrotor helicopter testbed. In related work, we have developed a new optimization scheme...for scheduling hybrid systems, and have demonstrated the results on an autonomous car simulation testbed. We are focusing efforts this summer for

Multi-Objective Bidding Strategy for Genco Using Non-Dominated Sorting Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Saksinchai, Apinat; Boonchuay, Chanwit; Ongsakul, Weerakorn

2010-06-01

This paper proposes a multi-objective bidding strategy for a generation company (GenCo) in uniform price spot market using non-dominated sorting particle swarm optimization (NSPSO). Instead of using a tradeoff technique, NSPSO is introduced to solve the multi-objective strategic bidding problem considering expected profit maximization and risk (profit variation) minimization. Monte Carlo simulation is employed to simulate rivals' bidding behavior. Test results indicate that the proposed approach can provide the efficient non-dominated solution front effectively. In addition, it can be used as a decision making tool for a GenCo compromising between expected profit and price risk in spot market.

Simulation and optimization of faceted structure for illumination

NASA Astrophysics Data System (ADS)

Liu, Lihong; Engel, Thierry; Flury, Manuel

2016-04-01

The re-direction of incoherent light using a surface containing only facets with specific angular values is proposed. A new photometric approach is adopted since the size of each facet is large in comparison with the wavelength. A reflective configuration is employed to avoid the dispersion problems of materials. The irradiance distribution of the reflected beam is determined by the angular position of each facet. In order to obtain the specific irradiance distribution, the angular position of each facet is optimized using Zemax OpticStudio 15 software. A detector is placed in the direction which is perpendicular to the reflected beam. According to the incoherent irradiance distribution on the detector, a merit function needs to be defined to pilot the optimization process. The two dimensional angular position of each facet is defined as a variable which is optimized within a specified varying range. Because the merit function needs to be updated, a macro program is carried out to update this function within Zemax. In order to reduce the complexity of the manual operation, an automatic optimization approach is established. Zemax is in charge of performing the optimization task and sending back the irradiance data to Matlab for further analysis. Several simulation results are given for the verification of the optimization method. The simulation results are compared to those obtained with the LightTools software in order to verify our optimization method.

[Application of ordinary Kriging method in entomologic ecology].

PubMed

Zhang, Runjie; Zhou, Qiang; Chen, Cuixian; Wang, Shousong

2003-01-01

Geostatistics is a statistic method based on regional variables and using the tool of variogram to analyze the spatial structure and the patterns of organism. In simulating the variogram within a great range, though optimal simulation cannot be obtained, the simulation method of a dialogue between human and computer can be used to optimize the parameters of the spherical models. In this paper, the method mentioned above and the weighted polynomial regression were utilized to simulate the one-step spherical model, the two-step spherical model and linear function model, and the available nearby samples were used to draw on the ordinary Kriging procedure, which provided a best linear unbiased estimate of the constraint of the unbiased estimation. The sum of square deviation between the estimating and measuring values of varying theory models were figured out, and the relative graphs were shown. It was showed that the simulation based on the two-step spherical model was the best simulation, and the one-step spherical model was better than the linear function model.

Development and validation of an observation tool for the assessment of nursing pain management practices in intensive care unit in a standardized clinical simulation setting.

PubMed

Gosselin, Emilie; Bourgault, Patricia; Lavoie, Stephan; Coleman, Robin-Marie; Méziat-Burdin, Anne

2014-12-01

Pain management in the intensive care unit is often inadequate. There is no tool available to assess nursing pain management practices. The aim of this study was to develop and validate a measuring tool to assess nursing pain management in the intensive care unit during standardized clinical simulation. A literature review was performed to identify relevant components demonstrating optimal pain management in adult intensive care units and to integrate them in an observation tool. This tool was submitted to an expert panel and pretested. It was then used to assess pain management practice during 26 discrete standardized clinical simulation sessions with intensive care nurses. The Nursing Observation Tool for Pain Management (NOTPaM) contains 28 statements grouped into 8 categories, which are grouped into 4 dimensions: subjective assessment, objective assessment, interventions, and reassessment. The tool's internal consistency was calculated at a Cronbach's alpha of 0.436 for the whole tool; the alpha varies from 0.328 to 0.518 for each dimension. To evaluate the inter-rater reliability, intra-class correlation coefficient was used, which was calculated at 0.751 (p < .001) for the whole tool, with variations from 0.619 to 0.920 (p < .01) between dimensions. The expert panel was satisfied with the content and face validity of the tool. The psychometric qualities of the NOTPaM developed in this study are satisfactory. However, the tool could be improved with slight modifications. Nevertheless, it was useful in assessing intensive care nurses' pain management in a standardized clinical simulation. The NOTPaM is the first tool created for this purpose. Copyright © 2014 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved.

Sub-half-micron contact window design with 3D photolithography simulator

NASA Astrophysics Data System (ADS)

Brainerd, Steve K.; Bernard, Douglas A.; Rey, Juan C.; Li, Jiangwei; Granik, Yuri; Boksha, Victor V.

1997-07-01

In state of the art IC design and manufacturing certain lithography layers have unique requirements. Latitudes and tolerances that apply to contacts and polysilicon gates are tight for such critical layers. Industry experts are discussing the most cost effective ways to use feature- oriented equipment and materials already developed for these layers. Such requirements introduce new dimensions into the traditionally challenging task for the photolithography engineer when considering various combinations of multiple factors to optimize and control the process. In addition, he/she faces a rapidly increasing cost of experiments, limited time and scarce access to equipment to conduct them. All the reasons presented above support simulation as an ideal method to satisfy these demands. However lithography engineers may be easily dissatisfied with a simulation tool when discovering disagreement between the simulation and experimental data. The problem is that several parameters used in photolithography simulation are very process specific. Calibration, i.e. matching experimental and simulation data using a specific set of procedures allows one to effectively use the simulation tool. We present results of a simulation based approach to optimize photolithography processes for sub-0.5 micron contact windows. Our approach consists of: (1) 3D simulation to explore different lithographic options, (2) calibration to a range of process conditions with extensive use of specifically developed optimization techniques. The choice of a 3D simulator is essential because of 3D nature of the problem of contact window design. We use DEPICT 4.1. This program performs fast aerial image simulation as presented before. For 3D exposure the program uses an extension to three-dimensions of the high numerical aperture model combined with Fast Fourier Transforms for maximum performance and accuracy. We use Kim (U.C. Berkeley) model and the fast marching Level Set method respectively for the calculation of resist development rates and resist surface movement during development process. Calibration efforts were aimed at matching experimental results on contact windows obtained after exposure of a binary mask. Additionally, simulation was applied to conduct quantitative analysis of PSM design capabilities, optical proximity correction, and stepper parameter optimization. Extensive experiments covered exposure (ASML 5500/100D stepper), pre- and post-exposure bake and development (2.38% TMAH, puddle process) of JSR IX725D2G and TOK iP3500 photoresists films on 200 mm test wafers. `Aquatar' was used as top antireflective coating, SEM pictures of developed patterns were analyzed and compared with simulation results for different values of defocus, exposure energies, numerical aperture and partial coherence.

Strategies for global optimization in photonics design.

PubMed

Vukovic, Ana; Sewell, Phillip; Benson, Trevor M

2010-10-01

This paper reports on two important issues that arise in the context of the global optimization of photonic components where large problem spaces must be investigated. The first is the implementation of a fast simulation method and associated matrix solver for assessing particular designs and the second, the strategies that a designer can adopt to control the size of the problem design space to reduce runtimes without compromising the convergence of the global optimization tool. For this study an analytical simulation method based on Mie scattering and a fast matrix solver exploiting the fast multipole method are combined with genetic algorithms (GAs). The impact of the approximations of the simulation method on the accuracy and runtime of individual design assessments and the consequent effects on the GA are also examined. An investigation of optimization strategies for controlling the design space size is conducted on two illustrative examples, namely, 60° and 90° waveguide bends based on photonic microstructures, and their effectiveness is analyzed in terms of a GA's ability to converge to the best solution within an acceptable timeframe. Finally, the paper describes some particular optimized solutions found in the course of this work.

NDE and SHM Simulation for CFRP Composites

NASA Technical Reports Server (NTRS)

Leckey, Cara A. C.; Parker, F. Raymond

2014-01-01

Ultrasound-based nondestructive evaluation (NDE) is a common technique for damage detection in composite materials. There is a need for advanced NDE that goes beyond damage detection to damage quantification and characterization in order to enable data driven prognostics. The damage types that exist in carbon fiber-reinforced polymer (CFRP) composites include microcracking and delaminations, and can be initiated and grown via impact forces (due to ground vehicles, tool drops, bird strikes, etc), fatigue, and extreme environmental changes. X-ray microfocus computed tomography data, among other methods, have shown that these damage types often result in voids/discontinuities of a complex volumetric shape. The specific damage geometry and location within ply layers affect damage growth. Realistic threedimensional NDE and structural health monitoring (SHM) simulations can aid in the development and optimization of damage quantification and characterization techniques. This paper is an overview of ongoing work towards realistic NDE and SHM simulation tools for composites, and also discusses NASA's need for such simulation tools in aeronautics and spaceflight. The paper describes the development and implementation of a custom ultrasound simulation tool that is used to model ultrasonic wave interaction with realistic 3-dimensional damage in CFRP composites. The custom code uses elastodynamic finite integration technique and is parallelized to run efficiently on computing cluster or multicore machines.

Mono and multi-objective optimization techniques applied to a large range of industrial test cases using Metamodel assisted Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Fourment, Lionel; Ducloux, Richard; Marie, Stéphane; Ejday, Mohsen; Monnereau, Dominique; Massé, Thomas; Montmitonnet, Pierre

2010-06-01

The use of material processing numerical simulation allows a strategy of trial and error to improve virtual processes without incurring material costs or interrupting production and therefore save a lot of money, but it requires user time to analyze the results, adjust the operating conditions and restart the simulation. Automatic optimization is the perfect complement to simulation. Evolutionary Algorithm coupled with metamodelling makes it possible to obtain industrially relevant results on a very large range of applications within a few tens of simulations and without any specific automatic optimization technique knowledge. Ten industrial partners have been selected to cover the different area of the mechanical forging industry and provide different examples of the forming simulation tools. It aims to demonstrate that it is possible to obtain industrially relevant results on a very large range of applications within a few tens of simulations and without any specific automatic optimization technique knowledge. The large computational time is handled by a metamodel approach. It allows interpolating the objective function on the entire parameter space by only knowing the exact function values at a reduced number of "master points". Two algorithms are used: an evolution strategy combined with a Kriging metamodel and a genetic algorithm combined with a Meshless Finite Difference Method. The later approach is extended to multi-objective optimization. The set of solutions, which corresponds to the best possible compromises between the different objectives, is then computed in the same way. The population based approach allows using the parallel capabilities of the utilized computer with a high efficiency. An optimization module, fully embedded within the Forge2009 IHM, makes possible to cover all the defined examples, and the use of new multi-core hardware to compute several simulations at the same time reduces the needed time dramatically. The presented examples demonstrate the method versatility. They include billet shape optimization of a common rail, the cogging of a bar and a wire drawing problem.

Optimization of Friction Stir Welding Tool Advance Speed via Monte-Carlo Simulation of the Friction Stir Welding Process

PubMed Central

Fraser, Kirk A.; St-Georges, Lyne; Kiss, Laszlo I.

2014-01-01

Recognition of the friction stir welding process is growing in the aeronautical and aero-space industries. To make the process more available to the structural fabrication industry (buildings and bridges), being able to model the process to determine the highest speed of advance possible that will not cause unwanted welding defects is desirable. A numerical solution to the transient two-dimensional heat diffusion equation for the friction stir welding process is presented. A non-linear heat generation term based on an arbitrary piecewise linear model of friction as a function of temperature is used. The solution is used to solve for the temperature distribution in the Al 6061-T6 work pieces. The finite difference solution of the non-linear problem is used to perform a Monte-Carlo simulation (MCS). A polynomial response surface (maximum welding temperature as a function of advancing and rotational speed) is constructed from the MCS results. The response surface is used to determine the optimum tool speed of advance and rotational speed. The exterior penalty method is used to find the highest speed of advance and the associated rotational speed of the tool for the FSW process considered. We show that good agreement with experimental optimization work is possible with this simplified model. Using our approach an optimal weld pitch of 0.52 mm/rev is obtained for 3.18 mm thick AA6061-T6 plate. Our method provides an estimate of the optimal welding parameters in less than 30 min of calculation time. PMID:28788627

Optimization of Friction Stir Welding Tool Advance Speed via Monte-Carlo Simulation of the Friction Stir Welding Process.

PubMed

Fraser, Kirk A; St-Georges, Lyne; Kiss, Laszlo I

2014-04-30

Recognition of the friction stir welding process is growing in the aeronautical and aero-space industries. To make the process more available to the structural fabrication industry (buildings and bridges), being able to model the process to determine the highest speed of advance possible that will not cause unwanted welding defects is desirable. A numerical solution to the transient two-dimensional heat diffusion equation for the friction stir welding process is presented. A non-linear heat generation term based on an arbitrary piecewise linear model of friction as a function of temperature is used. The solution is used to solve for the temperature distribution in the Al 6061-T6 work pieces. The finite difference solution of the non-linear problem is used to perform a Monte-Carlo simulation (MCS). A polynomial response surface (maximum welding temperature as a function of advancing and rotational speed) is constructed from the MCS results. The response surface is used to determine the optimum tool speed of advance and rotational speed. The exterior penalty method is used to find the highest speed of advance and the associated rotational speed of the tool for the FSW process considered. We show that good agreement with experimental optimization work is possible with this simplified model. Using our approach an optimal weld pitch of 0.52 mm/rev is obtained for 3.18 mm thick AA6061-T6 plate. Our method provides an estimate of the optimal welding parameters in less than 30 min of calculation time.

Combining local search with co-evolution in a remarkably simple way

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

Boettcher, S.; Percus, A.

2000-05-01

The authors explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problem. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. In contrast to genetic algorithms, which operate on an entire gene-pool of possible solutions, extremal optimization successively replaces extremely undesirable elements of a single sub-optimal solution with new, random ones. Large fluctuations, or avalanches, ensue that efficiently explore many local optima. Drawing upon models used to simulate far-from-equilibrium dynamics, extremal optimization complements heuristics inspired by equilibrium statistical physics, such as simulated annealing. With only onemore » adjustable parameter, its performance has proved competitive with more elaborate methods, especially near phase transitions. Phase transitions are found in many combinatorial optimization problems, and have been conjectured to occur in the region of parameter space containing the hardest instances. We demonstrate how extremal optimization can be implemented for a variety of hard optimization problems. We believe that this will be a useful tool in the investigation of phase transitions in combinatorial optimization, thereby helping to elucidate the origin of computational complexity.« less

DEVELOPMENT OF COMPUTATIONAL TOOLS FOR OPTIMAL IDENTIFICATION OF BIOLOGICAL NETWORKS

EPA Science Inventory

Following the theoretical analysis and computer simulations, the next step for the development of SNIP will be a proof-of-principle laboratory application. Specifically, we have obtained a synthetic transcriptional cascade (harbored in Escherichia coli...

Numerical simulation of controlled directional solidification under microgravity conditions

NASA Astrophysics Data System (ADS)

Holl, S.; Roos, D.; Wein, J.

The computer-assisted simulation of solidification processes influenced by gravity has gained increased importance during the previous years regarding ground-based as well as microgravity research. Depending on the specific needs of the investigator, the simulation model ideally covers a broad spectrum of applications. These primarily include the optimization of furnace design in interaction with selected process parameters to meet the desired crystallization conditions. Different approaches concerning the complexity of the simulation models as well as their dedicated applications will be discussed in this paper. Special emphasis will be put on the potential of software tools to increase the scientific quality and cost-efficiency of microgravity experimentation. The results gained so far in the context of TEXUS, FSLP, D-1 and D-2 (preparatory program) experiments, highlighting their simulation-supported preparation and evaluation will be discussed. An outlook will then be given on the possibilities to enhance the efficiency of pre-industrial research in the Columbus era through the incorporation of suitable simulation methods and tools.

Three-dimensional data-tracking dynamic optimization simulations of human locomotion generated by direct collocation.

PubMed

Lin, Yi-Chung; Pandy, Marcus G

2017-07-05

The aim of this study was to perform full-body three-dimensional (3D) dynamic optimization simulations of human locomotion by driving a neuromusculoskeletal model toward in vivo measurements of body-segmental kinematics and ground reaction forces. Gait data were recorded from 5 healthy participants who walked at their preferred speeds and ran at 2m/s. Participant-specific data-tracking dynamic optimization solutions were generated for one stride cycle using direct collocation in tandem with an OpenSim-MATLAB interface. The body was represented as a 12-segment, 21-degree-of-freedom skeleton actuated by 66 muscle-tendon units. Foot-ground interaction was simulated using six contact spheres under each foot. The dynamic optimization problem was to find the set of muscle excitations needed to reproduce 3D measurements of body-segmental motions and ground reaction forces while minimizing the time integral of muscle activations squared. Direct collocation took on average 2.7±1.0h and 2.2±1.6h of CPU time, respectively, to solve the optimization problems for walking and running. Model-computed kinematics and foot-ground forces were in good agreement with corresponding experimental data while the calculated muscle excitation patterns were consistent with measured EMG activity. The results demonstrate the feasibility of implementing direct collocation on a detailed neuromusculoskeletal model with foot-ground contact to accurately and efficiently generate 3D data-tracking dynamic optimization simulations of human locomotion. The proposed method offers a viable tool for creating feasible initial guesses needed to perform predictive simulations of movement using dynamic optimization theory. The source code for implementing the model and computational algorithm may be downloaded at http://simtk.org/home/datatracking. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of EnergyPlus for use in residential building energy optimization

NASA Astrophysics Data System (ADS)

Spencer, Justin S.

This work explored the utility of EnergyPlus as a simulation engine for doing residential building energy optimization, with the objective of finding the modeling areas that require further development in EnergyPlus for residential optimization applications. This work was conducted primarily during 2006-2007, with publication occurring later in 2010. The assessments and recommendations apply to the simulation tool versions available in 2007. During this work, an EnergyPlus v2.0 (2007) input file generator was developed for use in BEopt 0.8.0.4 (2007). BEopt 0.8.0.4 is a residential Building Energy optimization program developed at the National Renewable Energy Laboratory in Golden, Colorado. Residential modeling capabilities of EnergyPlus v2.0 were scrutinized and tested. Modeling deficiencies were identified in a number of areas. These deficiencies were compared to deficiencies in the DOE2.2 V44E4(2007)/TRNSYS simulation engines. The highest priority gaps in EnergyPlus v2.0's residential modeling capability are in infiltration, duct leakage, and foundation modeling. Optimization results from DOE2.2 V44E4 and EnergyPlus v2.0 were analyzed to search for modeling differences that have a significant impact on optimization results. Optimal buildings at different energy savings levels were compared to look for biases. It was discovered that the EnergyPlus v2.0 optimizations consistently chose higher wall insulation levels than the DOE2.2 V44E4 optimizations. The points composing the optimal paths chosen by DOE2.2 V44E4 and EnergyPlus v2.0 were compared to look for points chosen by one optimization that were significantly different from the other optimal path. These outliers were compared to consensus optimal points to determine the simulation differences that cause disparities in the optimization results. The differences were primarily caused by modeling of window radiation exchange and HVAC autosizing.

Engineering Effort Needed to Design Spacecraft with Radiation Constraints

NASA Technical Reports Server (NTRS)

Singleterry, Robert C., Jr.

2005-01-01

A roadmap is articulated that describes what is needed to allow designers, to include researchers, management, and engineers, to investigate, design, build, test, and fly spacecraft that meet the mission requirements yet, be as low cost as possible. This roadmap describes seven levels of tool fidelity and application: 1) Mission Speculation, 2) Management Overview, 3) Mission Design, 4) Detailed Design, 5) Simulation and Training, 6) Operations, and 7) Research. The interfaces and output are described in top-level detail along with the transport engines needed, and deficiencies are noted. This roadmap, if implemented, will allow Multidisciplinary Optimization (MDO) ideas to incorporate radiation concerns. Also, as NASA moves towards Simulation Based Acquisition (SBA), these tools will facilitate the appropriate spending of government money. Most of the tools needed to serve these levels do not exist or exist in pieces and need to be integrated to create the tool.

Didactic tools for understanding respiratory physiology

NASA Astrophysics Data System (ADS)

Donnelly Kehoe, P.; Bratovich, C.; Perrone, Ms; Mendez Castells, L.

2007-11-01

The challenges in Bioengineering are not only the application of engineering knowledge to the measurement of physiological variables, but also the simulation of biological systems. Experience has shown that the physiology of the respiratory system involves a set of concepts that cannot be effectively taught without the help of a group of didactic tools that contribute to the measurement of characteristic specific variables and to the simulation of the system itself. This article describes a series of tools designed to optimize the teaching of the respiratory system, including the use of spirometers and software developed entirely by undergraduate Bioengineering students from Universidad Nacional de Entre Rios (UNER). The impact these resources have caused on the understanding of the topic and how each of them has facilitated the interpretation of the concepts by the students is also discussed.

Surgical resource utilization in urban terrorist bombing: a computer simulation.

PubMed

Hirshberg, A; Stein, M; Walden, R

1999-09-01

The objective of this study was to analyze the utilization of surgical staff and facilities during an urban terrorist bombing incident. A discrete-event computer model of the emergency room and related hospital facilities was constructed and implemented, based on cumulated data from 12 urban terrorist bombing incidents in Israel. The simulation predicts that the admitting capacity of the hospital depends primarily on the number of available surgeons and defines an optimal staff profile for surgeons, residents, and trauma nurses. The major bottlenecks in the flow of critical casualties are the shock rooms and the computed tomographic scanner but not the operating rooms. The simulation also defines the number of reinforcement staff needed to treat noncritical casualties and shows that radiology is the major obstacle to the flow of these patients. Computer simulation is an important new tool for the optimization of surgical service elements for a multiple-casualty situation.

Moving-window dynamic optimization: design of stimulation profiles for walking.

PubMed

Dosen, Strahinja; Popović, Dejan B

2009-05-01

The overall goal of the research is to improve control for electrical stimulation-based assistance of walking in hemiplegic individuals. We present the simulation for generating offline input (sensors)-output (intensity of muscle stimulation) representation of walking that serves in synthesizing a rule-base for control of electrical stimulation for restoration of walking. The simulation uses new algorithm termed moving-window dynamic optimization (MWDO). The optimization criterion was to minimize the sum of the squares of tracking errors from desired trajectories with the penalty function on the total muscle efforts. The MWDO was developed in the MATLAB environment and tested using target trajectories characteristic for slow-to-normal walking recorded in healthy individual and a model with the parameters characterizing the potential hemiplegic user. The outputs of the simulation are piecewise constant intensities of electrical stimulation and trajectories generated when the calculated stimulation is applied to the model. We demonstrated the importance of this simulation by showing the outputs for healthy and hemiplegic individuals, using the same target trajectories. Results of the simulation show that the MWDO is an efficient tool for analyzing achievable trajectories and for determining the stimulation profiles that need to be delivered for good tracking.

Methods and tools to simulate the effect of economic instruments in complex water resources systems. Application to the Jucar river basin.

NASA Astrophysics Data System (ADS)

Lopez-Nicolas, Antonio; Pulido-Velazquez, Manuel

2014-05-01

The main challenge of the BLUEPRINT to safeguard Europe's water resources (EC, 2012) is to guarantee that enough good quality water is available for people's needs, the economy and the environment. In this sense, economic policy instruments such as water pricing policies and water markets can be applied to enhance efficient use of water. This paper presents a method based on hydro-economic tools to assess the effect of economic instruments on water resource systems. Hydro-economic models allow integrated analysis of water supply, demand and infrastructure operation at the river basin scale, by simultaneously combining engineering, hydrologic and economic aspects of water resources management. The method made use of the simulation and optimization hydroeconomic tools SIMGAMS and OPTIGAMS. The simulation tool SIMGAMS allocates water resources among the users according to priorities and operating rules, and evaluate economic scarcity costs of the system by using economic demand functions. The model's objective function is designed so that the system aims to meet the operational targets (ranked according to priorities) at each month while following the system operating rules. The optimization tool OPTIGAMS allocates water resources based on an economic efficiency criterion: maximize net benefits, or alternatively, minimizing the total water scarcity and operating cost of water use. SIMGAS allows to simulate incentive water pricing policies based on marginal resource opportunity costs (MROC; Pulido-Velazquez et al., 2013). Storage-dependent step pricing functions are derived from the time series of MROC values at a certain reservoir in the system. These water pricing policies are defined based on water availability in the system (scarcity pricing), so that when water storage is high, the MROC is low, while low storage (drought periods) will be associated to high MROC and therefore, high prices. We also illustrate the use of OPTIGAMS to simulate the effect of ideal water markets by economic optimization, without considering the potential effect of transaction costs. These methods and tools have been applied to the Jucar River basin (Spain). The results show the potential of economic instruments in setting incentives for a more efficient management of water resources systems. Acknowledgments: The study has been partially supported by the European Community 7th Framework Project (GENESIS project, n. 226536), SAWARES (Plan Nacional I+D+i 2008-2011, CGL2009-13238-C02-01 and C02-02), SCARCE (Consolider-Ingenio 2010 CSD2009-00065) of the Spanish Ministry of Economy and Competitiveness; and EC 7th Framework Project ENHANCE (n. 308438) Reference: Pulido-Velazquez, M., Alvarez-Mendiola, E., and Andreu, J., 2013. Design of Efficient Water Pricing Policies Integrating Basinwide Resource Opportunity Costs. J. Water Resour. Plann. Manage., 139(5): 583-592.

Satellite Constellation Optimization for Turkish Armed Forces

DTIC Science & Technology

2013-03-01

capability. 29 III. OPTIMIZATION WITH STK A. ANALYSIS The goal was to minimize the number of satellites and then minimize the number of planes...www.oosa.unvienna.org/pdf/reports/ac105/AC105_1005E.pdf. Wertz, James R. and Larson, Wiley J. “Space Mission Analysis and Design (Third Edition).” Space...Systems Tool Kit software for simulation and analysis of several possible communications and remote sensing satellite constellations covering Turkish

Summary of hydrologic modeling for the Delaware River Basin using the Water Availability Tool for Environmental Resources (WATER)

USGS Publications Warehouse

Williamson, Tanja N.; Lant, Jeremiah G.; Claggett, Peter; Nystrom, Elizabeth A.; Milly, Paul C.D.; Nelson, Hugh L.; Hoffman, Scott A.; Colarullo, Susan J.; Fischer, Jeffrey M.

2015-11-18

The Water Availability Tool for Environmental Resources (WATER) is a decision support system for the nontidal part of the Delaware River Basin that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. In order to quantify the uncertainty associated with these simulations, however, streamflow and the associated hydroclimatic variables of potential evapotranspiration, actual evapotranspiration, and snow accumulation and snowmelt must be simulated and compared to long-term, daily observations from sites. This report details model development and optimization, statistical evaluation of simulations for 57 basins ranging from 2 to 930 km2 and 11.0 to 99.5 percent forested cover, and how this statistical evaluation of daily streamflow relates to simulating environmental changes and management decisions that are best examined at monthly time steps normalized over multiple decades. The decision support system provides a database of historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover and general circulation model forecasts that focus on 2030 and 2060. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that were parameterized by using three hydrologic response units: forested, agricultural, and developed land cover. This integration enables the regional hydrologic modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model.

[The interactive neuroanatomical simulation and practical application of frontotemporal transsylvian exposure in neurosurgery].

PubMed

Balogh, Attila; Czigléczki, Gábor; Papal, Zsolt; Preul, Mark C; Banczerowski, Péter

2014-11-30

There is an increased need for new digital education tools in neurosurgical training. Illustrated textbooks offer anatomic and technical reference but do not substitute hands-on experience provided by surgery or cadaver dissection. Due to limited availability of cadaver dissections the need for development of simulation tools has been augmented. We explored simulation technology for producing virtual reality-like reconstructions of simulated surgical approaches on cadaver. Practical application of the simulation tool has been presented through frontotemporal transsylvian exposure. The dissections were performed on two cadaveric heads. Arteries and veins were prepared and injected with colorful silicon rubber. The heads were rigidly fixed in Mayfield headholder. A robotic microscope with two digital cameras in inverted cone method of image acquisition was used to capture images around a pivot point in several phases of dissections. Multilayered, high-resolution images have been built into interactive 4D environment by custom developed software. We have developed the simulation module of the frontotemporal transsylvian approach. The virtual specimens can be rotated or tilted to any selected angles and examined from different surgical perspectives at any stage of dissections. Important surgical issues such as appropriate head positioning or surgical maneuvers to expose deep situated neuroanatomic structures can be simulated and studied by using the module. The simulation module of the frontotemporal transsylvian exposure helps to examine effect of head positioning on the visibility of deep situated neuroanatomic structures and study surgical maneuvers required to achieve optimal exposure of deep situated anatomic structures. The simulation program is a powerful tool to study issues of preoperative planning and well suited for neurosurgical training.

VEDA: a web-based virtual environment for dynamic atomic force microscopy.

PubMed

Melcher, John; Hu, Shuiqing; Raman, Arvind

2008-06-01

We describe here the theory and applications of virtual environment dynamic atomic force microscopy (VEDA), a suite of state-of-the-art simulation tools deployed on nanoHUB (www.nanohub.org) for the accurate simulation of tip motion in dynamic atomic force microscopy (dAFM) over organic and inorganic samples. VEDA takes advantage of nanoHUB's cyberinfrastructure to run high-fidelity dAFM tip dynamics computations on local clusters and the teragrid. Consequently, these tools are freely accessible and the dAFM simulations are run using standard web-based browsers without requiring additional software. A wide range of issues in dAFM ranging from optimal probe choice, probe stability, and tip-sample interaction forces, power dissipation, to material property extraction and scanning dynamics over hetereogeneous samples can be addressed.

Invited Article: VEDA: A web-based virtual environment for dynamic atomic force microscopy

NASA Astrophysics Data System (ADS)

Melcher, John; Hu, Shuiqing; Raman, Arvind

2008-06-01

We describe here the theory and applications of virtual environment dynamic atomic force microscopy (VEDA), a suite of state-of-the-art simulation tools deployed on nanoHUB (www.nanohub.org) for the accurate simulation of tip motion in dynamic atomic force microscopy (dAFM) over organic and inorganic samples. VEDA takes advantage of nanoHUB's cyberinfrastructure to run high-fidelity dAFM tip dynamics computations on local clusters and the teragrid. Consequently, these tools are freely accessible and the dAFM simulations are run using standard web-based browsers without requiring additional software. A wide range of issues in dAFM ranging from optimal probe choice, probe stability, and tip-sample interaction forces, power dissipation, to material property extraction and scanning dynamics over hetereogeneous samples can be addressed.

X-ray optics simulation and beamline design for the APS upgrade

NASA Astrophysics Data System (ADS)

Shi, Xianbo; Reininger, Ruben; Harder, Ross; Haeffner, Dean

2017-08-01

The upgrade of the Advanced Photon Source (APS) to a Multi-Bend Achromat (MBA) will increase the brightness of the APS by between two and three orders of magnitude. The APS upgrade (APS-U) project includes a list of feature beamlines that will take full advantage of the new machine. Many of the existing beamlines will be also upgraded to profit from this significant machine enhancement. Optics simulations are essential in the design and optimization of these new and existing beamlines. In this contribution, the simulation tools used and developed at APS, ranging from analytical to numerical methods, are summarized. Three general optical layouts are compared in terms of their coherence control and focusing capabilities. The concept of zoom optics, where two sets of focusing elements (e.g., CRLs and KB mirrors) are used to provide variable beam sizes at a fixed focal plane, is optimized analytically. The effects of figure errors on the vertical spot size and on the local coherence along the vertical direction of the optimized design are investigated.

A mathematical tool to generate complex whole body motor tasks and test hypotheses on underlying motor planning.

PubMed

Tagliabue, Michele; Pedrocchi, Alessandra; Pozzo, Thierry; Ferrigno, Giancarlo

2008-01-01

In spite of the complexity of human motor behavior, difficulties in mathematical modeling have restricted to rather simple movements attempts to identify the motor planning criterion used by the central nervous system. This paper presents a novel-simulation technique able to predict the "desired trajectory" corresponding to a wide range of kinematic and kinetic optimality criteria for tasks involving many degrees of freedom and the coordination between goal achievement and balance maintenance. Employment of proper time discretization, inverse dynamic methods and constrained optimization technique are combined. The application of this simulator to a planar whole body pointing movement shows its effectiveness in managing system nonlinearities and instability as well as in ensuring the anatomo-physiological feasibility of predicted motor plans. In addition, the simulator's capability to simultaneously optimize competing movement aspects represents an interesting opportunity for the motor control community, in which the coexistence of several controlled variables has been hypothesized.

Simulation Based Optimization of Complex Monolithic Composite Structures Using Cellular Core Technology

NASA Astrophysics Data System (ADS)

Hickmott, Curtis W.

Cellular core tooling is a new technology which has the capability to manufacture complex integrated monolithic composite structures. This novel tooling method utilizes thermoplastic cellular cores as inner tooling. The semi-rigid nature of the cellular cores makes them convenient for lay-up, and under autoclave temperature and pressure they soften and expand providing uniform compaction on all surfaces including internal features such as ribs and spar tubes. This process has the capability of developing fully optimized aerospace structures by reducing or eliminating assembly using fasteners or bonded joints. The technology is studied in the context of evaluating its capabilities, advantages, and limitations in developing high quality structures. The complex nature of these parts has led to development of a model using the Finite Element Analysis (FEA) software Abaqus and the plug-in COMPRO Common Component Architecture (CCA) provided by Convergent Manufacturing Technologies. This model utilizes a "virtual autoclave" technique to simulate temperature profiles, resin flow paths, and ultimately deformation from residual stress. A model has been developed simulating the temperature profile during curing of composite parts made with the cellular core technology. While modeling of composites has been performed in the past, this project will look to take this existing knowledge and apply it to this new manufacturing method capable of building more complex parts and develop a model designed specifically for building large, complex components with a high degree of accuracy. The model development has been carried out in conjunction with experimental validation. A double box beam structure was chosen for analysis to determine the effects of the technology on internal ribs and joints. Double box beams were manufactured and sectioned into T-joints for characterization. Mechanical behavior of T-joints was performed using the T-joint pull-off test and compared to traditional tooling methods. Components made with the cellular core tooling method showed an improved strength at the joints. It is expected that this knowledge will help optimize the processing of complex, integrated structures and benefit applications in aerospace where lighter, structurally efficient components would be advantageous.

Improving the performance of surgery-based clinical pathways: a simulation-optimization approach.

PubMed

Ozcan, Yasar A; Tànfani, Elena; Testi, Angela

2017-03-01

This paper aims to improve the performance of clinical processes using clinical pathways (CPs). The specific goal of this research is to develop a decision support tool, based on a simulation-optimization approach, which identify the proper adjustment and alignment of resources to achieve better performance for both the patients and the health-care facility. When multiple perspectives are present in a decision problem, critical issues arise and often require the balancing of goals. In our approach, meeting patients' clinical needs in a timely manner, and to avoid worsening of clinical conditions, we assess the level of appropriate resources. The simulation-optimization model seeks and evaluates alternative resource configurations aimed at balancing the two main objectives-meeting patient needs and optimal utilization of beds and operating rooms.Using primary data collected at a Department of Surgery of a public hospital located in Genoa, Italy. The simulation-optimization modelling approach in this study has been applied to evaluate the thyroid surgical treatment together with the other surgery-based CPs. The low rate of bed utilization and the long elective waiting lists of the specialty under study indicates that the wards were oversized while the operating room capacity was the bottleneck of the system. The model enables hospital managers determine which objective has to be given priority, as well as the corresponding opportunity costs.

Dynamic approximate entropy electroanatomic maps detect rotors in a simulated atrial fibrillation model.

PubMed

Ugarte, Juan P; Orozco-Duque, Andrés; Tobón, Catalina; Kremen, Vaclav; Novak, Daniel; Saiz, Javier; Oesterlein, Tobias; Schmitt, Clauss; Luik, Armin; Bustamante, John

2014-01-01

There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping.

The Integrated Medical Model

NASA Technical Reports Server (NTRS)

Butler, Douglas J.; Kerstman, Eric

2010-01-01

This slide presentation reviews the goals and approach for the Integrated Medical Model (IMM). The IMM is a software decision support tool that forecasts medical events during spaceflight and optimizes medical systems during simulations. It includes information on the software capabilities, program stakeholders, use history, and the software logic.

Space Communications and Navigation (SCaN) Network Simulation Tool Development and Its Use Cases

NASA Technical Reports Server (NTRS)

Jennings, Esther; Borgen, Richard; Nguyen, Sam; Segui, John; Stoenescu, Tudor; Wang, Shin-Ywan; Woo, Simon; Barritt, Brian; Chevalier, Christine; Eddy, Wesley

2009-01-01

In this work, we focus on the development of a simulation tool to assist in analysis of current and future (proposed) network architectures for NASA. Specifically, the Space Communications and Navigation (SCaN) Network is being architected as an integrated set of new assets and a federation of upgraded legacy systems. The SCaN architecture for the initial missions for returning humans to the moon and beyond will include the Space Network (SN) and the Near-Earth Network (NEN). In addition to SCaN, the initial mission scenario involves a Crew Exploration Vehicle (CEV), the International Space Station (ISS) and NASA Integrated Services Network (NISN). We call the tool being developed the SCaN Network Integration and Engineering (SCaN NI&E) Simulator. The intended uses of such a simulator are: (1) to characterize performance of particular protocols and configurations in mission planning phases; (2) to optimize system configurations by testing a larger parameter space than may be feasible in either production networks or an emulated environment; (3) to test solutions in order to find issues/risks before committing more significant resources needed to produce real hardware or flight software systems. We describe two use cases of the tool: (1) standalone simulation of CEV to ISS baseline scenario to determine network performance, (2) participation in Distributed Simulation Integration Laboratory (DSIL) tests to perform function testing and verify interface and interoperability of geographically dispersed simulations/emulations.

Computational tool for simulation of power and refrigeration cycles

NASA Astrophysics Data System (ADS)

Córdoba Tuta, E.; Reyes Orozco, M.

2016-07-01

Small improvement in thermal efficiency of power cycles brings huge cost savings in the production of electricity, for that reason have a tool for simulation of power cycles allows modeling the optimal changes for a best performance. There is also a big boom in research Organic Rankine Cycle (ORC), which aims to get electricity at low power through cogeneration, in which the working fluid is usually a refrigerant. A tool to design the elements of an ORC cycle and the selection of the working fluid would be helpful, because sources of heat from cogeneration are very different and in each case would be a custom design. In this work the development of a multiplatform software for the simulation of power cycles and refrigeration, which was implemented in the C ++ language and includes a graphical interface which was developed using multiplatform environment Qt and runs on operating systems Windows and Linux. The tool allows the design of custom power cycles, selection the type of fluid (thermodynamic properties are calculated through CoolProp library), calculate the plant efficiency, identify the fractions of flow in each branch and finally generates a report very educational in pdf format via the LaTeX tool.

Common Methodology for Efficient Airspace Operations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar

2012-01-01

Topics include: a) Developing a common methodology to model and avoid disturbances affecting airspace. b) Integrated contrails and emission models to a national level airspace simulation. c) Developed capability to visualize, evaluate technology and alternate operational concepts and provide inputs for policy-analysis tools to reduce the impact of aviation on the environment. d) Collaborating with Volpe Research Center, NOAA and DLR to leverage expertise and tools in aircraft emissions and weather/climate modeling. Airspace operations is a trade-off balancing safety, capacity, efficiency and environmental considerations. Ideal flight: Unimpeded wind optimal route with optimal climb and descent. Operations degraded due to reduction in airport and airspace capacity caused by inefficient procedures and disturbances.

SU-G-BRC-10: Feasibility of a Web-Based Monte Carlo Simulation Tool for Dynamic Electron Arc Radiotherapy (DEAR)

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

Rodrigues, A; Wu, Q; Sawkey, D

Purpose: DEAR is a radiation therapy technique utilizing synchronized motion of gantry and couch during delivery to optimize dose distribution homogeneity and penumbra for treatment of superficial disease. Dose calculation for DEAR is not yet supported by commercial TPSs. The purpose of this study is to demonstrate the feasibility of using a web-based Monte Carlo (MC) simulation tool (VirtuaLinac) to calculate dose distributions for a DEAR delivery. Methods: MC simulations were run through VirtuaLinac, which is based on the GEANT4 platform. VirtuaLinac utilizes detailed linac head geometry and material models, validated phase space files, and a voxelized phantom. The inputmore » was expanded to include an XML file for simulation of varying mechanical axes as a function of MU. A DEAR XML plan was generated and used in the MC simulation and delivered on a TrueBeam in Developer Mode. Radiographic film wrapped on a cylindrical phantom (12.5 cm radius) measured dose at a depth of 1.5 cm and compared to the simulation results. Results: A DEAR plan was simulated using an energy of 6 MeV and a 3×10 cm{sup 2} cut-out in a 15×15 cm{sup 2} applicator for a delivery of a 90° arc. The resulting data were found to provide qualitative and quantitative evidence that the simulation platform could be used as the basis for DEAR dose calculations. The resulting unwrapped 2D dose distributions agreed well in the cross-plane direction along the arc, with field sizes of 18.4 and 18.2 cm and penumbrae of 1.9 and 2.0 cm for measurements and simulations, respectively. Conclusion: Preliminary feasibility of a DEAR delivery using a web-based MC simulation platform has been demonstrated. This tool will benefit treatment planning for DEAR as a benchmark for developing other model based algorithms, allowing efficient optimization of trajectories, and quality assurance of plans without the need for extensive measurements.« less

Thermal energy and economic analysis of a PCM-enhanced household envelope considering different climate zones in Morocco

NASA Astrophysics Data System (ADS)

Kharbouch, Yassine; Mimet, Abdelaziz; El Ganaoui, Mohammed; Ouhsaine, Lahoucine

2018-07-01

This study investigates the thermal energy potentials and economic feasibility of an air-conditioned family household-integrated phase change material (PCM) considering different climate zones in Morocco. A simulation-based optimisation was carried out in order to define the optimal design of a PCM-enhanced household envelope for thermal energy effectiveness and cost-effectiveness of predefined candidate solutions. The optimisation methodology is based on coupling Energyplus® as a dynamic simulation tool and GenOpt® as an optimisation tool. Considering the obtained optimum design strategies, a thermal energy and economic analysis are carried out to investigate PCMs' integration feasibility in the Moroccan constructions. The results show that the PCM-integrated household envelope allows minimising the cooling/heating thermal energy demand vs. a reference household without PCM. While for the cost-effectiveness optimisation, it has been deduced that the economic feasibility is stilling insufficient under the actual PCM market conditions. The optimal design parameters results are also analysed.

Noise tolerant illumination optimization applied to display devices

NASA Astrophysics Data System (ADS)

Cassarly, William J.; Irving, Bruce

2005-02-01

Display devices have historically been designed through an iterative process using numerous hardware prototypes. This process is effective but the number of iterations is limited by the time and cost to make the prototypes. In recent years, virtual prototyping using illumination software modeling tools has replaced many of the hardware prototypes. Typically, the designer specifies the design parameters, builds the software model, predicts the performance using a Monte Carlo simulation, and uses the performance results to repeat this process until an acceptable design is obtained. What is highly desired, and now possible, is to use illumination optimization to automate the design process. Illumination optimization provides the ability to explore a wider range of design options while also providing improved performance. Since Monte Carlo simulations are often used to calculate the system performance but those predictions have statistical uncertainty, the use of noise tolerant optimization algorithms is important. The use of noise tolerant illumination optimization is demonstrated by considering display device designs that extract light using 2D paint patterns as well as 3D textured surfaces. A hybrid optimization approach that combines a mesh feedback optimization with a classical optimizer is demonstrated. Displays with LED sources and cold cathode fluorescent lamps are considered.

A Photofission Delayed γ-ray Spectra Calculation Tool for the Conception of a Nuclear Material Characterization Facility

NASA Astrophysics Data System (ADS)

Bernard, D.; Serot, O.; Simon, E.; Boucher, L.; Plumeri, S.

2018-01-01

The photon interrogation analysis is a nondestructive technique allowing to identify and quantify fissile materials in nuclear waste packages. This paper details an automatic procedure which has been developed to simulate the delayed γ-ray spectra for several actinide photofissions. This calculation tool will be helpful for the fine conception (collimation, shielding, noise background optimizations, etc.) and for the on-line analysis of such a facility.

The development of a volume element model for energy systems engineering and integrative thermodynamic optimization

NASA Astrophysics Data System (ADS)

Yang, Sam

The dissertation presents the mathematical formulation, experimental validation, and application of a volume element model (VEM) devised for modeling, simulation, and optimization of energy systems in their early design stages. The proposed model combines existing modeling techniques and experimental adjustment to formulate a reduced-order model, while retaining sufficient accuracy to serve as a practical system-level design analysis and optimization tool. In the VEM, the physical domain under consideration is discretized in space using lumped hexahedral elements (i.e., volume elements), and the governing equations for the variable of interest are applied to each element to quantify diverse types of flows that cross it. Subsequently, a system of algebraic and ordinary differential equations is solved with respect to time and scalar (e.g., temperature, relative humidity, etc.) fields are obtained in both spatial and temporal domains. The VEM is capable of capturing and predicting dynamic physical behaviors in the entire system domain (i.e., at system level), including mutual interactions among system constituents, as well as with their respective surroundings and cooling systems, if any. The VEM is also generalizable; that is, the model can be easily adapted to simulate and optimize diverse systems of different scales and complexity and attain numerical convergence with sufficient accuracy. Both the capability and generalizability of the VEM are demonstrated in the dissertation via thermal modeling and simulation of an Off-Grid Zero Emissions Building, an all-electric ship, and a vapor compression refrigeration (VCR) system. Furthermore, the potential of the VEM as an optimization tool is presented through the integrative thermodynamic optimization of a VCR system, whose results are used to evaluate the trade-offs between various objective functions, namely, coefficient of performance, second law efficiency, pull-down time, and refrigerated space temperature, in both transient and steady-state operations.

TU-AB-BRC-12: Optimized Parallel MonteCarlo Dose Calculations for Secondary MU Checks

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

French, S; Nazareth, D; Bellor, M

Purpose: Secondary MU checks are an important tool used during a physics review of a treatment plan. Commercial software packages offer varying degrees of theoretical dose calculation accuracy, depending on the modality involved. Dose calculations of VMAT plans are especially prone to error due to the large approximations involved. Monte Carlo (MC) methods are not commonly used due to their long run times. We investigated two methods to increase the computational efficiency of MC dose simulations with the BEAMnrc code. Distributed computing resources, along with optimized code compilation, will allow for accurate and efficient VMAT dose calculations. Methods: The BEAMnrcmore » package was installed on a high performance computing cluster accessible to our clinic. MATLAB and PYTHON scripts were developed to convert a clinical VMAT DICOM plan into BEAMnrc input files. The BEAMnrc installation was optimized by running the VMAT simulations through profiling tools which indicated the behavior of the constituent routines in the code, e.g. the bremsstrahlung splitting routine, and the specified random number generator. This information aided in determining the most efficient compiling parallel configuration for the specific CPU’s available on our cluster, resulting in the fastest VMAT simulation times. Our method was evaluated with calculations involving 10{sup 8} – 10{sup 9} particle histories which are sufficient to verify patient dose using VMAT. Results: Parallelization allowed the calculation of patient dose on the order of 10 – 15 hours with 100 parallel jobs. Due to the compiler optimization process, further speed increases of 23% were achieved when compared with the open-source compiler BEAMnrc packages. Conclusion: Analysis of the BEAMnrc code allowed us to optimize the compiler configuration for VMAT dose calculations. In future work, the optimized MC code, in conjunction with the parallel processing capabilities of BEAMnrc, will be applied to provide accurate and efficient secondary MU checks.« less

SPOKES: An end-to-end simulation facility for spectroscopic cosmological surveys

DOE PAGES

Nord, B.; Amara, A.; Refregier, A.; ...

2016-03-03

The nature of dark matter, dark energy and large-scale gravity pose some of the most pressing questions in cosmology today. These fundamental questions require highly precise measurements, and a number of wide-field spectroscopic survey instruments are being designed to meet this requirement. A key component in these experiments is the development of a simulation tool to forecast science performance, define requirement flow-downs, optimize implementation, demonstrate feasibility, and prepare for exploitation. We present SPOKES (SPectrOscopic KEn Simulation), an end-to-end simulation facility for spectroscopic cosmological surveys designed to address this challenge. SPOKES is based on an integrated infrastructure, modular function organization, coherentmore » data handling and fast data access. These key features allow reproducibility of pipeline runs, enable ease of use and provide flexibility to update functions within the pipeline. The cyclic nature of the pipeline offers the possibility to make the science output an efficient measure for design optimization and feasibility testing. We present the architecture, first science, and computational performance results of the simulation pipeline. The framework is general, but for the benchmark tests, we use the Dark Energy Spectrometer (DESpec), one of the early concepts for the upcoming project, the Dark Energy Spectroscopic Instrument (DESI). As a result, we discuss how the SPOKES framework enables a rigorous process to optimize and exploit spectroscopic survey experiments in order to derive high-precision cosmological measurements optimally.« less

Polycrystalline CVD diamond device level modeling for particle detection applications

NASA Astrophysics Data System (ADS)

Morozzi, A.; Passeri, D.; Kanxheri, K.; Servoli, L.; Lagomarsino, S.; Sciortino, S.

2016-12-01

Diamond is a promising material whose excellent physical properties foster its use for radiation detection applications, in particular in those hostile operating environments where the silicon-based detectors behavior is limited due to the high radiation fluence. Within this framework, the application of Technology Computer Aided Design (TCAD) simulation tools is highly envisaged for the study, the optimization and the predictive analysis of sensing devices. Since the novelty of using diamond in electronics, this material is not included in the library of commercial, state-of-the-art TCAD software tools. In this work, we propose the development, the application and the validation of numerical models to simulate the electrical behavior of polycrystalline (pc)CVD diamond conceived for diamond sensors for particle detection. The model focuses on the characterization of a physically-based pcCVD diamond bandgap taking into account deep-level defects acting as recombination centers and/or trap states. While a definite picture of the polycrystalline diamond band-gap is still debated, the effect of the main parameters (e.g. trap densities, capture cross-sections, etc.) can be deeply investigated thanks to the simulated approach. The charge collection efficiency due to β -particle irradiation of diamond materials provided by different vendors and with different electrode configurations has been selected as figure of merit for the model validation. The good agreement between measurements and simulation findings, keeping the traps density as the only one fitting parameter, assesses the suitability of the TCAD modeling approach as a predictive tool for the design and the optimization of diamond-based radiation detectors.

Spot and Runway Departure Advisor

NASA Technical Reports Server (NTRS)

Jung, Yoon Chul

2013-01-01

The Spot and Runway Departure Advisor (SARDA) is a research prototype of a decision support tool for ATC tower controllers to assist in manging and controlling traffic on the surface of an airport. SARDA employs a scheduler to generate an optimal runway schedule and gate push-back - spot release sequence and schedule that improves efficiency of surface operations. The advisories for ATC tower controllers are displayed on an Electronic Flight Strip (EFS) system. The human-in-the-loop simulation of the SARDA tool was conducted for east operations of Dallas-Ft. Worth International Airport (DFW) to evaluate performance of the SARDA tool and human factors, such as situational awareness and workload. The results indicates noticeable taxi delay reduction and fuel savings by using the SARDA tool. Reduction in controller workload were also observed throughout the scenario runs. The future plan includes modeling and simulation of the ramp operations of the Charlotte International Airport, and develop a decision support tool for the ramp controllers.

Numerical simulation of the casting process of titanium tooth crowns and bridges.

PubMed

Wu, M; Augthun, M; Wagner, I; Sahm, P R; Spiekermann, H

2001-06-01

The objectives of this paper were to simulate the casting process of titanium tooth crowns and bridges; to predict and control porosity defect. A casting simulation software, MAGMASOFT, was used. The geometry of the crowns with fine details of the occlusal surface were digitized by means of laser measuring technique, then converted and read in the simulation software. Both mold filling and solidification were simulated, the shrinkage porosity was predicted by a "feeding criterion", and the gas pore sensitivity was studied based on the mold filling and solidification simulations. Two types of dental prostheses (a single-crown casting and a three-unit-bridge) with various sprue designs were numerically "poured", and only one optimal design for each prosthesis was recommended for real casting trial. With the numerically optimized design, real titanium dental prostheses (five replicas for each) were made on a centrifugal casting machine. All the castings endured radiographic examination, and no porosity was detected in the cast prostheses. It indicates that the numerical simulation is an efficient tool for dental casting design and porosity control. Copyright 2001 Kluwer Academic Publishers

Virtual reality simulation for the optimization of endovascular procedures: current perspectives.

PubMed

Rudarakanchana, Nung; Van Herzeele, Isabelle; Desender, Liesbeth; Cheshire, Nicholas J W

2015-01-01

Endovascular technologies are rapidly evolving, often requiring coordination and cooperation between clinicians and technicians from diverse specialties. These multidisciplinary interactions lead to challenges that are reflected in the high rate of errors occurring during endovascular procedures. Endovascular virtual reality (VR) simulation has evolved from simple benchtop devices to full physic simulators with advanced haptics and dynamic imaging and physiological controls. The latest developments in this field include the use of fully immersive simulated hybrid angiosuites to train whole endovascular teams in crisis resource management and novel technologies that enable practitioners to build VR simulations based on patient-specific anatomy. As our understanding of the skills, both technical and nontechnical, required for optimal endovascular performance improves, the requisite tools for objective assessment of these skills are being developed and will further enable the use of VR simulation in the training and assessment of endovascular interventionalists and their entire teams. Simulation training that allows deliberate practice without danger to patients may be key to bridging the gap between new endovascular technology and improved patient outcomes.

Strength Analysis and Process Simulation of Subway Contact Rail Support Bracket of Composite Materials

NASA Astrophysics Data System (ADS)

Fedulov, Boris N.; Safonov, Alexander A.; Sergeichev, Ivan V.; Ushakov, Andrey E.; Klenin, Yuri G.; Makarenko, Irina V.

2016-10-01

An application of composites for construction of subway brackets is a very effective approach to extend their lifetime. However, this approach involves the necessity to prevent process-induced distortions of the bracket due to thermal deformation and chemical shrinkage. At present study, a process simulation has been carried out to support the design of the production tooling. The simulation was based on the application of viscoelastic model for the resin. Simulation results were verified by comparison with results of manufacturing experiments. To optimize the bracket structure the strength analysis was carried out as well.

Monte-Carlo background simulations of present and future detectors in x-ray astronomy

NASA Astrophysics Data System (ADS)

Tenzer, C.; Kendziorra, E.; Santangelo, A.

2008-07-01

Reaching a low-level and well understood internal instrumental background is crucial for the scientific performance of an X-ray detector and, therefore, a main objective of the instrument designers. Monte-Carlo simulations of the physics processes and interactions taking place in a space-based X-ray detector as a result of its orbital environment can be applied to explain the measured background of existing missions. They are thus an excellent tool to predict and optimize the background of future observatories. Weak points of a design and the main sources of the background can be identified and methods to reduce them can be implemented and studied within the simulations. Using the Geant4 Monte-Carlo toolkit, we have created a simulation environment for space-based detectors and we present results of such background simulations for XMM-Newton's EPIC pn-CCD camera. The environment is also currently used to estimate and optimize the background of the future instruments Simbol-X and eRosita.

Radiofrequency ablation of hepatic tumors: simulation, planning, and contribution of virtual reality and haptics.

PubMed

Villard, Caroline; Soler, Luc; Gangi, Afshin

2005-08-01

For radiofrequency ablation (RFA) of liver tumors, evaluation of vascular architecture, post-RFA necrosis prediction, and the choice of a suitable needle placement strategy using conventional radiological techniques remain difficult. In an attempt to enhance the safety of RFA, a 3D simulator, treatment planning, and training tool, that simulates the insertion of the needle, the necrosis of the treated area, and proposes an optimal needle placement, has been developed. The 3D scenes are automatically reconstructed from enhanced spiral CT scans. The simulator takes into account the cooling effect of local vessels greater than 3 mm in diameter, making necrosis shapes more realistic. Optimal needle positioning can be automatically generated by the software to produce complete destruction of the tumor, with maximum respect of the healthy liver and of all major structures to avoid. We also studied how the use of virtual reality and haptic devices are valuable to make simulation and training realistic and effective.

Maestro: an orchestration framework for large-scale WSN simulations.

PubMed

Riliskis, Laurynas; Osipov, Evgeny

2014-03-18

Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation.

Maestro: An Orchestration Framework for Large-Scale WSN Simulations

PubMed Central

Riliskis, Laurynas; Osipov, Evgeny

2014-01-01

Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation. PMID:24647123

Developing a Hydrologic Assessment Tool for Designing Bioretention in a watershed

NASA Astrophysics Data System (ADS)

Baek, Sangsoo; Ligaray, Mayzonee; Park, Jeong-Pyo; Kwon, Yongsung; Cho, Kyung Hwa

2017-04-01

Continuous urbanization has negatively impacted the ecological and hydrological environments at the global, regional, and local scales. This issue was addressed by developing Low Impact Development (LID) practices to deliver better hydrologic function and improve the environmental, economic, social and cultural outcomes. This study developed a modeling software to simulate and optimize bioretentions among LID in a given watershed. The model calculated a detailed soil infiltration process in bioretention with hydrological conditions and hydraulic facilities (e.g. riser and underdrain) and also generated an optimized plan using Flow Duration Curve (FDC). The optimization result from the simulation demonstrated that the location and size of bioretention, as well as the soil texture, are important elements for an efficient bioretention. We hope that the developed software in this study could be useful for establishing an appropriate scheme of LID installment

Optimal Operation of a Thermal Energy Storage Tank Using Linear Optimization

NASA Astrophysics Data System (ADS)

Civit Sabate, Carles

In this thesis, an optimization procedure for minimizing the operating costs of a Thermal Energy Storage (TES) tank is presented. The facility in which the optimization is based is the combined cooling, heating, and power (CCHP) plant at the University of California, Irvine. TES tanks provide the ability of decoupling the demand of chilled water from its generation, over the course of a day, from the refrigeration and air-conditioning plants. They can be used to perform demand-side management, and optimization techniques can help to approach their optimal use. The proposed optimization approach provides a fast and reliable methodology of finding the optimal use of the TES tank to reduce energy costs and provides a tool for future implementation of optimal control laws on the system. Advantages of the proposed methodology are studied using simulation with historical data.

Advanced power analysis methodology targeted to the optimization of a digital pixel readout chip design and its critical serial powering system

NASA Astrophysics Data System (ADS)

Marconi, S.; Orfanelli, S.; Karagounis, M.; Hemperek, T.; Christiansen, J.; Placidi, P.

2017-02-01

A dedicated power analysis methodology, based on modern digital design tools and integrated with the VEPIX53 simulation framework developed within RD53 collaboration, is being used to guide vital choices for the design and optimization of the next generation ATLAS and CMS pixel chips and their critical serial powering circuit (shunt-LDO). Power consumption is studied at different stages of the design flow under different operating conditions. Significant effort is put into extensive investigations of dynamic power variations in relation with the decoupling seen by the powering network. Shunt-LDO simulations are also reported to prove the reliability at the system level.

Technologies to Increase PV Hosting Capacity in Distribution Feeders: Preprint

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

Ding, Fei; Mather, Barry; Gotseff, Peter

This paper studies the distributed photovoltaic (PV) hosting capacity in distribution feeders by using the stochastic analysis approach. Multiple scenario simulations are conducted to analyze several factors that affect PV hosting capacity, including the existence of voltage regulator, PV location, the power factor of PV inverter and Volt/VAR control. Based on the conclusions obtained from simulation results, three approaches are then proposed to increase distributed PV hosting capacity, which can be formulated as the optimization problem to obtain the optimal solution. All technologies investigated in this paper utilize only existing assets in the feeder and therefore are implementable for amore » low cost. Additionally, the tool developed for these studies is described.« less

Technologies to Increase PV Hosting Capacity in Distribution Feeders

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

Ding, Fei; Mather, Barry; Gotseff, Peter

This paper studies the distributed photovoltaic (PV) hosting capacity in distribution feeders by using the stochastic analysis approach. Multiple scenario simulations are conducted to analyze several factors that affect PV hosting capacity, including the existence of voltage regulator, PV location, the power factor of PV inverter and Volt/VAR control. Based on the conclusions obtained from simulation results, three approaches are then proposed to increase distributed PV hosting capacity, which can be formulated as the optimization problem to obtain the optimal solution. All technologies investigated in this paper utilize only existing assets in the feeder and therefore are implementable for amore » low cost. Additionally, the tool developed for these studies is described.« less

Use of EPANET solver to manage water distribution in Smart City

NASA Astrophysics Data System (ADS)

Antonowicz, A.; Brodziak, R.; Bylka, J.; Mazurkiewicz, J.; Wojtecki, S.; Zakrzewski, P.

2018-02-01

Paper presents a method of using EPANET solver to support manage water distribution system in Smart City. The main task is to develop the application that allows remote access to the simulation model of the water distribution network developed in the EPANET environment. Application allows to perform both single and cyclic simulations with the specified step of changing the values of the selected process variables. In the paper the architecture of application was shown. The application supports the selection of the best device control algorithm using optimization methods. Optimization procedures are possible with following methods: brute force, SLSQP (Sequential Least SQuares Programming), Modified Powell Method. Article was supplemented by example of using developed computer tool.

Homogeneous Canine Chest Phantom Construction: A Tool for Image Quality Optimization.

PubMed

Pavan, Ana Luiza Menegatti; Rosa, Maria Eugênia Dela; Giacomini, Guilherme; Bacchim Neto, Fernando Antonio; Yamashita, Seizo; Vulcano, Luiz Carlos; Duarte, Sergio Barbosa; Miranda, José Ricardo de Arruda; de Pina, Diana Rodrigues

2016-01-01

Digital radiographic imaging is increasing in veterinary practice. The use of radiation demands responsibility to maintain high image quality. Low doses are necessary because workers are requested to restrain the animal. Optimizing digital systems is necessary to avoid unnecessary exposure, causing the phenomenon known as dose creep. Homogeneous phantoms are widely used to optimize image quality and dose. We developed an automatic computational methodology to classify and quantify tissues (i.e., lung tissue, adipose tissue, muscle tissue, and bone) in canine chest computed tomography exams. The thickness of each tissue was converted to simulator materials (i.e., Lucite, aluminum, and air). Dogs were separated into groups of 20 animals each according to weight. Mean weights were 6.5 ± 2.0 kg, 15.0 ± 5.0 kg, 32.0 ± 5.5 kg, and 50.0 ± 12.0 kg, for the small, medium, large, and giant groups, respectively. The one-way analysis of variance revealed significant differences in all simulator material thicknesses (p < 0.05) quantified between groups. As a result, four phantoms were constructed for dorsoventral and lateral views. In conclusion, the present methodology allows the development of phantoms of the canine chest and possibly other body regions and/or animals. The proposed phantom is a practical tool that may be employed in future work to optimize veterinary X-ray procedures.

Meta-heuristic algorithms as tools for hydrological science

NASA Astrophysics Data System (ADS)

Yoo, Do Guen; Kim, Joong Hoon

2014-12-01

In this paper, meta-heuristic optimization techniques are introduced and their applications to water resources engineering, particularly in hydrological science are introduced. In recent years, meta-heuristic optimization techniques have been introduced that can overcome the problems inherent in iterative simulations. These methods are able to find good solutions and require limited computation time and memory use without requiring complex derivatives. Simulation-based meta-heuristic methods such as Genetic algorithms (GAs) and Harmony Search (HS) have powerful searching abilities, which can occasionally overcome the several drawbacks of traditional mathematical methods. For example, HS algorithms can be conceptualized from a musical performance process and used to achieve better harmony; such optimization algorithms seek a near global optimum determined by the value of an objective function, providing a more robust determination of musical performance than can be achieved through typical aesthetic estimation. In this paper, meta-heuristic algorithms and their applications (focus on GAs and HS) in hydrological science are discussed by subject, including a review of existing literature in the field. Then, recent trends in optimization are presented and a relatively new technique such as Smallest Small World Cellular Harmony Search (SSWCHS) is briefly introduced, with a summary of promising results obtained in previous studies. As a result, previous studies have demonstrated that meta-heuristic algorithms are effective tools for the development of hydrological models and the management of water resources.

Homogeneous Canine Chest Phantom Construction: A Tool for Image Quality Optimization

PubMed Central

2016-01-01

Digital radiographic imaging is increasing in veterinary practice. The use of radiation demands responsibility to maintain high image quality. Low doses are necessary because workers are requested to restrain the animal. Optimizing digital systems is necessary to avoid unnecessary exposure, causing the phenomenon known as dose creep. Homogeneous phantoms are widely used to optimize image quality and dose. We developed an automatic computational methodology to classify and quantify tissues (i.e., lung tissue, adipose tissue, muscle tissue, and bone) in canine chest computed tomography exams. The thickness of each tissue was converted to simulator materials (i.e., Lucite, aluminum, and air). Dogs were separated into groups of 20 animals each according to weight. Mean weights were 6.5 ± 2.0 kg, 15.0 ± 5.0 kg, 32.0 ± 5.5 kg, and 50.0 ± 12.0 kg, for the small, medium, large, and giant groups, respectively. The one-way analysis of variance revealed significant differences in all simulator material thicknesses (p < 0.05) quantified between groups. As a result, four phantoms were constructed for dorsoventral and lateral views. In conclusion, the present methodology allows the development of phantoms of the canine chest and possibly other body regions and/or animals. The proposed phantom is a practical tool that may be employed in future work to optimize veterinary X-ray procedures. PMID:27101001

Simulated single molecule microscopy with SMeagol.

PubMed

Lindén, Martin; Ćurić, Vladimir; Boucharin, Alexis; Fange, David; Elf, Johan

2016-08-01

SMeagol is a software tool to simulate highly realistic microscopy data based on spatial systems biology models, in order to facilitate development, validation and optimization of advanced analysis methods for live cell single molecule microscopy data. SMeagol runs on Matlab R2014 and later, and uses compiled binaries in C for reaction-diffusion simulations. Documentation, source code and binaries for Mac OS, Windows and Ubuntu Linux can be downloaded from http://smeagol.sourceforge.net johan.elf@icm.uu.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Development of the ARISTOTLE webware for cloud-based rarefied gas flow modeling

NASA Astrophysics Data System (ADS)

Deschenes, Timothy R.; Grot, Jonathan; Cline, Jason A.

2016-11-01

Rarefied gas dynamics are important for a wide variety of applications. An improvement in the ability of general users to predict these gas flows will enable optimization of current, and discovery of future processes. Despite this potential, most rarefied simulation software is designed by and for experts in the community. This has resulted in low adoption of the methods outside of the immediate RGD community. This paper outlines an ongoing effort to create a rarefied gas dynamics simulation tool that can be used by a general audience. The tool leverages a direct simulation Monte Carlo (DSMC) library that is available to the entire community and a web-based simulation process that will enable all users to take advantage of high performance computing capabilities. First, the DSMC library and simulation architecture are described. Then the DSMC library is used to predict a number of representative transient gas flows that are applicable to the rarefied gas dynamics community. The paper closes with a summary and future direction.

Parameter Estimation of Computationally Expensive Watershed Models Through Efficient Multi-objective Optimization and Interactive Decision Analytics

NASA Astrophysics Data System (ADS)

Akhtar, Taimoor; Shoemaker, Christine

2016-04-01

Watershed model calibration is inherently a multi-criteria problem. Conflicting trade-offs exist between different quantifiable calibration criterions indicating the non-existence of a single optimal parameterization. Hence, many experts prefer a manual approach to calibration where the inherent multi-objective nature of the calibration problem is addressed through an interactive, subjective, time-intensive and complex decision making process. Multi-objective optimization can be used to efficiently identify multiple plausible calibration alternatives and assist calibration experts during the parameter estimation process. However, there are key challenges to the use of multi objective optimization in the parameter estimation process which include: 1) multi-objective optimization usually requires many model simulations, which is difficult for complex simulation models that are computationally expensive; and 2) selection of one from numerous calibration alternatives provided by multi-objective optimization is non-trivial. This study proposes a "Hybrid Automatic Manual Strategy" (HAMS) for watershed model calibration to specifically address the above-mentioned challenges. HAMS employs a 3-stage framework for parameter estimation. Stage 1 incorporates the use of an efficient surrogate multi-objective algorithm, GOMORS, for identification of numerous calibration alternatives within a limited simulation evaluation budget. The novelty of HAMS is embedded in Stages 2 and 3 where an interactive visual and metric based analytics framework is available as a decision support tool to choose a single calibration from the numerous alternatives identified in Stage 1. Stage 2 of HAMS provides a goodness-of-fit measure / metric based interactive framework for identification of a small subset (typically less than 10) of meaningful and diverse set of calibration alternatives from the numerous alternatives obtained in Stage 1. Stage 3 incorporates the use of an interactive visual analytics framework for decision support in selection of one parameter combination from the alternatives identified in Stage 2. HAMS is applied for calibration of flow parameters of a SWAT model, (Soil and Water Assessment Tool) designed to simulate flow in the Cannonsville watershed in upstate New York. Results from the application of HAMS to Cannonsville indicate that efficient multi-objective optimization and interactive visual and metric based analytics can bridge the gap between the effective use of both automatic and manual strategies for parameter estimation of computationally expensive watershed models.

Simulation supported POD for RT test case-concept and modeling

NASA Astrophysics Data System (ADS)

Gollwitzer, C.; Bellon, C.; Deresch, A.; Ewert, U.; Jaenisch, G.-R.; Zscherpel, U.; Mistral, Q.

2012-05-01

Within the framework of the European project PICASSO, the radiographic simulator aRTist (analytical Radiographic Testing inspection simulation tool) developed by BAM has been extended for reliability assessment of film and digital radiography. NDT of safety relevant components of aerospace industry requires the proof of probability of detection (POD) of the inspection. Modeling tools can reduce the expense of such extended, time consuming NDT trials, if the result of simulation fits to the experiment. Our analytic simulation tool consists of three modules for the description of the radiation source, the interaction of radiation with test pieces and flaws, and the detection process with special focus on film and digital industrial radiography. It features high processing speed with near-interactive frame rates and a high level of realism. A concept has been developed as well as a software extension for reliability investigations, completed by a user interface for planning automatic simulations with varying parameters and defects. Furthermore, an automatic image analysis procedure is included to evaluate the defect visibility. The radiographic modeling from 3D CAD of aero engine components and quality test samples are compared as a precondition for real trials. This enables the evaluation and optimization of film replacement for application of modern digital equipment for economical NDT and defined POD.

Performance optimization for space-based sensors: simulation and modelling at Fraunhofer IOSB

NASA Astrophysics Data System (ADS)

Schweitzer, Caroline; Stein, Karin

2014-10-01

The prediction of the effectiveness of a space-based sensor for its designated application in space (e.g. special earth surface observations or missile detection) can help to reduce the expenses, especially during the phases of mission planning and instrumentation. In order to optimize the performance of such systems we simulate and analyse the entire operational scenario, including: - optional waveband - various orbit heights and viewing angles - system design characteristics, e. g. pixel size and filter transmission - atmospheric effects, e. g. different cloud types, climate zones and seasons In the following, an evaluation of the appropriate infrared (IR) waveband for the designated sensor application is given. The simulation environment is also capable of simulating moving objects like aircraft or missiles. Therefore, the spectral signature of the object/missile as well as its track along a flight path is implemented. The resulting video sequence is then analysed by a tracking algorithm and an estimation of the effectiveness of the sensor system can be simulated. This paper summarizes the work carried out at Fraunhofer IOSB in the field of simulation and modelling for the performance optimization of space based sensors. The paper is structured as follows: First, an overview of the applied simulation and modelling software is given. Then, the capability of those tools is illustrated by means of a hypothetical threat scenario for space-based early warning (launch of a long-range ballistic missile (BM)).

Monitoring Object Library Usage and Changes

NASA Technical Reports Server (NTRS)

Owen, R. K.; Craw, James M. (Technical Monitor)

1995-01-01

The NASA Ames Numerical Aerodynamic Simulation program Aeronautics Consolidated Supercomputing Facility (NAS/ACSF) supercomputing center services over 1600 users, and has numerous analysts with root access. Several tools have been developed to monitor object library usage and changes. Some of the tools do "noninvasive" monitoring and other tools implement run-time logging even for object-only libraries. The run-time logging identifies who, when, and what is being used. The benefits are that real usage can be measured, unused libraries can be discontinued, training and optimization efforts can be focused at those numerical methods that are actually used. An overview of the tools will be given and the results will be discussed.

Atomdroid: a computational chemistry tool for mobile platforms.

PubMed

Feldt, Jonas; Mata, Ricardo A; Dieterich, Johannes M

2012-04-23

We present the implementation of a new molecular mechanics program designed for use in mobile platforms, the first specifically built for these devices. The software is designed to run on Android operating systems and is compatible with several modern tablet-PCs and smartphones available in the market. It includes molecular viewer/builder capabilities with integrated routines for geometry optimizations and Monte Carlo simulations. These functionalities allow it to work as a stand-alone tool. We discuss some particular development aspects, as well as the overall feasibility of using computational chemistry software packages in mobile platforms. Benchmark calculations show that through efficient implementation techniques even hand-held devices can be used to simulate midsized systems using force fields.

PyOperators: Operators and solvers for high-performance computing

NASA Astrophysics Data System (ADS)

Chanial, P.; Barbey, N.

2012-12-01

PyOperators is a publicly available library that provides basic operators and solvers for small-to-very large inverse problems ({http://pchanial.github.com/pyoperators}). It forms the backbone of the package PySimulators, which implements specific operators to construct an instrument model and means to conveniently represent a map, a timeline or a time-dependent observation ({http://pchanial.github.com/pysimulators}). Both are part of the Tamasis (Tools for Advanced Map-making, Analysis and SImulations of Submillimeter surveys) toolbox, aiming at providing versatile, reliable, easy-to-use, and optimal map-making tools for Herschel and future generation of sub-mm instruments. The project is a collaboration between 4 institutes (ESO Garching, IAS Orsay, CEA Saclay, Univ. Leiden).

Conceptual achievement of 1GBq activity in a Plasma Focus driven system.

PubMed

Tabbakh, Farshid; Sadat Kiai, Seyed Mahmood; Pashaei, Mohammad

2017-11-01

This is an approach to evaluate the radioisotope production by means of typical dense plasma focus devices. The production rate of the appropriate positron emitters, F-18, N-13 and O-15 has been studied. The beam-target mechanism was simulated by GEANT4 Monte Carlo tool using QGSP_BIC and QGSP_INCLXX physic models as comparison. The results for positron emitters have been evaluated by reported experimental data and found conformity between simulations and experimental reports that leads to using this code as a reliable tool in optimizing the DPF driven systems for achieving to 1GBq activity of produced radioisotope. Copyright © 2017 Elsevier Ltd. All rights reserved.

PICASSO: an end-to-end image simulation tool for space and airborne imaging systems

NASA Astrophysics Data System (ADS)

Cota, Steve A.; Bell, Jabin T.; Boucher, Richard H.; Dutton, Tracy E.; Florio, Chris J.; Franz, Geoffrey A.; Grycewicz, Thomas J.; Kalman, Linda S.; Keller, Robert A.; Lomheim, Terrence S.; Paulson, Diane B.; Willkinson, Timothy S.

2008-08-01

The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image quality within real world constraints such as cost, schedule and overall risk. Image chain analysis - the prediction of image quality from fundamental design parameters - is an important part of this design process. At The Aerospace Corporation we have been using a variety of image chain analysis tools for many years, the Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) among them. In this paper we describe our PICASSO tool, showing how, starting with a high quality input image and hypothetical design descriptions representative of the current state of the art in commercial imaging satellites, PICASSO can generate standard metrics of image quality in support of the decision processes of designers and program managers alike.

PICASSO: an end-to-end image simulation tool for space and airborne imaging systems

NASA Astrophysics Data System (ADS)

Cota, Stephen A.; Bell, Jabin T.; Boucher, Richard H.; Dutton, Tracy E.; Florio, Christopher J.; Franz, Geoffrey A.; Grycewicz, Thomas J.; Kalman, Linda S.; Keller, Robert A.; Lomheim, Terrence S.; Paulson, Diane B.; Wilkinson, Timothy S.

2010-06-01

The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image quality within real world constraints such as cost, schedule and overall risk. Image chain analysis - the prediction of image quality from fundamental design parameters - is an important part of this design process. At The Aerospace Corporation we have been using a variety of image chain analysis tools for many years, the Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) among them. In this paper we describe our PICASSO tool, showing how, starting with a high quality input image and hypothetical design descriptions representative of the current state of the art in commercial imaging satellites, PICASSO can generate standard metrics of image quality in support of the decision processes of designers and program managers alike.

Harnessing the power of emerging petascale platforms

NASA Astrophysics Data System (ADS)

Mellor-Crummey, John

2007-07-01

As part of the US Department of Energy's Scientific Discovery through Advanced Computing (SciDAC-2) program, science teams are tackling problems that require computational simulation and modeling at the petascale. A grand challenge for computer science is to develop software technology that makes it easier to harness the power of these systems to aid scientific discovery. As part of its activities, the SciDAC-2 Center for Scalable Application Development Software (CScADS) is building open source software tools to support efficient scientific computing on the emerging leadership-class platforms. In this paper, we describe two tools for performance analysis and tuning that are being developed as part of CScADS: a tool for analyzing scalability and performance, and a tool for optimizing loop nests for better node performance. We motivate these tools by showing how they apply to S3D, a turbulent combustion code under development at Sandia National Laboratory. For S3D, our node performance analysis tool helped uncover several performance bottlenecks. Using our loop nest optimization tool, we transformed S3D's most costly loop nest to reduce execution time by a factor of 2.94 for a processor working on a 503 domain.

Engaging Undergraduate Math Majors in Geoscience Research using Interactive Simulations and Computer Art

NASA Astrophysics Data System (ADS)

Matott, L. S.; Hymiak, B.; Reslink, C. F.; Baxter, C.; Aziz, S.

2012-12-01

As part of the NSF-sponsored 'URGE (Undergraduate Research Group Experiences) to Compute' program, Dr. Matott has been collaborating with talented Math majors to explore the design of cost-effective systems to safeguard groundwater supplies from contaminated sites. Such activity is aided by a combination of groundwater modeling, simulation-based optimization, and high-performance computing - disciplines largely unfamiliar to the students at the outset of the program. To help train and engage the students, a number of interactive and graphical software packages were utilized. Examples include: (1) a tutorial for exploring the behavior of evolutionary algorithms and other heuristic optimizers commonly used in simulation-based optimization; (2) an interactive groundwater modeling package for exploring alternative pump-and-treat containment scenarios at a contaminated site in Billings, Montana; (3) the R software package for visualizing various concepts related to subsurface hydrology; and (4) a job visualization tool for exploring the behavior of numerical experiments run on a large distributed computing cluster. Further engagement and excitement in the program was fostered by entering (and winning) a computer art competition run by the Coalition for Academic Scientific Computation (CASC). The winning submission visualizes an exhaustively mapped optimization cost surface and dramatically illustrates the phenomena of artificial minima - valley locations that correspond to designs whose costs are only partially optimal.

Fast multipurpose Monte Carlo simulation for proton therapy using multi- and many-core CPU architectures.

PubMed

Souris, Kevin; Lee, John Aldo; Sterpin, Edmond

2016-04-01

Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithm of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the gate/geant4 Monte Carlo application for homogeneous and heterogeneous geometries. Comparisons with gate/geant4 for various geometries show deviations within 2%-1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10(7) primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.

Performance index and meta-optimization of a direct search optimization method

NASA Astrophysics Data System (ADS)

Krus, P.; Ölvander, J.

2013-10-01

Design optimization is becoming an increasingly important tool for design, often using simulation as part of the evaluation of the objective function. A measure of the efficiency of an optimization algorithm is of great importance when comparing methods. The main contribution of this article is the introduction of a singular performance criterion, the entropy rate index based on Shannon's information theory, taking both reliability and rate of convergence into account. It can also be used to characterize the difficulty of different optimization problems. Such a performance criterion can also be used for optimization of the optimization algorithms itself. In this article the Complex-RF optimization method is described and its performance evaluated and optimized using the established performance criterion. Finally, in order to be able to predict the resources needed for optimization an objective function temperament factor is defined that indicates the degree of difficulty of the objective function.

Asymptotic analysis of SPTA-based algorithms for no-wait flow shop scheduling problem with release dates.

PubMed

Ren, Tao; Zhang, Chuan; Lin, Lin; Guo, Meiting; Xie, Xionghang

2014-01-01

We address the scheduling problem for a no-wait flow shop to optimize total completion time with release dates. With the tool of asymptotic analysis, we prove that the objective values of two SPTA-based algorithms converge to the optimal value for sufficiently large-sized problems. To further enhance the performance of the SPTA-based algorithms, an improvement scheme based on local search is provided for moderate scale problems. New lower bound is presented for evaluating the asymptotic optimality of the algorithms. Numerical simulations demonstrate the effectiveness of the proposed algorithms.

Asymptotic Analysis of SPTA-Based Algorithms for No-Wait Flow Shop Scheduling Problem with Release Dates

PubMed Central

Ren, Tao; Zhang, Chuan; Lin, Lin; Guo, Meiting; Xie, Xionghang

2014-01-01

We address the scheduling problem for a no-wait flow shop to optimize total completion time with release dates. With the tool of asymptotic analysis, we prove that the objective values of two SPTA-based algorithms converge to the optimal value for sufficiently large-sized problems. To further enhance the performance of the SPTA-based algorithms, an improvement scheme based on local search is provided for moderate scale problems. New lower bound is presented for evaluating the asymptotic optimality of the algorithms. Numerical simulations demonstrate the effectiveness of the proposed algorithms. PMID:24764774

A three-dimensional inverse finite element analysis of the heel pad.

PubMed

Chokhandre, Snehal; Halloran, Jason P; van den Bogert, Antonie J; Erdemir, Ahmet

2012-03-01

Quantification of plantar tissue behavior of the heel pad is essential in developing computational models for predictive analysis of preventive treatment options such as footwear for patients with diabetes. Simulation based studies in the past have generally adopted heel pad properties from the literature, in return using heel-specific geometry with material properties of a different heel. In exceptional cases, patient-specific material characterization was performed with simplified two-dimensional models, without further evaluation of a heel-specific response under different loading conditions. The aim of this study was to conduct an inverse finite element analysis of the heel in order to calculate heel-specific material properties in situ. Multidimensional experimental data available from a previous cadaver study by Erdemir et al. ("An Elaborate Data Set Characterizing the Mechanical Response of the Foot," ASME J. Biomech. Eng., 131(9), pp. 094502) was used for model development, optimization, and evaluation of material properties. A specimen-specific three-dimensional finite element representation was developed. Heel pad material properties were determined using inverse finite element analysis by fitting the model behavior to the experimental data. Compression dominant loading, applied using a spherical indenter, was used for optimization of the material properties. The optimized material properties were evaluated through simulations representative of a combined loading scenario (compression and anterior-posterior shear) with a spherical indenter and also of a compression dominant loading applied using an elevated platform. Optimized heel pad material coefficients were 0.001084 MPa (μ), 9.780 (α) (with an effective Poisson's ratio (ν) of 0.475), for a first-order nearly incompressible Ogden material model. The model predicted structural response of the heel pad was in good agreement for both the optimization (<1.05% maximum tool force, 0.9% maximum tool displacement) and validation cases (6.5% maximum tool force, 15% maximum tool displacement). The inverse analysis successfully predicted the material properties for the given specimen-specific heel pad using the experimental data for the specimen. The modeling framework and results can be used for accurate predictions of the three-dimensional interaction of the heel pad with its surroundings.

Parametric investigations of plasma characteristics in a remote inductively coupled plasma system

NASA Astrophysics Data System (ADS)

Shukla, Prasoon; Roy, Abhra; Jain, Kunal; Bhoj, Ananth

2016-09-01

Designing a remote plasma system involves source chamber sizing, selection of coils and/or electrodes to power the plasma, designing the downstream tubes, selection of materials used in the source and downstream regions, locations of inlets and outlets and finally optimizing the process parameter space of pressure, gas flow rates and power delivery. Simulations can aid in spatial and temporal plasma characterization in what are often inaccessible locations for experimental probes in the source chamber. In this paper, we report on simulations of a remote inductively coupled Argon plasma system using the modeling platform CFD-ACE +. The coupled multiphysics model description successfully address flow, chemistry, electromagnetics, heat transfer and plasma transport in the remote plasma system. The SimManager tool enables easy setup of parametric simulations to investigate the effect of varying the pressure, power, frequency, flow rates and downstream tube lengths. It can also enable the automatic solution of the varied parameters to optimize a user-defined objective function, which may be the integral ion and radical fluxes at the wafer. The fast run time coupled with the parametric and optimization capabilities can add significant insight and value in design and optimization.

2-D Ultrasound Sparse Arrays Multidepth Radiation Optimization Using Simulated Annealing and Spiral-Array Inspired Energy Functions.

PubMed

Roux, Emmanuel; Ramalli, Alessandro; Tortoli, Piero; Cachard, Christian; Robini, Marc C; Liebgott, Herve

2016-12-01

Full matrix arrays are excellent tools for 3-D ultrasound imaging, but the required number of active elements is too high to be individually controlled by an equal number of scanner channels. The number of active elements is significantly reduced by the sparse array techniques, but the position of the remaining elements must be carefully optimized. This issue is faced here by introducing novel energy functions in the simulated annealing (SA) algorithm. At each iteration step of the optimization process, one element is freely translated and the associated radiated pattern is simulated. To control the pressure field behavior at multiple depths, three energy functions inspired by the pressure field radiated by a Blackman-tapered spiral array are introduced. Such energy functions aim at limiting the main lobe width while lowering the side lobe and grating lobe levels at multiple depths. Numerical optimization results illustrate the influence of the number of iterations, pressure measurement points, and depths, as well as the influence of the energy function definition on the optimized layout. It is also shown that performance close to or even better than the one provided by a spiral array, here assumed as reference, may be obtained. The finite-time convergence properties of SA allow the duration of the optimization process to be set in advance.

Multijunction Solar Cell Technology for Mars Surface Applications

NASA Technical Reports Server (NTRS)

Stella, Paul M.; Mardesich, Nick; Ewell, Richard C.; Mueller, Robert L.; Endicter, Scott; Aiken, Daniel; Edmondson, Kenneth; Fetze, Chris

2006-01-01

Solar cells used for Mars surface applications have been commercial space qualified AM0 optimized devices. Due to the Martian atmosphere, these cells are not optimized for the Mars surface and as a result operate at a reduced efficiency. A multi-year program, MOST (Mars Optimized Solar Cell Technology), managed by JPL and funded by NASA Code S, was initiated in 2004, to develop tools to modify commercial AM0 cells for the Mars surface solar spectrum and to fabricate Mars optimized devices for verification. This effort required defining the surface incident spectrum, developing an appropriate laboratory solar simulator measurement capability, and to develop and test commercial cells modified for the Mars surface spectrum. This paper discusses the program, including results for the initial modified cells. Simulated Mars surface measurements of MER cells and Phoenix Lander cells (2007 launch) are provided to characterize the performance loss for those missions. In addition, the performance of the MER rover solar arrays is updated to reflect their more than two (2) year operation.

Strategy and gaps for modeling, simulation, and control of hybrid systems

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

Rabiti, Cristian; Garcia, Humberto E.; Hovsapian, Rob

2015-04-01

The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers,more » and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled, dynamic energy systems requires multiple simulation tools, potentially developed in several programming languages and resolved on separate time scales. Whereas further investigation and development of hybrid concepts will provide a more complete understanding of the joint computational and physical modeling needs, this report highlights areas in which co-simulation capabilities are warranted. The current development status, quality assurance, availability and maintainability of simulation tools that are currently available for hybrid systems modeling is presented. Existing gaps in the modeling and simulation toolsets and development needs are subsequently discussed. This effort will feed into a broader Roadmap activity for designing, developing, and demonstrating hybrid energy systems.« less

Workstation-Based Simulation for Rapid Prototyping and Piloted Evaluation of Control System Designs

NASA Technical Reports Server (NTRS)

Mansur, M. Hossein; Colbourne, Jason D.; Chang, Yu-Kuang; Aiken, Edwin W. (Technical Monitor)

1998-01-01

The development and optimization of flight control systems for modem fixed- and rotary-. wing aircraft consume a significant portion of the overall time and cost of aircraft development. Substantial savings can be achieved if the time required to develop and flight test the control system, and the cost, is reduced. To bring about such reductions, software tools such as Matlab/Simulink are being used to readily implement block diagrams and rapidly evaluate the expected responses of the completed system. Moreover, tools such as CONDUIT (CONtrol Designer's Unified InTerface) have been developed that enable the controls engineers to optimize their control laws and ensure that all the relevant quantitative criteria are satisfied, all within a fully interactive, user friendly, unified software environment.

Optimising probe holder design for sentinel lymph node imaging using clinical photoacoustic system with Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Sivasubramanian, Kathyayini; Periyasamy, Vijitha; Wen, Kew Kok; Pramanik, Manojit

2017-03-01

Photoacoustic tomography is a hybrid imaging modality that combines optical and ultrasound imaging. It is rapidly gaining attention in the field of medical imaging. The challenge is to translate it into a clinical setup. In this work, we report the development of a handheld clinical photoacoustic imaging system. A clinical ultrasound imaging system is modified to integrate photoacoustic imaging with the ultrasound imaging. Hence, light delivery has been integrated with the ultrasound probe. The angle of light delivery is optimized in this work with respect to the depth of imaging. Optimization was performed based on Monte Carlo simulation for light transport in tissues. Based on the simulation results, the probe holders were fabricated using 3D printing. Similar results were obtained experimentally using phantoms. Phantoms were developed to mimic sentinel lymph node imaging scenario. Also, in vivo sentinel lymph node imaging was done using the same system with contrast agent methylene blue up to a depth of 1.5 cm. The results validate that one can use Monte Carlo simulation as a tool to optimize the probe holder design depending on the imaging needs. This eliminates a trial and error approach generally used for designing a probe holder.

A combined geostatistical-optimization model for the optimal design of a groundwater quality monitoring network

NASA Astrophysics Data System (ADS)

Kolosionis, Konstantinos; Papadopoulou, Maria P.

2017-04-01

Monitoring networks provide essential information for water resources management especially in areas with significant groundwater exploitation due to extensive agricultural activities. In this work, a simulation-optimization framework is developed based on heuristic optimization methodologies and geostatistical modeling approaches to obtain an optimal design for a groundwater quality monitoring network. Groundwater quantity and quality data obtained from 43 existing observation locations at 3 different hydrological periods in Mires basin in Crete, Greece will be used in the proposed framework in terms of Regression Kriging to develop the spatial distribution of nitrates concentration in the aquifer of interest. Based on the existing groundwater quality mapping, the proposed optimization tool will determine a cost-effective observation wells network that contributes significant information to water managers and authorities. The elimination of observation wells that add little or no beneficial information to groundwater level and quality mapping of the area can be obtain using estimations uncertainty and statistical error metrics without effecting the assessment of the groundwater quality. Given the high maintenance cost of groundwater monitoring networks, the proposed tool could used by water regulators in the decision-making process to obtain a efficient network design that is essential.

Automatic Parameter Tuning for the Morpheus Vehicle Using Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Birge, B.

2013-01-01

A high fidelity simulation using a PC based Trick framework has been developed for Johnson Space Center's Morpheus test bed flight vehicle. There is an iterative development loop of refining and testing the hardware, refining the software, comparing the software simulation to hardware performance and adjusting either or both the hardware and the simulation to extract the best performance from the hardware as well as the most realistic representation of the hardware from the software. A Particle Swarm Optimization (PSO) based technique has been developed that increases speed and accuracy of the iterative development cycle. Parameters in software can be automatically tuned to make the simulation match real world subsystem data from test flights. Special considerations for scale, linearity, discontinuities, can be all but ignored with this technique, allowing fast turnaround both for simulation tune up to match hardware changes as well as during the test and validation phase to help identify hardware issues. Software models with insufficient control authority to match hardware test data can be immediately identified and using this technique requires very little to no specialized knowledge of optimization, freeing model developers to concentrate on spacecraft engineering. Integration of the PSO into the Morpheus development cycle will be discussed as well as a case study highlighting the tool's effectiveness.

Homotopy method for optimization of variable-specific-impulse low-thrust trajectories

NASA Astrophysics Data System (ADS)

Chi, Zhemin; Yang, Hongwei; Chen, Shiyu; Li, Junfeng

2017-11-01

The homotopy method has been used as a useful tool in solving fuel-optimal trajectories with constant-specific-impulse low thrust. However, the specific impulse is often variable for many practical solar electric power-limited thrusters. This paper investigates the application of the homotopy method for optimization of variable-specific-impulse low-thrust trajectories. Difficulties arise when the two commonly-used homotopy functions are employed for trajectory optimization. The optimal power throttle level and the optimal specific impulse are coupled with the commonly-used quadratic and logarithmic homotopy functions. To overcome these difficulties, a modified logarithmic homotopy function is proposed to serve as a gateway for trajectory optimization, leading to decoupled expressions of both the optimal power throttle level and the optimal specific impulse. The homotopy method based on this homotopy function is proposed. Numerical simulations validate the feasibility and high efficiency of the proposed method.

Virtual Factory Framework for Supporting Production Planning and Control.

PubMed

Kibira, Deogratias; Shao, Guodong

2017-01-01

Developing optimal production plans for smart manufacturing systems is challenging because shop floor events change dynamically. A virtual factory incorporating engineering tools, simulation, and optimization generates and communicates performance data to guide wise decision making for different control levels. This paper describes such a platform specifically for production planning. We also discuss verification and validation of the constituent models. A case study of a machine shop is used to demonstrate data generation for production planning in a virtual factory.

Simulation Tool for Optimizing Non-Combatant Evacuation (STONE): Optimization of Evacuation Time and Transportation Resource Utilization

DTIC Science & Technology

2015-05-01

2015 © Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2015 Abstract A Non-Combatant Evacuation...Standing Senate Committee on Foreign Affairs and International Trade recommended that more frequent assessments of NEO plans be conducted...étrangères et du commerce international a recommandé que des évaluations dans ses missions à l’étranger soient faites plus fréquemment

Hierarchical multistage MCMC follow-up of continuous gravitational wave candidates

NASA Astrophysics Data System (ADS)

Ashton, G.; Prix, R.

2018-05-01

Leveraging Markov chain Monte Carlo optimization of the F statistic, we introduce a method for the hierarchical follow-up of continuous gravitational wave candidates identified by wide-parameter space semicoherent searches. We demonstrate parameter estimation for continuous wave sources and develop a framework and tools to understand and control the effective size of the parameter space, critical to the success of the method. Monte Carlo tests of simulated signals in noise demonstrate that this method is close to the theoretical optimal performance.

Towards the Integration of APECS with VE-Suite to Create a Comprehensive Virtual Engineering Environment

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

McCorkle, D.; Yang, C.; Jordan, T.

2007-06-01

Modeling and simulation tools are becoming pervasive in the process engineering practice of designing advanced power generation facilities. These tools enable engineers to explore many what-if scenarios before cutting metal or constructing a pilot scale facility. While such tools enable investigation of crucial plant design aspects, typical commercial process simulation tools such as Aspen Plus®, gPROMS®, and HYSYS® still do not explore some plant design information, including computational fluid dynamics (CFD) models for complex thermal and fluid flow phenomena, economics models for policy decisions, operational data after the plant is constructed, and as-built information for use in as-designed models. Softwaremore » tools must be created that allow disparate sources of information to be integrated if environments are to be constructed where process simulation information can be accessed. At the Department of Energy’s (DOE) National Energy Technology Laboratory (NETL), the Advanced Process Engineering Co-Simulator (APECS) has been developed as an integrated software suite that combines process simulation (e.g., Aspen Plus) and high-fidelity equipment simulation (e.g., Fluent® CFD), together with advanced analysis capabilities including case studies, sensitivity analysis, stochastic simulation for risk/uncertainty analysis, and multi-objective optimization. In this paper, we discuss the initial phases of integrating APECS with the immersive and interactive virtual engineering software, VE-Suite, developed at Iowa State University and Ames Laboratory. VE-Suite utilizes the ActiveX (OLE Automation) controls in Aspen Plus wrapped by the CASI library developed by Reaction Engineering International to run the process simulation and query for unit operation results. This integration permits any application that uses the VE-Open interface to integrate with APECS co-simulations, enabling construction of the comprehensive virtual engineering environment needed for the rapid engineering of advanced power generation facilities.« less

Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model

NASA Astrophysics Data System (ADS)

Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr

2017-10-01

Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations, gradient based and nature inspired optimization algorithms and experimental data, the latter of which take the form of a load-extension curve obtained from the evaluation of uniaxial tensile test results. The aim of this research was to obtain material model parameters corresponding to the quasi-static tensile loading which may be further used for the research involving dynamic and high-speed tensile loading. Based on the obtained results it can be concluded that the set goal has been reached.

Finite element simulation and Experimental verification of Incremental Sheet metal Forming

NASA Astrophysics Data System (ADS)

Kaushik Yanamundra, Krishna; Karthikeyan, R., Dr.; Naranje, Vishal, Dr

2018-04-01

Incremental sheet metal forming is now a proven manufacturing technique that can be employed to obtain application specific, customized, symmetric or asymmetric shapes that are required by automobile or biomedical industries for specific purposes like car body parts, dental implants or knee implants. Finite element simulation of metal forming process is being performed successfully using explicit dynamics analysis of commercial FE software. The simulation is mainly useful in optimization of the process as well design of the final product. This paper focuses on simulating the incremental sheet metal forming process in ABAQUS, and validating the results using experimental methods. The shapes generated for testing are of trapezoid, dome and elliptical shapes whose G codes are written and fed into the CNC milling machine with an attached forming tool with a hemispherical bottom. The same pre-generated coordinates are used to simulate a similar machining conditions in ABAQUS and the tool forces, stresses and strains in the workpiece while machining are obtained as the output data. The forces experimentally were recorded using a dynamometer. The experimental and simulated results were then compared and thus conclusions were drawn.

Guided wave energy trapping to detect hidden multilayer delamination damage

NASA Astrophysics Data System (ADS)

Leckey, Cara A. C.; Seebo, Jeffrey P.

2015-03-01

Nondestructive Evaluation (NDE) and Structural Health Monitoring (SHM) simulation tools capable of modeling three-dimensional (3D) realistic energy-damage interactions are needed for aerospace composites. Current practice in NDE/SHM simulation for composites commonly involves over-simplification of the material parameters and/or a simplified two-dimensional (2D) approach. The unique damage types that occur in composite materials (delamination, microcracking, etc) develop as complex 3D geometry features. This paper discusses the application of 3D custom ultrasonic simulation tools to study wave interaction with multilayer delamination damage in carbon-fiber reinforced polymer (CFRP) composites. In particular, simulation based studies of ultrasonic guided wave energy trapping due to multilayer delamination damage were performed. The simulation results show changes in energy trapping at the composite surface as additional delaminations are added through the composite thickness. The results demonstrate a potential approach for identifying the presence of hidden multilayer delamination damage in applications where only single-sided access to a component is available. The paper also describes recent advancements in optimizing the custom ultrasonic simulation code for increases in computation speed.

Range Process Simulation Tool

NASA Technical Reports Server (NTRS)

Phillips, Dave; Haas, William; Barth, Tim; Benjamin, Perakath; Graul, Michael; Bagatourova, Olga

2005-01-01

Range Process Simulation Tool (RPST) is a computer program that assists managers in rapidly predicting and quantitatively assessing the operational effects of proposed technological additions to, and/or upgrades of, complex facilities and engineering systems such as the Eastern Test Range. Originally designed for application to space transportation systems, RPST is also suitable for assessing effects of proposed changes in industrial facilities and large organizations. RPST follows a model-based approach that includes finite-capacity schedule analysis and discrete-event process simulation. A component-based, scalable, open architecture makes RPST easily and rapidly tailorable for diverse applications. Specific RPST functions include: (1) definition of analysis objectives and performance metrics; (2) selection of process templates from a processtemplate library; (3) configuration of process models for detailed simulation and schedule analysis; (4) design of operations- analysis experiments; (5) schedule and simulation-based process analysis; and (6) optimization of performance by use of genetic algorithms and simulated annealing. The main benefits afforded by RPST are provision of information that can be used to reduce costs of operation and maintenance, and the capability for affordable, accurate, and reliable prediction and exploration of the consequences of many alternative proposed decisions.

Dynamic Approximate Entropy Electroanatomic Maps Detect Rotors in a Simulated Atrial Fibrillation Model

PubMed Central

Ugarte, Juan P.; Orozco-Duque, Andrés; Tobón, Catalina; Kremen, Vaclav; Novak, Daniel; Saiz, Javier; Oesterlein, Tobias; Schmitt, Clauss; Luik, Armin; Bustamante, John

2014-01-01

There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping. PMID:25489858

OptFlux: an open-source software platform for in silico metabolic engineering.

PubMed

Rocha, Isabel; Maia, Paulo; Evangelista, Pedro; Vilaça, Paulo; Soares, Simão; Pinto, José P; Nielsen, Jens; Patil, Kiran R; Ferreira, Eugénio C; Rocha, Miguel

2010-04-19

Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications. OptFlux is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes. OptFlux also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms. The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. OptFlux has a visualization module that allows the analysis of the model structure that is compatible with the layout information of Cell Designer, allowing the superimposition of simulation results with the model graph. The OptFlux software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community. Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models.

OptFlux: an open-source software platform for in silico metabolic engineering

PubMed Central

2010-01-01

Background Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications. Results OptFlux is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes. OptFlux also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms. The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. OptFlux has a visualization module that allows the analysis of the model structure that is compatible with the layout information of Cell Designer, allowing the superimposition of simulation results with the model graph. Conclusions The OptFlux software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community. Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models. PMID:20403172

Community Petascale Project for Accelerator Science and Simulation: Advancing Computational Science for Future Accelerators and Accelerator Technologies

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

Spentzouris, P.; /Fermilab; Cary, J.

The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors. ComPASS is in the first year of executing its plan to develop the next-generation HPC accelerator modeling tools. ComPASS aims to develop an integrated simulation environment that will utilize existing and new accelerator physics modules with petascale capabilities, by employing modern computing and solver technologies. The ComPASS vision is to deliver to accelerator scientists a virtual accelerator and virtual prototyping modeling environment, with the necessary multiphysics, multiscale capabilities. The plan for this development includes delivering accelerator modeling applications appropriate for each stage of the ComPASS software evolution. Such applications are already being used to address challenging problems in accelerator design and optimization. The ComPASS organization for software development and applications accounts for the natural domain areas (beam dynamics, electromagnetics, and advanced acceleration), and all areas depend on the enabling technologies activities, such as solvers and component technology, to deliver the desired performance and integrated simulation environment. The ComPASS applications focus on computationally challenging problems important for design or performance optimization to all major HEP, NP, and BES accelerator facilities. With the cost and complexity of particle accelerators rising, the use of computation to optimize their designs and find improved operating regimes becomes essential, potentially leading to significant cost savings with modest investment.« less

Automated planning of tangential breast intensity-modulated radiotherapy using heuristic optimization.

PubMed

Purdie, Thomas G; Dinniwell, Robert E; Letourneau, Daniel; Hill, Christine; Sharpe, Michael B

2011-10-01

To present an automated technique for two-field tangential breast intensity-modulated radiotherapy (IMRT) treatment planning. A total of 158 planned patients with Stage 0, I, and II breast cancer treated using whole-breast IMRT were retrospectively replanned using automated treatment planning tools. The tools developed are integrated into the existing clinical treatment planning system (Pinnacle(3)) and are designed to perform the manual volume delineation, beam placement, and IMRT treatment planning steps carried out by the treatment planning radiation therapist. The automated algorithm, using only the radio-opaque markers placed at CT simulation as inputs, optimizes the tangential beam parameters to geometrically minimize the amount of lung and heart treated while covering the whole-breast volume. The IMRT parameters are optimized according to the automatically delineated whole-breast volume. The mean time to generate a complete treatment plan was 6 min, 50 s ± 1 min 12 s. For the automated plans, 157 of 158 plans (99%) were deemed clinically acceptable, and 138 of 158 plans (87%) were deemed clinically improved or equal to the corresponding clinical plan when reviewed in a randomized, double-blinded study by one experienced breast radiation oncologist. In addition, overall the automated plans were dosimetrically equivalent to the clinical plans when scored for target coverage and lung and heart doses. We have developed robust and efficient automated tools for fully inversed planned tangential breast IMRT planning that can be readily integrated into clinical practice. The tools produce clinically acceptable plans using only the common anatomic landmarks from the CT simulation process as an input. We anticipate the tools will improve patient access to high-quality IMRT treatment by simplifying the planning process and will reduce the effort and cost of incorporating more advanced planning into clinical practice. Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.

CMOST: an open-source framework for the microsimulation of colorectal cancer screening strategies.

PubMed

Prakash, Meher K; Lang, Brian; Heinrich, Henriette; Valli, Piero V; Bauerfeind, Peter; Sonnenberg, Amnon; Beerenwinkel, Niko; Misselwitz, Benjamin

2017-06-05

Colorectal cancer (CRC) is a leading cause of cancer-related mortality. CRC incidence and mortality can be reduced by several screening strategies, including colonoscopy, but randomized CRC prevention trials face significant obstacles such as the need for large study populations with long follow-up. Therefore, CRC screening strategies will likely be designed and optimized based on computer simulations. Several computational microsimulation tools have been reported for estimating efficiency and cost-effectiveness of CRC prevention. However, none of these tools is publicly available. There is a need for an open source framework to answer practical questions including testing of new screening interventions and adapting findings to local conditions. We developed and implemented a new microsimulation model, Colon Modeling Open Source Tool (CMOST), for modeling the natural history of CRC, simulating the effects of CRC screening interventions, and calculating the resulting costs. CMOST facilitates automated parameter calibration against epidemiological adenoma prevalence and CRC incidence data. Predictions of CMOST were highly similar compared to a large endoscopic CRC prevention study as well as predictions of existing microsimulation models. We applied CMOST to calculate the optimal timing of a screening colonoscopy. CRC incidence and mortality are reduced most efficiently by a colonoscopy between the ages of 56 and 59; while discounted life years gained (LYG) is maximal at 49-50 years. With a dwell time of 13 years, the most cost-effective screening is at 59 years, at $17,211 discounted USD per LYG. While cost-efficiency varied according to dwell time it did not influence the optimal time point of screening interventions within the tested range. Predictions of CMOST are highly similar compared to a randomized CRC prevention trial as well as those of other microsimulation tools. This open source tool will enable health-economics analyses in for various countries, health-care scenarios and CRC prevention strategies. CMOST is freely available under the GNU General Public License at https://gitlab.com/misselwb/CMOST.

A tool to convert CAD models for importation into Geant4

NASA Astrophysics Data System (ADS)

Vuosalo, C.; Carlsmith, D.; Dasu, S.; Palladino, K.; LUX-ZEPLIN Collaboration

2017-10-01

The engineering design of a particle detector is usually performed in a Computer Aided Design (CAD) program, and simulation of the detector’s performance can be done with a Geant4-based program. However, transferring the detector design from the CAD program to Geant4 can be laborious and error-prone. SW2GDML is a tool that reads a design in the popular SOLIDWORKS CAD program and outputs Geometry Description Markup Language (GDML), used by Geant4 for importing and exporting detector geometries. Other methods for outputting CAD designs are available, such as the STEP format, and tools exist to convert these formats into GDML. However, these conversion methods produce very large and unwieldy designs composed of tessellated solids that can reduce Geant4 performance. In contrast, SW2GDML produces compact, human-readable GDML that employs standard geometric shapes rather than tessellated solids. This paper will describe the development and current capabilities of SW2GDML and plans for its enhancement. The aim of this tool is to automate importation of detector engineering models into Geant4-based simulation programs to support rapid, iterative cycles of detector design, simulation, and optimization.

ASTEC and MODEL: Controls software development at Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Downing, John P.; Bauer, Frank H.; Surber, Jeffrey L.

1993-01-01

The ASTEC (Analysis and Simulation Tools for Engineering Controls) software is under development at the Goddard Space Flight Center (GSFC). The design goal is to provide a wide selection of controls analysis tools at the personal computer level, as well as the capability to upload compute-intensive jobs to a mainframe or supercomputer. In the last three years the ASTEC (Analysis and Simulation Tools for Engineering Controls) software has been under development. ASTEC is meant to be an integrated collection of controls analysis tools for use at the desktop level. MODEL (Multi-Optimal Differential Equation Language) is a translator that converts programs written in the MODEL language to FORTRAN. An upgraded version of the MODEL program will be merged into ASTEC. MODEL has not been modified since 1981 and has not kept with changes in computers or user interface techniques. This paper describes the changes made to MODEL in order to make it useful in the 90's and how it relates to ASTEC.

The use of Tecnomatix software to simulate the manufacturing flows in an industrial enterprise producing hydrostatic components

NASA Astrophysics Data System (ADS)

Petrila, S.; Brabie, G.; Chirita, B.

2016-08-01

The analysis performed on manufacturing flows within industrial enterprises producing hydrostatic components twos made on a number of factors that influence smooth running of production such: distance between pieces, waiting time from one surgery to another; time achievement of setups on CNC machines; tool changing in case of a large number of operators and manufacturing complexity of large files [2]. To optimize the manufacturing flow it was used the software Tecnomatix. This software represents a complete portfolio of manufacturing solutions digital manufactured by Siemens. It provides innovation by linking all production methods of a product from process design, process simulation, validation and ending the manufacturing process. Among its many capabilities to create a wide range of simulations, the program offers various demonstrations regarding the behavior manufacturing cycles. This program allows the simulation and optimization of production systems and processes in several areas such as: car suppliers, production of industrial equipment; electronics manufacturing, design and production of aerospace and defense parts.

Localized Overheating Phenomena and Optimization of Spark-Plasma Sintering Tooling Design

PubMed Central

Giuntini, Diletta; Olevsky, Eugene A.; Garcia-Cardona, Cristina; Maximenko, Andrey L.; Yurlova, Maria S.; Haines, Christopher D.; Martin, Darold G.; Kapoor, Deepak

2013-01-01

The present paper shows the application of a three-dimensional coupled electrical, thermal, mechanical finite element macro-scale modeling framework of Spark Plasma Sintering (SPS) to an actual problem of SPS tooling overheating, encountered during SPS experimentation. The overheating phenomenon is analyzed by varying the geometry of the tooling that exhibits the problem, namely by modeling various tooling configurations involving sequences of disk-shape spacers with step-wise increasing radii. The analysis is conducted by means of finite element simulations, intended to obtain temperature spatial distributions in the graphite press-forms, including punches, dies, and spacers; to identify the temperature peaks and their respective timing, and to propose a more suitable SPS tooling configuration with the avoidance of the overheating as a final aim. Electric currents-based Joule heating, heat transfer, mechanical conditions, and densification are imbedded in the model, utilizing the finite-element software COMSOL™, which possesses a distinguishing ability of coupling multiple physics. Thereby the implementation of a finite element method applicable to a broad range of SPS procedures is carried out, together with the more specific optimization of the SPS tooling design when dealing with excessive heating phenomena. PMID:28811398

Optimizing a reconfigurable material via evolutionary computation

NASA Astrophysics Data System (ADS)

Wilken, Sam; Miskin, Marc Z.; Jaeger, Heinrich M.

2015-08-01

Rapid prototyping by combining evolutionary computation with simulations is becoming a powerful tool for solving complex design problems in materials science. This method of optimization operates in a virtual design space that simulates potential material behaviors and after completion needs to be validated by experiment. However, in principle an evolutionary optimizer can also operate on an actual physical structure or laboratory experiment directly, provided the relevant material parameters can be accessed by the optimizer and information about the material's performance can be updated by direct measurements. Here we provide a proof of concept of such direct, physical optimization by showing how a reconfigurable, highly nonlinear material can be tuned to respond to impact. We report on an entirely computer controlled laboratory experiment in which a 6 ×6 grid of electromagnets creates a magnetic field pattern that tunes the local rigidity of a concentrated suspension of ferrofluid and iron filings. A genetic algorithm is implemented and tasked to find field patterns that minimize the force transmitted through the suspension. Searching within a space of roughly 1010 possible configurations, after testing only 1500 independent trials the algorithm identifies an optimized configuration of layered rigid and compliant regions.

Optimization of the resources management in fighting wildfires.

PubMed

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

Optimization of the Resources Management in Fighting Wildfires

NASA Astrophysics Data System (ADS)

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J. Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

Using block pulse functions for seismic vibration semi-active control of structures with MR dampers

NASA Astrophysics Data System (ADS)

Rahimi Gendeshmin, Saeed; Davarnia, Daniel

2018-03-01

This article applied the idea of block pulse functions in the semi-active control of structures. The BP functions give effective tools to approximate complex problems. The applied control algorithm has a major effect on the performance of the controlled system and the requirements of the control devices. In control problems, it is important to devise an accurate analytical technique with less computational cost. It is proved that the BP functions are fundamental tools in approximation problems which have been applied in disparate areas in last decades. This study focuses on the employment of BP functions in control algorithm concerning reduction the computational cost. Magneto-rheological (MR) dampers are one of the well-known semi-active tools that can be used to control the response of civil Structures during earthquake. For validation purposes, numerical simulations of a 5-story shear building frame with MR dampers are presented. The results of suggested method were compared with results obtained by controlling the frame by the optimal control method based on linear quadratic regulator theory. It can be seen from simulation results that the suggested method can be helpful in reducing seismic structural responses. Besides, this method has acceptable accuracy and is in agreement with optimal control method with less computational costs.

Two-Dimensional Self-Consistent Radio Frequency Plasma Simulations Relevant to the Gaseous Electronics Conference RF Reference Cell

PubMed Central

Lymberopoulos, Dimitris P.; Economou, Demetre J.

1995-01-01

Over the past few years multidimensional self-consistent plasma simulations including complex chemistry have been developed which are promising tools for furthering our understanding of reactive gas plasmas and for reactor design and optimization. These simulations must be benchmarked against experimental data obtained in well-characterized systems such as the Gaseous Electronics Conference (GEC) reference cell. Two-dimensional simulations relevant to the GEC Cell are reviewed in this paper with emphasis on fluid simulations. Important features observed experimentally, such as off-axis maxima in the charge density and hot spots of metastable species density near the electrode edges in capacitively-coupled GEC cells, have been captured by these simulations. PMID:29151756

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

Zitney, S.E.

This presentation will examine process systems engineering R&D needs for application to advanced fossil energy (FE) systems and highlight ongoing research activities at the National Energy Technology Laboratory (NETL) under the auspices of a recently launched Collaboratory for Process & Dynamic Systems Research. The three current technology focus areas include: 1) High-fidelity systems with NETL's award-winning Advanced Process Engineering Co-Simulator (APECS) technology for integrating process simulation with computational fluid dynamics (CFD) and virtual engineering concepts, 2) Dynamic systems with R&D on plant-wide IGCC dynamic simulation, control, and real-time training applications, and 3) Systems optimization including large-scale process optimization, stochastic simulationmore » for risk/uncertainty analysis, and cost estimation. Continued R&D aimed at these and other key process systems engineering models, methods, and tools will accelerate the development of advanced gasification-based FE systems and produce increasingly valuable outcomes for DOE and the Nation.« less

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

Nord, B.; Amara, A.; Refregier, A.

The nature of dark matter, dark energy and large-scale gravity pose some of the most pressing questions in cosmology today. These fundamental questions require highly precise measurements, and a number of wide-field spectroscopic survey instruments are being designed to meet this requirement. A key component in these experiments is the development of a simulation tool to forecast science performance, define requirement flow-downs, optimize implementation, demonstrate feasibility, and prepare for exploitation. We present SPOKES (SPectrOscopic KEn Simulation), an end-to-end simulation facility for spectroscopic cosmological surveys designed to address this challenge. SPOKES is based on an integrated infrastructure, modular function organization, coherentmore » data handling and fast data access. These key features allow reproducibility of pipeline runs, enable ease of use and provide flexibility to update functions within the pipeline. The cyclic nature of the pipeline offers the possibility to make the science output an efficient measure for design optimization and feasibility testing. We present the architecture, first science, and computational performance results of the simulation pipeline. The framework is general, but for the benchmark tests, we use the Dark Energy Spectrometer (DESpec), one of the early concepts for the upcoming project, the Dark Energy Spectroscopic Instrument (DESI). As a result, we discuss how the SPOKES framework enables a rigorous process to optimize and exploit spectroscopic survey experiments in order to derive high-precision cosmological measurements optimally.« less

Desktop microsimulation: a tool to improve efficiency in the medical office practice.

PubMed

Montgomery, James B; Linville, Beth A; Slonim, Anthony D

2013-01-01

Because the economic crisis in the United States continues to have an impact on healthcare organizations, industry leaders must optimize their decision making. Discrete-event computer simulation is a quality tool with a demonstrated track record of improving the precision of analysis for process redesign. However, the use of simulation to consolidate practices and design efficiencies into an unfinished medical office building was a unique task. A discrete-event computer simulation package was used to model the operations and forecast future results for four orthopedic surgery practices. The scenarios were created to allow an evaluation of the impact of process change on the output variables of exam room utilization, patient queue size, and staff utilization. The model helped with decisions regarding space allocation and efficient exam room use by demonstrating the impact of process changes in patient queues at check-in/out, x-ray, and cast room locations when compared to the status quo model. The analysis impacted decisions on facility layout, patient flow, and staff functions in this newly consolidated practice. Simulation was found to be a useful tool for process redesign and decision making even prior to building occupancy. © 2011 National Association for Healthcare Quality.

Empty tracks optimization based on Z-Map model

NASA Astrophysics Data System (ADS)

Liu, Le; Yan, Guangrong; Wang, Zaijun; Zang, Genao

2017-12-01

For parts with many features, there are more empty tracks during machining. If these tracks are not optimized, the machining efficiency will be seriously affected. In this paper, the characteristics of the empty tracks are studied in detail. Combining with the existing optimization algorithm, a new tracks optimization method based on Z-Map model is proposed. In this method, the tool tracks are divided into the unit processing section, and then the Z-Map model simulation technique is used to analyze the order constraint between the unit segments. The empty stroke optimization problem is transformed into the TSP with sequential constraints, and then through the genetic algorithm solves the established TSP problem. This kind of optimization method can not only optimize the simple structural parts, but also optimize the complex structural parts, so as to effectively plan the empty tracks and greatly improve the processing efficiency.

MASTOS: Mammography Simulation Tool for design Optimization Studies.

PubMed

Spyrou, G; Panayiotakis, G; Tzanakos, G

2000-01-01

Mammography is a high quality imaging technique for the detection of breast lesions, which requires dedicated equipment and optimum operation. The design parameters of a mammography unit have to be decided and evaluated before the construction of such a high cost of apparatus. The optimum operational parameters also must be defined well before the real breast examination. MASTOS is a software package, based on Monte Carlo methods, that is designed to be used as a simulation tool in mammography. The input consists of the parameters that have to be specified when using a mammography unit, and also the parameters specifying the shape and composition of the breast phantom. In addition, the input may specify parameters needed in the design of a new mammographic apparatus. The main output of the simulation is a mammographic image and calculations of various factors that describe the image quality. The Monte Carlo simulation code is PC-based and is driven by an outer shell of a graphical user interface. The entire software package is a simulation tool for mammography and can be applied in basic research and/or in training in the fields of medical physics and biomedical engineering as well as in the performance evaluation of new designs of mammography units and in the determination of optimum standards for the operational parameters of a mammography unit.

An Alternative Frictional Boundary Condition for Computational Fluid Dynamics Simulation of Friction Stir Welding

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

Chen, Gaoqiang; Feng, Zhili; Zhu, Yucan

For better application of numerical simulation in optimization and design of friction stir welding (FSW), this paper presents a new frictional boundary condition at the tool/workpiece interface for computational fluid dynamics (CFD) modeling of FSW. The proposed boundary condition is based on an implementation of the Coulomb friction model. Using the new boundary condition, the CFD simulation yields non-uniform distribution of contact state over the tool/workpiece interface, as validated by the experimental weld macrostructure. It is found that interfacial sticking state is present over large area at the tool-workpiece interface, while significant interfacial sliding occurs at the shoulder periphery, themore » lower part of pin side, and the periphery of pin bottom. Due to the interfacial sticking, a rotating flow zone is found under the shoulder, in which fast circular motion occurs. The diameter of the rotating flow zone is smaller than the shoulder diameter, which is attributed to the presence of the interfacial sliding at the shoulder periphery. For the simulated welding condition, the heat generation due to friction and plastic deformation makes up 54.4 and 45.6% of the total heat generation rate, respectively. In conclusion, the simulated temperature field is validated by the good agreement to the experimental measurements.« less

An Alternative Frictional Boundary Condition for Computational Fluid Dynamics Simulation of Friction Stir Welding

DOE PAGES

Chen, Gaoqiang; Feng, Zhili; Zhu, Yucan; ...

2016-07-11

For better application of numerical simulation in optimization and design of friction stir welding (FSW), this paper presents a new frictional boundary condition at the tool/workpiece interface for computational fluid dynamics (CFD) modeling of FSW. The proposed boundary condition is based on an implementation of the Coulomb friction model. Using the new boundary condition, the CFD simulation yields non-uniform distribution of contact state over the tool/workpiece interface, as validated by the experimental weld macrostructure. It is found that interfacial sticking state is present over large area at the tool-workpiece interface, while significant interfacial sliding occurs at the shoulder periphery, themore » lower part of pin side, and the periphery of pin bottom. Due to the interfacial sticking, a rotating flow zone is found under the shoulder, in which fast circular motion occurs. The diameter of the rotating flow zone is smaller than the shoulder diameter, which is attributed to the presence of the interfacial sliding at the shoulder periphery. For the simulated welding condition, the heat generation due to friction and plastic deformation makes up 54.4 and 45.6% of the total heat generation rate, respectively. In conclusion, the simulated temperature field is validated by the good agreement to the experimental measurements.« less

BMP analysis system for watershed-based stormwater management.

PubMed

Zhen, Jenny; Shoemaker, Leslie; Riverson, John; Alvi, Khalid; Cheng, Mow-Soung

2006-01-01

Best Management Practices (BMPs) are measures for mitigating nonpoint source (NPS) pollution caused mainly by stormwater runoff. Established urban and newly developing areas must develop cost effective means for restoring or minimizing impacts, and planning future growth. Prince George's County in Maryland, USA, a fast-growing region in the Washington, DC metropolitan area, has developed a number of tools to support analysis and decision making for stormwater management planning and design at the watershed level. These tools support watershed analysis, innovative BMPs, and optimization. Application of these tools can help achieve environmental goals and lead to significant cost savings. This project includes software development that utilizes GIS information and technology, integrates BMP processes simulation models, and applies system optimization techniques for BMP planning and selection. The system employs the ESRI ArcGIS as the platform, and provides GIS-based visualization and support for developing networks including sequences of land uses, BMPs, and stream reaches. The system also provides interfaces for BMP placement, BMP attribute data input, and decision optimization management. The system includes a stand-alone BMP simulation and evaluation module, which complements both research and regulatory nonpoint source control assessment efforts, and allows flexibility in the examining various BMP design alternatives. Process based simulation of BMPs provides a technique that is sensitive to local climate and rainfall patterns. The system incorporates a meta-heuristic optimization technique to find the most cost-effective BMP placement and implementation plan given a control target, or a fixed cost. A case study is presented to demonstrate the application of the Prince George's County system. The case study involves a highly urbanized area in the Anacostia River (a tributary to Potomac River) watershed southeast of Washington, DC. An innovative system of management practices is proposed to minimize runoff, improve water quality, and provide water reuse opportunities. Proposed management techniques include bioretention, green roof, and rooftop runoff collection (rain barrel) systems. The modeling system was used to identify the most cost-effective combinations of management practices to help minimize frequency and size of runoff events and resulting combined sewer overflows to the Anacostia River.

An End-to-End simulator for the development of atmospheric corrections and temperature - emissivity separation algorithms in the TIR spectral domain

NASA Astrophysics Data System (ADS)

Rock, Gilles; Fischer, Kim; Schlerf, Martin; Gerhards, Max; Udelhoven, Thomas

2017-04-01

The development and optimization of image processing algorithms requires the availability of datasets depicting every step from earth surface to the sensor's detector. The lack of ground truth data obliges to develop algorithms on simulated data. The simulation of hyperspectral remote sensing data is a useful tool for a variety of tasks such as the design of systems, the understanding of the image formation process, and the development and validation of data processing algorithms. An end-to-end simulator has been set up consisting of a forward simulator, a backward simulator and a validation module. The forward simulator derives radiance datasets based on laboratory sample spectra, applies atmospheric contributions using radiative transfer equations, and simulates the instrument response using configurable sensor models. This is followed by the backward simulation branch, consisting of an atmospheric correction (AC), a temperature and emissivity separation (TES) or a hybrid AC and TES algorithm. An independent validation module allows the comparison between input and output dataset and the benchmarking of different processing algorithms. In this study, hyperspectral thermal infrared scenes of a variety of surfaces have been simulated to analyze existing AC and TES algorithms. The ARTEMISS algorithm was optimized and benchmarked against the original implementations. The errors in TES were found to be related to incorrect water vapor retrieval. The atmospheric characterization could be optimized resulting in increasing accuracies in temperature and emissivity retrieval. Airborne datasets of different spectral resolutions were simulated from terrestrial HyperCam-LW measurements. The simulated airborne radiance spectra were subjected to atmospheric correction and TES and further used for a plant species classification study analyzing effects related to noise and mixed pixels.

Proximity matching for ArF and KrF scanners

NASA Astrophysics Data System (ADS)

Kim, Young Ki; Pohling, Lua; Hwee, Ng Teng; Kim, Jeong Soo; Benyon, Peter; Depre, Jerome; Hong, Jongkyun; Serebriakov, Alexander

2009-03-01

There are many IC-manufacturers over the world that use various exposure systems and work with very high requirements in order to establish and maintain stable lithographic processes of 65 nm, 45 nm and below. Once the process is established, manufacturer desires to be able to run it on different tools that are available. This is why the proximity matching plays a key role to maximize tools utilization in terms of productivity for different types of exposure tools. In this paper, we investigate the source of errors that cause optical proximity mismatch and evaluate several approaches for proximity matching of different types of 193 nm and 248 nm scanner systems such as set-get sigma calibration, contrast adjustment, and, finally, tuning imaging parameters by optimization with Manual Scanner Matcher. First, to monitor the proximity mismatch, we collect CD measurement data for the reference tool and for the tool-to-be-matched. Normally, the measurement is performed for a set of line or space through pitch structures. Secondly, by simulation or experiment, we determine the sensitivity of the critical structures with respect to small adjustment of exposure settings such as NA, sigma inner, sigma outer, dose, focus scan range etc. that are called 'proximity tuning knobs'. Then, with the help of special optimization software, we compute the proximity knob adjustment that has to be applied to the tool-to-be-matched to match the reference tool. Finally, we verify successful matching by exposing on the tool-to-be-matched with tuned exposure settings. This procedure is applicable for inter- and intra scanner type matching, but possibly also for process transfers to the design targets. In order to illustrate the approach we show experimental data as well as results of imaging simulations. The set demonstrate successful matching of critical structures for ArF scanners of different tool generations.

Stability analysis using SDSA tool

NASA Astrophysics Data System (ADS)

Goetzendorf-Grabowski, Tomasz; Mieszalski, Dawid; Marcinkiewicz, Ewa

2011-11-01

The SDSA (Simulation and Dynamic Stability Analysis) application is presented as a tool for analysing the dynamic characteristics of the aircraft just in the conceptual design stage. SDSA is part of the CEASIOM (Computerized Environment for Aircraft Synthesis and Integrated Optimization Methods) software environment which was developed within the SimSAC (Simulating Aircraft Stability And Control Characteristics for Use in Conceptual Design) project, funded by the European Commission 6th Framework Program. SDSA can also be used as stand alone software, and integrated with other design and optimisation systems using software wrappers. This paper focuses on the main functionalities of SDSA and presents both computational and free flight experimental results to compare and validate the presented software. Two aircraft are considered, the EADS Ranger 2000 and the Warsaw University designed PW-6 glider. For the two cases considered here the SDSA software is shown to be an excellent tool for predicting dynamic characteristics of an aircraft.

Electric power market agent design

NASA Astrophysics Data System (ADS)

Oh, Hyungseon

The electric power industry in many countries has been restructured in the hope of a more economically efficient system. In the restructured system, traditional operating and planning tools based on true marginal cost do not perform well since information required is strictly confidential. For developing a new tool, it is necessary to understand offer behavior. The main objective of this study is to create a new tool for power system planning. For the purpose, this dissertation develops models for a market and market participants. A new model is developed in this work for explaining a supply-side offer curve, and several variables are introduced to characterize the curve. Demand is estimated using a neural network, and a numerical optimization process is used to determine the values of the variables that maximize the profit of the agent. The amount of data required for the optimization is chosen with the aid of nonlinear dynamics. To suggest an optimal demand-side bidding function, two optimization problems are constructed and solved for maximizing consumer satisfaction based on the properties of two different types of demands: price-based demand and must-be-served demand. Several different simulations are performed to test how an agent reacts in various situations. The offer behavior depends on locational benefit as well as the offer strategies of competitors.

Techniques for designing rotorcraft control systems

NASA Technical Reports Server (NTRS)

Levine, William S.; Barlow, Jewel

1993-01-01

This report summarizes the work that was done on the project from 1 Apr. 1992 to 31 Mar. 1993. The main goal of this research is to develop a practical tool for rotorcraft control system design based on interactive optimization tools (CONSOL-OPTCAD) and classical rotorcraft design considerations (ADOCS). This approach enables the designer to combine engineering intuition and experience with parametric optimization. The combination should make it possible to produce a better design faster than would be possible using either pure optimization or pure intuition and experience. We emphasize that the goal of this project is not to develop an algorithm. It is to develop a tool. We want to keep the human designer in the design process to take advantage of his or her experience and creativity. The role of the computer is to perform the calculation necessary to improve and to display the performance of the nominal design. Briefly, during the first year we have connected CONSOL-OPTCAD, an existing software package for optimizing parameters with respect to multiple performance criteria, to a simplified nonlinear simulation of the UH-60 rotorcraft. We have also created mathematical approximations to the Mil-specs for rotorcraft handling qualities and input them into CONSOL-OPTCAD. Finally, we have developed the additional software necessary to use CONSOL-OPTCAD for the design of rotorcraft controllers.

Optimization and parallelization of the thermal–hydraulic subchannel code CTF for high-fidelity multi-physics applications

DOE PAGES

Salko, Robert K.; Schmidt, Rodney C.; Avramova, Maria N.

2014-11-23

This study describes major improvements to the computational infrastructure of the CTF subchannel code so that full-core, pincell-resolved (i.e., one computational subchannel per real bundle flow channel) simulations can now be performed in much shorter run-times, either in stand-alone mode or as part of coupled-code multi-physics calculations. These improvements support the goals of the Department Of Energy Consortium for Advanced Simulation of Light Water Reactors (CASL) Energy Innovation Hub to develop high fidelity multi-physics simulation tools for nuclear energy design and analysis.

Optimum spaceborne computer system design by simulation

NASA Technical Reports Server (NTRS)

Williams, T.; Kerner, H.; Weatherbee, J. E.; Taylor, D. S.; Hodges, B.

1973-01-01

A deterministic simulator is described which models the Automatically Reconfigurable Modular Multiprocessor System (ARMMS), a candidate computer system for future manned and unmanned space missions. Its use as a tool to study and determine the minimum computer system configuration necessary to satisfy the on-board computational requirements of a typical mission is presented. The paper describes how the computer system configuration is determined in order to satisfy the data processing demand of the various shuttle booster subsytems. The configuration which is developed as a result of studies with the simulator is optimal with respect to the efficient use of computer system resources.

Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits.

PubMed

Carvalho, Henrique F; Barbosa, Arménio J M; Roque, Ana C A; Iranzo, Olga; Branco, Ricardo J F

2017-01-01

Recent advances in de novo protein design have gained considerable insight from the intrinsic dynamics of proteins, based on the integration of molecular dynamics simulations protocols on the state-of-the-art de novo protein design protocols used nowadays. With this protocol we illustrate how to set up and run a molecular dynamics simulation followed by a functional protein dynamics analysis. New users will be introduced to some useful open-source computational tools, including the GROMACS molecular dynamics simulation software package and ProDy for protein structural dynamics analysis.

The application of simulation modeling to the cost and performance ranking of solar thermal power plants

NASA Technical Reports Server (NTRS)

Rosenberg, L. S.; Revere, W. R.; Selcuk, M. K.

1981-01-01

Small solar thermal power systems (up to 10 MWe in size) were tested. The solar thermal power plant ranking study was performed to aid in experiment activity and support decisions for the selection of the most appropriate technological approach. The cost and performance were determined for insolation conditions by utilizing the Solar Energy Simulation computer code (SESII). This model optimizes the size of the collector field and energy storage subsystem for given engine generator and energy transport characteristics. The development of the simulation tool, its operation, and the results achieved from the analysis are discussed.

Simulation of groundwater flow and analysis of the effects of water-management options in the North Platte Natural Resources District, Nebraska

USGS Publications Warehouse

Peterson, Steven M.; Flynn, Amanda T.; Vrabel, Joseph; Ryter, Derek W.

2015-08-12

The calibrated groundwater-flow model was used with the Groundwater-Management Process for the 2005 version of the U.S. Geological Survey modular three-dimensional groundwater model, MODFLOW–2005, to provide a tool for the NPNRD to better understand how water-management decisions could affect stream base flows of the North Platte River at Bridgeport, Nebr., streamgage in a future period from 2008 to 2019 under varying climatic conditions. The simulation-optimization model was constructed to analyze the maximum increase in simulated stream base flow that could be obtained with the minimum amount of reductions in groundwater withdrawals for irrigation. A second analysis extended the first to analyze the simulated base-flow benefit of groundwater withdrawals along with application of intentional recharge, that is, water from canals being released into rangeland areas with sandy soils. With optimized groundwater withdrawals and intentional recharge, the maximum simulated stream base flow was 15–23 cubic feet per second (ft3/s) greater than with no management at all, or 10–15 ft3/s larger than with managed groundwater withdrawals only. These results indicate not only the amount that simulated stream base flow can be increased by these management options, but also the locations where the management options provide the most or least benefit to the simulated stream base flow. For the analyses in this report, simulated base flow was best optimized by reductions in groundwater withdrawals north of the North Platte River and in the western half of the area. Intentional recharge sites selected by the optimization had a complex distribution but were more likely to be closer to the North Platte River or its tributaries. Future users of the simulation-optimization model will be able to modify the input files as to type, location, and timing of constraints, decision variables of groundwater withdrawals by zone, and other variables to explore other feasible management scenarios that may yield different increases in simulated future base flow of the North Platte River.

C-SWAT: The Soil and Water Assessment Tool with consolidated input files in alleviating computational burden of recursive simulations

USDA-ARS?s Scientific Manuscript database

The temptation to include model parameters and high resolution input data together with the availability of powerful optimization and uncertainty analysis algorithms has significantly enhanced the complexity of hydrologic and water quality modeling. However, the ability to take advantage of sophist...

Uncertainty analysis in ecological studies: an overview

Treesearch

Harbin Li; Jianguo Wu

2006-01-01

Large-scale simulation models are essential tools for scientific research and environmental decision-making because they can be used to synthesize knowledge, predict consequences of potential scenarios, and develop optimal solutions (Clark et al. 2001, Berk et al. 2002, Katz 2002). Modeling is often the only means of addressing complex environmental problems that occur...

Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues.

PubMed

Kim, Munju; Gillies, Robert J; Rejniak, Katarzyna A

2013-11-18

Delivery of anti-cancer drugs to tumor tissues, including their interstitial transport and cellular uptake, is a complex process involving various biochemical, mechanical, and biophysical factors. Mathematical modeling provides a means through which to understand this complexity better, as well as to examine interactions between contributing components in a systematic way via computational simulations and quantitative analyses. In this review, we present the current state of mathematical modeling approaches that address phenomena related to drug delivery. We describe how various types of models were used to predict spatio-temporal distributions of drugs within the tumor tissue, to simulate different ways to overcome barriers to drug transport, or to optimize treatment schedules. Finally, we discuss how integration of mathematical modeling with experimental or clinical data can provide better tools to understand the drug delivery process, in particular to examine the specific tissue- or compound-related factors that limit drug penetration through tumors. Such tools will be important in designing new chemotherapy targets and optimal treatment strategies, as well as in developing non-invasive diagnosis to monitor treatment response and detect tumor recurrence.

Dynamic Systems Analysis for Turbine Based Aero Propulsion Systems

NASA Technical Reports Server (NTRS)

Csank, Jeffrey T.

2016-01-01

The aircraft engine design process seeks to optimize the overall system-level performance, weight, and cost for a given concept. Steady-state simulations and data are used to identify trade-offs that should be balanced to optimize the system in a process known as systems analysis. These systems analysis simulations and data may not adequately capture the true performance trade-offs that exist during transient operation. Dynamic systems analysis provides the capability for assessing the dynamic tradeoffs at an earlier stage of the engine design process. The dynamic systems analysis concept, developed tools, and potential benefit are presented in this paper. To provide this capability, the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) was developed to provide the user with an estimate of the closed-loop performance (response time) and operability (high pressure compressor surge margin) for a given engine design and set of control design requirements. TTECTrA along with engine deterioration information, can be used to develop a more generic relationship between performance and operability that can impact the engine design constraints and potentially lead to a more efficient engine.

Progress in Modeling and Simulation of Batteries

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

Turner, John A

2016-01-01

Modeling and simulation of batteries, in conjunction with theory and experiment, are important research tools that offer opportunities for advancement of technologies that are critical to electric motors. The development of data from the application of these tools can provide the basis for managerial and technical decision-making. Together, these will continue to transform batteries for electric vehicles. This collection of nine papers presents the modeling and simulation of batteries and the continuing contribution being made to this impressive progress, including topics that cover: * Thermal behavior and characteristics * Battery management system design and analysis * Moderately high-fidelity 3D capabilitiesmore » * Optimization Techniques and Durability As electric vehicles continue to gain interest from manufacturers and consumers alike, improvements in economy and affordability, as well as adoption of alternative fuel sources to meet government mandates are driving battery research and development. Progress in modeling and simulation will continue to contribute to battery improvements that deliver increased power, energy storage, and durability to further enhance the appeal of electric vehicles.« less

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Selecting and optimizing eco-physiological parameters of Biome-BGC to reproduce observed woody and leaf biomass growth of Eucommia ulmoides plantation in China using Dakota optimizer

NASA Astrophysics Data System (ADS)

Miyauchi, T.; Machimura, T.

2013-12-01

In the simulation using an ecosystem process model, the adjustment of parameters is indispensable for improving the accuracy of prediction. This procedure, however, requires much time and effort for approaching the simulation results to the measurements on models consisting of various ecosystem processes. In this study, we tried to apply a general purpose optimization tool in the parameter optimization of an ecosystem model, and examined its validity by comparing the simulated and measured biomass growth of a woody plantation. A biometric survey of tree biomass growth was performed in 2009 in an 11-year old Eucommia ulmoides plantation in Henan Province, China. Climate of the site was dry temperate. Leaf, above- and below-ground woody biomass were measured from three cut trees and converted into carbon mass per area by measured carbon contents and stem density. Yearly woody biomass growth of the plantation was calculated according to allometric relationships determined by tree ring analysis of seven cut trees. We used Biome-BGC (Thornton, 2002) to reproduce biomass growth of the plantation. Air temperature and humidity from 1981 to 2010 was used as input climate condition. The plant functional type was deciduous broadleaf, and non-optimizing parameters were left default. 11-year long normal simulations were performed following a spin-up run. In order to select optimizing parameters, we analyzed the sensitivity of leaf, above- and below-ground woody biomass to eco-physiological parameters. Following the selection, optimization of parameters was performed by using the Dakota optimizer. Dakota is an optimizer developed by Sandia National Laboratories for providing a systematic and rapid means to obtain optimal designs using simulation based models. As the object function, we calculated the sum of relative errors between simulated and measured leaf, above- and below-ground woody carbon at each of eleven years. In an alternative run, errors at the last year (at the field survey) were weighted for priority. We compared some gradient-based global optimization methods of Dakota starting with the default parameters of Biome-BGC. In the result of sensitive analysis, carbon allocation parameters between coarse root and leaf, between stem and leaf, and SLA had high contribution on both leaf and woody biomass changes. These parameters were selected to be optimized. The measured leaf, above- and below-ground woody biomass carbon density at the last year were 0.22, 1.81 and 0.86 kgC m-2, respectively, whereas those simulated in the non-optimized control case using all default parameters were 0.12, 2.26 and 0.52 kgC m-2, respectively. After optimizing the parameters, the simulated values were improved to 0.19, 1.81 and 0.86 kgC m-2, respectively. The coliny global optimization method gave the better fitness than efficient global and ncsu direct method. The optimized parameters showed the higher carbon allocation rates to coarse roots and leaves and the lower SLA than the default parameters, which were consistent to the general water physiological response in a dry climate. The simulation using the weighted object function resulted in the closer simulations to the measurements at the last year with the lower fitness during the previous years.

Publicly Releasing a Large Simulation Dataset with NDS Labs

NASA Astrophysics Data System (ADS)

Goldbaum, Nathan

2016-03-01

Optimally, all publicly funded research should be accompanied by the tools, code, and data necessary to fully reproduce the analysis performed in journal articles describing the research. This ideal can be difficult to attain, particularly when dealing with large (>10 TB) simulation datasets. In this lightning talk, we describe the process of publicly releasing a large simulation dataset to accompany the submission of a journal article. The simulation was performed using Enzo, an open source, community-developed N-body/hydrodynamics code and was analyzed using a wide range of community- developed tools in the scientific Python ecosystem. Although the simulation was performed and analyzed using an ecosystem of sustainably developed tools, we enable sustainable science using our data by making it publicly available. Combining the data release with the NDS Labs infrastructure allows a substantial amount of added value, including web-based access to analysis and visualization using the yt analysis package through an IPython notebook interface. In addition, we are able to accompany the paper submission to the arXiv preprint server with links to the raw simulation data as well as interactive real-time data visualizations that readers can explore on their own or share with colleagues during journal club discussions. It is our hope that the value added by these services will substantially increase the impact and readership of the paper.

Ion transfer from an atmospheric pressure ion funnel into a mass spectrometer with different interface options: Simulation-based optimization of ion transmission efficiency.

PubMed

Mayer, Thomas; Borsdorf, Helko

2016-02-15

We optimized an atmospheric pressure ion funnel (APIF) including different interface options (pinhole, capillary, and nozzle) regarding a maximal ion transmission. Previous computer simulations consider the ion funnel itself and do not include the geometry of the following components which can considerably influence the ion transmission into the vacuum stage. Initially, a three-dimensional computer-aided design (CAD) model of our setup was created using Autodesk Inventor. This model was imported to the Autodesk Simulation CFD program where the computational fluid dynamics (CFD) were calculated. The flow field was transferred to SIMION 8.1. Investigations of ion trajectories were carried out using the SDS (statistical diffusion simulation) tool of SIMION, which allowed us to evaluate the flow regime, pressure, and temperature values that we obtained. The simulation-based optimization of different interfaces between an atmospheric pressure ion funnel and the first vacuum stage of a mass spectrometer require the consideration of fluid dynamics. The use of a Venturi nozzle ensures the highest level of transmission efficiency in comparison to capillaries or pinholes. However, the application of radiofrequency (RF) voltage and an appropriate direct current (DC) field leads to process optimization and maximum ion transfer. The nozzle does not hinder the transfer of small ions. Our high-resolution SIMION model (0.01 mm grid unit(-1) ) under consideration of fluid dynamics is generally suitable for predicting the ion transmission through an atmospheric-vacuum system for mass spectrometry and enables the optimization of operational parameters. A Venturi nozzle inserted between the ion funnel and the mass spectrometer permits maximal ion transmission. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

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

Zitney, S.E.

Emerging fossil energy power generation systems must operate with unprecedented efficiency and near-zero emissions, while optimizing profitably amid cost fluctuations for raw materials, finished products, and energy. To help address these challenges, the fossil energy industry will have to rely increasingly on the use advanced computational tools for modeling and simulating complex process systems. In this paper, we present the computational research challenges and opportunities for the optimization of fossil energy power generation systems across the plant lifecycle from process synthesis and design to plant operations. We also look beyond the plant gates to discuss research challenges and opportunities formore » enterprise-wide optimization, including planning, scheduling, and supply chain technologies.« less

Parallel Harmony Search Based Distributed Energy Resource Optimization

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

Ceylan, Oguzhan; Liu, Guodong; Tomsovic, Kevin

2015-01-01

This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electricalmore » power distribution systems operation.« less

Optimal health insurance: the case of observable, severe illness.

PubMed

Chernew, M E; Encinosa, W E; Hirth, R A

2000-09-01

We explore optimal cost-sharing provisions for insurance contracts when individuals have observable, severe diseases with a discrete number of medically appropriate treatment options. Variation in preferences for alternative treatments is unobserved by the insurer and non-contractible. Interest in such situations is increasingly common, exemplified by disease carve-out programs and shared decision-making (SDM) tools. We demonstrate that optimal insurance charges a copay to patients choosing the high-cost treatment and provides consumers of the low-cost treatment a cash payment. A simulation of the effect of such a policy, based on prostate cancer, indicates a substantial reduction in moral hazard.

Trajectories for High Specific Impulse High Specific Power Deep Space Exploration

NASA Technical Reports Server (NTRS)

Polsgrove, Tara; Adams, Robert B.; Brady, Hugh J. (Technical Monitor)

2002-01-01

Flight times and deliverable masses for electric and fusion propulsion systems are difficult to approximate. Numerical integration is required for these continuous thrust systems. Many scientists are not equipped with the tools and expertise to conduct interplanetary and interstellar trajectory analysis for their concepts. Several charts plotting the results of well-known trajectory simulation codes were developed and are contained in this paper. These charts illustrate the dependence of time of flight and payload ratio on jet power, initial mass, specific impulse and specific power. These charts are intended to be a tool by which people in the propulsion community can explore the possibilities of their propulsion system concepts. Trajectories were simulated using the tools VARITOP and IPOST. VARITOP is a well known trajectory optimization code that involves numerical integration based on calculus of variations. IPOST has several methods of trajectory simulation; the one used in this paper is Cowell's method for full integration of the equations of motion. An analytical method derived in the companion paper was also evaluated. The accuracy of this method is discussed in the paper.

INTEGRATION OF COST MODELS AND PROCESS SIMULATION TOOLS FOR OPTIMUM COMPOSITE MANUFACTURING PROCESS

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

Pack, Seongchan; Wilson, Daniel; Aitharaju, Venkat

Manufacturing cost of resin transfer molded composite parts is significantly influenced by the cycle time, which is strongly related to the time for both filling and curing of the resin in the mold. The time for filling can be optimized by various injection strategies, and by suitably reducing the length of the resin flow distance during the injection. The curing time can be reduced by the usage of faster curing resins, but it requires a high pressure injection equipment, which is capital intensive. Predictive manufacturing simulation tools that are being developed recently for composite materials are able to provide variousmore » scenarios of processing conditions virtually well in advance of manufacturing the parts. In the present study, we integrate the cost models with process simulation tools to study the influence of various parameters such as injection strategies, injection pressure, compression control to minimize high pressure injection, resin curing rate, and demold time on the manufacturing cost as affected by the annual part volume. A representative automotive component was selected for the study and the results are presented in this paper« less

Using Collaborative Simulation Modeling to Develop a Web-Based Tool to Support Policy-Level Decision Making About Breast Cancer Screening Initiation Age

PubMed Central

Burnside, Elizabeth S.; Lee, Sandra J.; Bennette, Carrie; Near, Aimee M.; Alagoz, Oguzhan; Huang, Hui; van den Broek, Jeroen J.; Kim, Joo Yeon; Ergun, Mehmet A.; van Ravesteyn, Nicolien T.; Stout, Natasha K.; de Koning, Harry J.; Mandelblatt, Jeanne S.

2017-01-01

Background There are no publicly available tools designed specifically to assist policy makers to make informed decisions about the optimal ages of breast cancer screening initiation for different populations of US women. Objective To use three established simulation models to develop a web-based tool called Mammo OUTPuT. Methods The simulation models use the 1970 US birth cohort and common parameters for incidence, digital screening performance, and treatment effects. Outcomes include breast cancers diagnosed, breast cancer deaths averted, breast cancer mortality reduction, false-positive mammograms, benign biopsies, and overdiagnosis. The Mammo OUTPuT tool displays these outcomes for combinations of age at screening initiation (every year from 40 to 49), annual versus biennial interval, lifetime versus 10-year horizon, and breast density, compared to waiting to start biennial screening at age 50 and continuing to 74. The tool was piloted by decision makers (n = 16) who completed surveys. Results The tool demonstrates that benefits in the 40s increase linearly with earlier initiation age, without a specific threshold age. Likewise, the harms of screening increase monotonically with earlier ages of initiation in the 40s. The tool also shows users how the balance of benefits and harms varies with breast density. Surveys revealed that 100% of users (16/16) liked the appearance of the site; 94% (15/16) found the tool helpful; and 94% (15/16) would recommend the tool to a colleague. Conclusions This tool synthesizes a representative subset of the most current CISNET (Cancer Intervention and Surveillance Modeling Network) simulation model outcomes to provide policy makers with quantitative data on the benefits and harms of screening women in the 40s. Ultimate decisions will depend on program goals, the population served, and informed judgments about the weight of benefits and harms. PMID:29376135

Process-orientated simulation of tillage practices and land use change to optimize distributed flood control measures

NASA Astrophysics Data System (ADS)

Disse, M.; Rieger, W.

2009-04-01

Not only climate change affects hydrological systems but also land use change and agricultural tillage practises have an important impact on infiltration and runoff generation. In the last five to six decades monocropping, drainage and rectification of small rivers were carried out to optimize crop yields and economic benefits. However, in recent years more holistic and sustainable management concepts are required. The advantages of ecological management of land, soil and water resources are manifold: the biodiversity is higher, the buffer function of soils will be conserved and both low water and floods are positive affected. The target of the presented research project which is financed by the Bavarian environment agency, is to establish an optimal flood retention concept in a mesoscale catchment of 150 km² which emphasizes ecological flood measures like best tillage practices, small retention basins and renaturation of small rivers. To quantify the effects of these measures the water balance model WaSiM-ETH was used. The grid-based water flow and balance simulation model WaSiM-ETH is a well-established tool for investigating the spatial and temporal variability of hydrological processes in complex river basins. The model can be seen as a reasonable compromise between detailed physical basis and minimum data requirements (http://www.wasim.ch/en/index.html). WaSiM was coupled with a 2d-ground water model and an additional drainage tool. Different vegetation was parameterized with high spatial and temporal resolution. Additionally, future climate scenarios like the extension of vegetation periods were considered. The effectiveness of decentralized retention basins could be simulated by a new implemented see storage tool. The presentation will give quantitative results for different flood control measures. The pros and cons of physically based approaches in hydrological modelling will be discussed.

Using genetic algorithm to solve a new multi-period stochastic optimization model

NASA Astrophysics Data System (ADS)

Zhang, Xin-Li; Zhang, Ke-Cun

2009-09-01

This paper presents a new asset allocation model based on the CVaR risk measure and transaction costs. Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [N. Hibiki, A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation, in: H. Takahashi, (Ed.) The Japanese Association of Financial Econometrics and Engineering, JAFFE Journal (2001) 89-119 (in Japanese); N. Hibiki A hybrid simulation/tree stochastic optimization model for dynamic asset allocation, in: B. Scherer (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, 2003, pp. 269-294], which was called a hybrid model. However, the transaction costs weren't considered in that paper. In this paper, we improve Hibiki's model in the following aspects: (1) The risk measure CVaR is introduced to control the wealth loss risk while maximizing the expected utility; (2) Typical market imperfections such as short sale constraints, proportional transaction costs are considered simultaneously. (3) Applying a genetic algorithm to solve the resulting model is discussed in detail. Numerical results show the suitability and feasibility of our methodology.

Simulation of Trajectories for High Specific Impulse Deep Space Exploration

NASA Technical Reports Server (NTRS)

Polsgrove, Tara; Adams, Robert B.; Brady, Hugh J. (Technical Monitor)

2002-01-01

Difficulties in approximating flight times and deliverable masses for continuous thrust propulsion systems have complicated comparison and evaluation of proposed propulsion concepts. These continuous thrust propulsion systems are of interest to many groups, not the least of which are the electric propulsion and fusion communities. Several charts plotting the results of well-known trajectory simulation codes were developed and are contained in this paper. These charts illustrate the dependence of time of flight and payload ratio on jet power, initial mass, specific impulse and specific power. These charts are intended to be a tool by which people in the propulsion community can explore the possibilities of their propulsion system concepts. Trajectories were simulated using the tools VARITOP and IPOST. VARITOP is a well known trajectory optimization code that involves numerical integration based on calculus of variations. IPOST has several methods of trajectory simulation; the one used in this paper is Cowell's method for full integration of the equations of motion. The analytical method derived in the companion paper was also used to simulate the trajectory. The accuracy of this method is discussed in the paper.

Parameter Sweep and Optimization of Loosely Coupled Simulations Using the DAKOTA Toolkit

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

Elwasif, Wael R; Bernholdt, David E; Pannala, Sreekanth

2012-01-01

The increasing availability of large scale computing capabilities has accelerated the development of high-fidelity coupled simulations. Such simulations typically involve the integration of models that implement various aspects of the complex phenomena under investigation. Coupled simulations are playing an integral role in fields such as climate modeling, earth systems modeling, rocket simulations, computational chemistry, fusion research, and many other computational fields. Model coupling provides scientists with systematic ways to virtually explore the physical, mathematical, and computational aspects of the problem. Such exploration is rarely done using a single execution of a simulation, but rather by aggregating the results from manymore » simulation runs that, together, serve to bring to light novel knowledge about the system under investigation. Furthermore, it is often the case (particularly in engineering disciplines) that the study of the underlying system takes the form of an optimization regime, where the control parameter space is explored to optimize an objective functions that captures system realizability, cost, performance, or a combination thereof. Novel and flexible frameworks that facilitate the integration of the disparate models into a holistic simulation are used to perform this research, while making efficient use of the available computational resources. In this paper, we describe the integration of the DAKOTA optimization and parameter sweep toolkit with the Integrated Plasma Simulator (IPS), a component-based framework for loosely coupled simulations. The integration allows DAKOTA to exploit the internal task and resource management of the IPS to dynamically instantiate simulation instances within a single IPS instance, allowing for greater control over the trade-off between efficiency of resource utilization and time to completion. We present a case study showing the use of the combined DAKOTA-IPS system to aid in the design of a lithium ion battery (LIB) cell, by studying a coupled system involving the electrochemistry and ion transport at the lower length scales and thermal energy transport at the device scales. The DAKOTA-IPS system provides a flexible tool for use in optimization and parameter sweep studies involving loosely coupled simulations that is suitable for use in situations where changes to the constituent components in the coupled simulation are impractical due to intellectual property or code heritage issues.« less

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

PubMed

Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

Validation of the SimSET simulation package for modeling the Siemens Biograph mCT PET scanner

NASA Astrophysics Data System (ADS)

Poon, Jonathan K.; Dahlbom, Magnus L.; Casey, Michael E.; Qi, Jinyi; Cherry, Simon R.; Badawi, Ramsey D.

2015-02-01

Monte Carlo simulation provides a valuable tool in performance assessment and optimization of system design parameters for PET scanners. SimSET is a popular Monte Carlo simulation toolkit that features fast simulation time, as well as variance reduction tools to further enhance computational efficiency. However, SimSET has lacked the ability to simulate block detectors until its most recent release. Our goal is to validate new features of SimSET by developing a simulation model of the Siemens Biograph mCT PET scanner and comparing the results to a simulation model developed in the GATE simulation suite and to experimental results. We used the NEMA NU-2 2007 scatter fraction, count rates, and spatial resolution protocols to validate the SimSET simulation model and its new features. The SimSET model overestimated the experimental results of the count rate tests by 11-23% and the spatial resolution test by 13-28%, which is comparable to previous validation studies of other PET scanners in the literature. The difference between the SimSET and GATE simulation was approximately 4-8% for the count rate test and approximately 3-11% for the spatial resolution test. In terms of computational time, SimSET performed simulations approximately 11 times faster than GATE simulations. The new block detector model in SimSET offers a fast and reasonably accurate simulation toolkit for PET imaging applications.

A study on optimization of hybrid drive train using Advanced Vehicle Simulator (ADVISOR)

NASA Astrophysics Data System (ADS)

Same, Adam; Stipe, Alex; Grossman, David; Park, Jae Wan

This study investigates the advantages and disadvantages of three hybrid drive train configurations: series, parallel, and "through-the-ground" parallel. Power flow simulations are conducted with the MATLAB/Simulink-based software ADVISOR. These simulations are then applied in an application for the UC Davis SAE Formula Hybrid vehicle. ADVISOR performs simulation calculations for vehicle position using a combined backward/forward method. These simulations are used to study how efficiency and agility are affected by the motor, fuel converter, and hybrid configuration. Three different vehicle models are developed to optimize the drive train of a vehicle for three stages of the SAE Formula Hybrid competition: autocross, endurance, and acceleration. Input cycles are created based on rough estimates of track geometry. The output from these ADVISOR simulations is a series of plots of velocity profile and energy storage State of Charge that provide a good estimate of how the Formula Hybrid vehicle will perform on the given course. The most noticeable discrepancy between the input cycle and the actual velocity profile of the vehicle occurs during deceleration. A weighted ranking system is developed to organize the simulation results and to determine the best drive train configuration for the Formula Hybrid vehicle. Results show that the through-the-ground parallel configuration with front-mounted motors achieves an optimal balance of efficiency, simplicity, and cost. ADVISOR is proven to be a useful tool for vehicle power train design for the SAE Formula Hybrid competition. This vehicle model based on ADVISOR simulation is applicable to various studies concerning performance and efficiency of hybrid drive trains.

Analyzing the effectiveness of flare dispensing programs against pulse width modulation seekers using self-organizing maps

NASA Astrophysics Data System (ADS)

Şahingil, Mehmet C.; Aslan, Murat Š.

2013-10-01

Infrared guided missile seekers utilizing pulse width modulation in target tracking is one of the threats against air platforms. To be able to achieve a "soft-kill" protection of own platform against these type of threats, one needs to examine carefully the seeker operating principle with its special electronic counter-counter measure (ECCM) capability. One of the cost-effective ways of soft kill protection is to use flare decoys in accordance with an optimized dispensing program. Such an optimization requires a good understanding of the threat seeker, capabilities of the air platform and engagement scenario information between them. Modeling and simulation is very powerful tool to achieve a valuable insight and understand the underlying phenomenology. A careful interpretation of simulation results is crucial to infer valuable conclusions from the data. In such an interpretation there are lots of factors (features) which affect the results. Therefore, powerful statistical tools and pattern recognition algorithms are of special interest in the analysis. In this paper, we show how self-organizing maps (SOMs), which is one of those powerful tools, can be used in analyzing the effectiveness of various flare dispensing programs against a PWM seeker. We perform several Monte Carlo runs for a typical engagement scenario in a MATLAB-based simulation environment. In each run, we randomly change the flare dispending program and obtain corresponding class: "successful" or "unsuccessful", depending on whether the corresponding flare dispensing program deceives the seeker or not, respectively. Then, in the analysis phase, we use SOMs to interpret and visualize the results.

Comparison of simulated and measured spectra from an X-ray tube for the energies between 20 and 35 keV

NASA Astrophysics Data System (ADS)

Yücel, M.; Emirhan, E.; Bayrak, A.; Ozben, C. S.; Yücel, E. Barlas

2015-11-01

Design and production of a simple and low cost X-ray imaging system that can be used for light industrial applications was targeted in the Nuclear Physics Laboratory of Istanbul Technical University. In this study, production, transmission and detection of X-rays were simulated for the proposed imaging device. OX/70-P dental tube was used and X-ray spectra simulated by Geant4 were validated by comparison with X-ray spectra measured between 20 and 35 keV. Relative detection efficiency of the detector was also determined to confirm the physics processes used in the simulations. Various time optimization tools were performed to reduce the simulation time.

Three-dimensional microstructure simulation of Ni-based superalloy investment castings

NASA Astrophysics Data System (ADS)

Pan, Dong; Xu, Qingyan; Liu, Baicheng

2011-05-01

An integrated macro and micro multi-scale model for the three-dimensional microstructure simulation of Ni-based superalloy investment castings was developed, and applied to industrial castings to investigate grain evolution during solidification. A ray tracing method was used to deal with the complex heat radiation transfer. The microstructure evolution was simulated based on the Modified Cellular Automaton method, which was coupled with three-dimensional nested macro and micro grids. Experiments for Ni-based superalloy turbine wheel investment casting were carried out, which showed a good correspondence with the simulated results. It is indicated that the proposed model is able to predict the microstructure of the casting precisely, which provides a tool for the optimizing process.

Optimization of removal function in computer controlled optical surfacing

NASA Astrophysics Data System (ADS)

Chen, Xi; Guo, Peiji; Ren, Jianfeng

2010-10-01

The technical principle of computer controlled optical surfacing (CCOS) and the common method of optimizing removal function that is used in CCOS are introduced in this paper. A new optimizing method time-sharing synthesis of removal function is proposed to solve problems of the removal function being far away from Gaussian type and slow approaching of the removal function error that encountered in the mode of planet motion or translation-rotation. Detailed time-sharing synthesis of using six removal functions is discussed. For a given region on the workpiece, six positions are selected as the centers of the removal function; polishing tool controlled by the executive system of CCOS revolves around each centre to complete a cycle in proper order. The overall removal function obtained by the time-sharing process is the ratio of total material removal in six cycles to time duration of the six cycles, which depends on the arrangement and distribution of the six removal functions. Simulations on the synthesized overall removal functions under two different modes of motion, i.e., planet motion and translation-rotation are performed from which the optimized combination of tool parameters and distribution of time-sharing synthesis removal functions are obtained. The evaluation function when optimizing is determined by an approaching factor which is defined as the ratio of the material removal within the area of half of the polishing tool coverage from the polishing center to the total material removal within the full polishing tool coverage area. After optimization, it is found that the optimized removal function obtained by time-sharing synthesis is closer to the ideal Gaussian type removal function than those by the traditional methods. The time-sharing synthesis method of the removal function provides an efficient way to increase the convergence speed of the surface error in CCOS for the fabrication of aspheric optical surfaces, and to reduce the intermediate- and high-frequency error.

Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)

2016-01-01

Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.

The design of electron and ion guns, beams, and collectors

NASA Astrophysics Data System (ADS)

Becker, Reinard; Herrmannsfeldt, William B.

2004-01-01

The well known `SLAC Electron Trajectory Program' (EGUN) has been ported to PCs and has been developed into a family of programs for the design and the optimization of particle optics devices including electron and ion guns, beam transport sections and collectors. We will discuss the application of these tools for the design and the optimization of the essential parts of EBIS/T devices. The discussion will include conditions in which restrictions in the reliability of simulations may occur due to the mathematical modeling and how to overcome them.

Simulation Framework for Rapid Entry, Descent, and Landing (EDL) Analysis. Volume 2; Appendices

NASA Technical Reports Server (NTRS)

Murri, Daniel G.

2010-01-01

The NASA Engineering and Safety Center (NESC) was requested to establish the Simulation Framework for Rapid Entry, Descent, and Landing (EDL) Analysis assessment, which involved development of an enhanced simulation architecture using the Program to Optimize Simulated Trajectories II (POST2) simulation tool. The assessment was requested to enhance the capability of the Agency to provide rapid evaluation of EDL characteristics in systems analysis studies, preliminary design, mission development and execution, and time-critical assessments. Many of the new simulation framework capabilities were developed to support the Agency EDL Systems Analysis (EDL-SA) team, that is conducting studies of the technologies and architectures that are required to enable higher mass robotic and human mission to Mars. The appendices to the original report are contained in this document.

Simulation Framework for Rapid Entry, Descent, and Landing (EDL) Analysis, Phase 2 Results

NASA Technical Reports Server (NTRS)

Murri, Daniel G.

2011-01-01

The NASA Engineering and Safety Center (NESC) was requested to establish the Simulation Framework for Rapid Entry, Descent, and Landing (EDL) Analysis assessment, which involved development of an enhanced simulation architecture using the Program to Optimize Simulated Trajectories II simulation tool. The assessment was requested to enhance the capability of the Agency to provide rapid evaluation of EDL characteristics in systems analysis studies, preliminary design, mission development and execution, and time-critical assessments. Many of the new simulation framework capabilities were developed to support the Agency EDL-Systems Analysis (SA) team that is conducting studies of the technologies and architectures that are required to enable human and higher mass robotic missions to Mars. The findings, observations, and recommendations from the NESC are provided in this report.

Simulation Framework for Rapid Entry, Descent, and Landing (EDL) Analysis. Volume 1

NASA Technical Reports Server (NTRS)

Murri, Daniel G.

2010-01-01

The NASA Engineering and Safety Center (NESC) was requested to establish the Simulation Framework for Rapid Entry, Descent, and Landing (EDL) Analysis assessment, which involved development of an enhanced simulation architecture using the Program to Optimize Simulated Trajectories II (POST2) simulation tool. The assessment was requested to enhance the capability of the Agency to provide rapid evaluation of EDL characteristics in systems analysis studies, preliminary design, mission development and execution, and time-critical assessments. Many of the new simulation framework capabilities were developed to support the Agency EDL Systems Analysis (EDL-SA) team, that is conducting studies of the technologies and architectures that are required to enable higher mass robotic and human mission to Mars. The findings of the assessment are contained in this report.

Development and Testing of Control Laws for the Active Aeroelastic Wing Program

NASA Technical Reports Server (NTRS)

Dibley, Ryan P.; Allen, Michael J.; Clarke, Robert; Gera, Joseph; Hodgkinson, John

2005-01-01

The Active Aeroelastic Wing research program was a joint program between the U.S. Air Force Research Laboratory and NASA established to investigate the characteristics of an aeroelastic wing and the technique of using wing twist for roll control. The flight test program employed the use of an F/A-18 aircraft modified by reducing the wing torsional stiffness and adding a custom research flight control system. The research flight control system was optimized to maximize roll rate using only wing surfaces to twist the wing while simultaneously maintaining design load limits, stability margins, and handling qualities. NASA Dryden Flight Research Center developed control laws using the software design tool called CONDUIT, which employs a multi-objective function optimization to tune selected control system design parameters. Modifications were made to the Active Aeroelastic Wing implementation in this new software design tool to incorporate the NASA Dryden Flight Research Center nonlinear F/A-18 simulation for time history analysis. This paper describes the design process, including how the control law requirements were incorporated into constraints for the optimization of this specific software design tool. Predicted performance is also compared to results from flight.

3D FEM Geometry and Material Flow Optimization of Porthole-Die Extrusion

NASA Astrophysics Data System (ADS)

Ceretti, Elisabetta; Mazzoni, Luca; Giardini, Claudio

2007-05-01

The aim of this work is to design and to improve the geometry of a porthole-die for the production of aluminum components by means of 3D FEM simulations. In fact, the use of finite element models will allow to investigate the effects of the die geometry (webs, extrusion cavity) on the material flow and on the stresses acting on the die so to reduce the die wear and to improve the tool life. The software used to perform the simulations was a commercial FEM code, Deform 3D. The technological data introduced in the FE model have been furnished by METRA S.p.A. Company, partner in this research. The results obtained have been considered valid and helpful by the Company for building a new optimized extrusion porthole-die.

A numerical identifiability test for state-space models--application to optimal experimental design.

PubMed

Hidalgo, M E; Ayesa, E

2001-01-01

This paper describes a mathematical tool for identifiability analysis, easily applicable to high order non-linear systems modelled in state-space and implementable in simulators with a time-discrete approach. This procedure also permits a rigorous analysis of the expected estimation errors (average and maximum) in calibration experiments. The methodology is based on the recursive numerical evaluation of the information matrix during the simulation of a calibration experiment and in the setting-up of a group of information parameters based on geometric interpretations of this matrix. As an example of the utility of the proposed test, the paper presents its application to an optimal experimental design of ASM Model No. 1 calibration, in order to estimate the maximum specific growth rate microH and the concentration of heterotrophic biomass XBH.

A Study on Micro-Machining Technology for the Machining of NiTi: Five-Axis Micro-Milling and Micro Deep-Hole Drilling

NASA Astrophysics Data System (ADS)

Biermann, D.; Kahleyss, F.; Krebs, E.; Upmeier, T.

2011-07-01

Micro-sized applications are gaining more and more relevance for NiTi-based shape memory alloys (SMA). Different types of micro-machining offer unique possibilities for the manufacturing of NiTi components. The advantage of machining is the low thermal influence on the workpiece. This is important, because the phase transformation temperatures of NiTi SMAs can be changed and the components may need extensive post manufacturing. The article offers a simulation-based approach to optimize five-axis micro-milling processes with respect to the special material properties of NiTi SMA. Especially, the influence of the various tool inclination angles is considered for introducing an intelligent tool inclination optimization algorithm. Furthermore, aspects of micro deep-hole drilling of SMAs are discussed. Tools with diameters as small as 0.5 mm are used. The possible length-to-diameter ratio reaches up to 50. This process offers new possibilities in the manufacturing of microstents. The study concentrates on the influence of the cutting speed, the feed and the tool design on the tool wear and the quality of the drilled holes.

Validating the Performance of the FHWA Work Zone Model Version 1.0: A Case Study Along I-91 in Springfield, Massachusetts

DOT National Transportation Integrated Search

2017-08-01

Central to the effective design of work zones is being able to understand how drivers behave as they approach and enter a work zone area. States use simulation tools in modeling freeway work zones to predict work zone impacts and to select optimal de...

Computational mechanics and physics at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

South, Jerry C., Jr.

1987-01-01

An overview is given of computational mechanics and physics at NASA Langley Research Center. Computational analysis is a major component and tool in many of Langley's diverse research disciplines, as well as in the interdisciplinary research. Examples are given for algorithm development and advanced applications in aerodynamics, transition to turbulence and turbulence simulation, hypersonics, structures, and interdisciplinary optimization.

2009 Navy ManTech Project Book

DTIC Science & Technology

2009-01-01

pieces which are welded together, filled with syntactic foam , and welded to the sail and hull structure. The ManTech project was successful in...cladding has demonstrated the required performance characteristics . The testing demonstrated manufacturability of optical fibers with enhanced hard...using Liquid Injection Molding Simulation (LIMS) and Polyworx software tools for infusion set-up optimization. Test articles fabricated are

Numerical investigation of optimized CZTSSe based solar cell in Wx-Amps environment

NASA Astrophysics Data System (ADS)

Mohanty, Soumya Priyadarshini; Padhy, Srinibasa; Chowdhury, Joy; Sing, Udai P.

2018-05-01

The CZTSSe is the modified version of CZTS with selenium infusion. It shows maximum efficiency in the band gap from 1 to 1.4 eV. In our present work CZTSSe based solar cell is investigated using Wx-Amps tool. The Mo layer, absorber layer, CdS layer, i-ZnO [4]and Al-ZnO layers with their electrical, optical and material parameters are fitted in the tool. The vital parameters such as carrier density, thickness of the CZTSSe absorber layer, operating temperature, CdS buffer layer thickness and its carrier density on the cell interpretation are calculated. From[4] the simulation results it is apparent that the optimal absorber layer varies from 2.9 µm to 3.7 µm. The temperature variation has a strong influence on the efficiency of the cell. An optimal efficiency of 22% (With Jsc=33 mA/cm2, Voc=0.98 V, and fill factor= 68%) are attained. These results will give some insight for makeing higher efficiency CZTSSe based solar cell.

Optimization and Control of Agent-Based Models in Biology: A Perspective.

PubMed

An, G; Fitzpatrick, B G; Christley, S; Federico, P; Kanarek, A; Neilan, R Miller; Oremland, M; Salinas, R; Laubenbacher, R; Lenhart, S

2017-01-01

Agent-based models (ABMs) have become an increasingly important mode of inquiry for the life sciences. They are particularly valuable for systems that are not understood well enough to build an equation-based model. These advantages, however, are counterbalanced by the difficulty of analyzing and using ABMs, due to the lack of the type of mathematical tools available for more traditional models, which leaves simulation as the primary approach. As models become large, simulation becomes challenging. This paper proposes a novel approach to two mathematical aspects of ABMs, optimization and control, and it presents a few first steps outlining how one might carry out this approach. Rather than viewing the ABM as a model, it is to be viewed as a surrogate for the actual system. For a given optimization or control problem (which may change over time), the surrogate system is modeled instead, using data from the ABM and a modeling framework for which ready-made mathematical tools exist, such as differential equations, or for which control strategies can explored more easily. Once the optimization problem is solved for the model of the surrogate, it is then lifted to the surrogate and tested. The final step is to lift the optimization solution from the surrogate system to the actual system. This program is illustrated with published work, using two relatively simple ABMs as a demonstration, Sugarscape and a consumer-resource ABM. Specific techniques discussed include dimension reduction and approximation of an ABM by difference equations as well systems of PDEs, related to certain specific control objectives. This demonstration illustrates the very challenging mathematical problems that need to be solved before this approach can be realistically applied to complex and large ABMs, current and future. The paper outlines a research program to address them.

Adaptive surrogate model based multiobjective optimization for coastal aquifer management

NASA Astrophysics Data System (ADS)

Song, Jian; Yang, Yun; Wu, Jianfeng; Wu, Jichun; Sun, Xiaomin; Lin, Jin

2018-06-01

In this study, a novel surrogate model assisted multiobjective memetic algorithm (SMOMA) is developed for optimal pumping strategies of large-scale coastal groundwater problems. The proposed SMOMA integrates an efficient data-driven surrogate model with an improved non-dominated sorted genetic algorithm-II (NSGAII) that employs a local search operator to accelerate its convergence in optimization. The surrogate model based on Kernel Extreme Learning Machine (KELM) is developed and evaluated as an approximate simulator to generate the patterns of regional groundwater flow and salinity levels in coastal aquifers for reducing huge computational burden. The KELM model is adaptively trained during evolutionary search to satisfy desired fidelity level of surrogate so that it inhibits error accumulation of forecasting and results in correctly converging to true Pareto-optimal front. The proposed methodology is then applied to a large-scale coastal aquifer management in Baldwin County, Alabama. Objectives of minimizing the saltwater mass increase and maximizing the total pumping rate in the coastal aquifers are considered. The optimal solutions achieved by the proposed adaptive surrogate model are compared against those solutions obtained from one-shot surrogate model and original simulation model. The adaptive surrogate model does not only improve the prediction accuracy of Pareto-optimal solutions compared with those by the one-shot surrogate model, but also maintains the equivalent quality of Pareto-optimal solutions compared with those by NSGAII coupled with original simulation model, while retaining the advantage of surrogate models in reducing computational burden up to 94% of time-saving. This study shows that the proposed methodology is a computationally efficient and promising tool for multiobjective optimizations of coastal aquifer managements.

Investigation of roughing machining simulation by using visual basic programming in NX CAM system

NASA Astrophysics Data System (ADS)

Hafiz Mohamad, Mohamad; Nafis Osman Zahid, Muhammed

2018-03-01

This paper outlines a simulation study to investigate the characteristic of roughing machining simulation in 4th axis milling processes by utilizing visual basic programming in NX CAM systems. The selection and optimization of cutting orientation in rough milling operation is critical in 4th axis machining. The main purpose of roughing operation is to approximately shape the machined parts into finished form by removing the bulk of material from workpieces. In this paper, the simulations are executed by manipulating a set of different cutting orientation to generate estimated volume removed from the machine parts. The cutting orientation with high volume removal is denoted as an optimum value and chosen to execute a roughing operation. In order to run the simulation, customized software is developed to assist the routines. Operations build-up instructions in NX CAM interface are translated into programming codes via advanced tool available in the Visual Basic Studio. The codes is customized and equipped with decision making tools to run and control the simulations. It permits the integration with any independent program files to execute specific operations. This paper aims to discuss about the simulation program and identifies optimum cutting orientations for roughing processes. The output of this study will broaden up the simulation routines performed in NX CAM systems.

A Python tool to set up relative free energy calculations in GROMACS

PubMed Central

Klimovich, Pavel V.; Mobley, David L.

2015-01-01

Free energy calculations based on molecular dynamics (MD) simulations have seen a tremendous growth in the last decade. However, it is still difficult and tedious to set them up in an automated manner, as the majority of the present-day MD simulation packages lack that functionality. Relative free energy calculations are a particular challenge for several reasons, including the problem of finding a common substructure and mapping the transformation to be applied. Here we present a tool, alchemical-setup.py, that automatically generates all the input files needed to perform relative solvation and binding free energy calculations with the MD package GROMACS. When combined with Lead Optimization Mapper [14], recently developed in our group, alchemical-setup.py allows fully automated setup of relative free energy calculations in GROMACS. Taking a graph of the planned calculations and a mapping, both computed by LOMAP, our tool generates the topology and coordinate files needed to perform relative free energy calculations for a given set of molecules, and provides a set of simulation input parameters. The tool was validated by performing relative hydration free energy calculations for a handful of molecules from the SAMPL4 challenge [16]. Good agreement with previously published results and the straightforward way in which free energy calculations can be conducted make alchemical-setup.py a promising tool for automated setup of relative solvation and binding free energy calculations. PMID:26487189

The Alba ray tracing code: ART

NASA Astrophysics Data System (ADS)

Nicolas, Josep; Barla, Alessandro; Juanhuix, Jordi

2013-09-01

The Alba ray tracing code (ART) is a suite of Matlab functions and tools for the ray tracing simulation of x-ray beamlines. The code is structured in different layers, which allow its usage as part of optimization routines as well as an easy control from a graphical user interface. Additional tools for slope error handling and for grating efficiency calculations are also included. Generic characteristics of ART include the accumulation of rays to improve statistics without memory limitations, and still providing normalized values of flux and resolution in physically meaningful units.

Extending rule-based methods to model molecular geometry and 3D model resolution.

PubMed

Hoard, Brittany; Jacobson, Bruna; Manavi, Kasra; Tapia, Lydia

2016-08-01

Computational modeling is an important tool for the study of complex biochemical processes associated with cell signaling networks. However, it is challenging to simulate processes that involve hundreds of large molecules due to the high computational cost of such simulations. Rule-based modeling is a method that can be used to simulate these processes with reasonably low computational cost, but traditional rule-based modeling approaches do not include details of molecular geometry. The incorporation of geometry into biochemical models can more accurately capture details of these processes, and may lead to insights into how geometry affects the products that form. Furthermore, geometric rule-based modeling can be used to complement other computational methods that explicitly represent molecular geometry in order to quantify binding site accessibility and steric effects. We propose a novel implementation of rule-based modeling that encodes details of molecular geometry into the rules and binding rates. We demonstrate how rules are constructed according to the molecular curvature. We then perform a study of antigen-antibody aggregation using our proposed method. We simulate the binding of antibody complexes to binding regions of the shrimp allergen Pen a 1 using a previously developed 3D rigid-body Monte Carlo simulation, and we analyze the aggregate sizes. Then, using our novel approach, we optimize a rule-based model according to the geometry of the Pen a 1 molecule and the data from the Monte Carlo simulation. We use the distances between the binding regions of Pen a 1 to optimize the rules and binding rates. We perform this procedure for multiple conformations of Pen a 1 and analyze the impact of conformation and resolution on the optimal rule-based model. We find that the optimized rule-based models provide information about the average steric hindrance between binding regions and the probability that antibodies will bind to these regions. These optimized models quantify the variation in aggregate size that results from differences in molecular geometry and from model resolution.

Study on Ultra-deep Azimuthal Electromagnetic Resistivity LWD Tool by Influence Quantification on Azimuthal Depth of Investigation and Real Signal

NASA Astrophysics Data System (ADS)

Li, Kesai; Gao, Jie; Ju, Xiaodong; Zhu, Jun; Xiong, Yanchun; Liu, Shuai

2018-05-01

This paper proposes a new tool design of ultra-deep azimuthal electromagnetic (EM) resistivity logging while drilling (LWD) for deeper geosteering and formation evaluation, which can benefit hydrocarbon exploration and development. First, a forward numerical simulation of azimuthal EM resistivity LWD is created based on the fast Hankel transform (FHT) method, and its accuracy is confirmed under classic formation conditions. Then, a reasonable range of tool parameters is designed by analyzing the logging response. However, modern technological limitations pose challenges to selecting appropriate tool parameters for ultra-deep azimuthal detection under detectable signal conditions. Therefore, this paper uses grey relational analysis (GRA) to quantify the influence of tool parameters on voltage and azimuthal investigation depth. After analyzing thousands of simulation data under different environmental conditions, the random forest is used to fit data and identify an optimal combination of tool parameters due to its high efficiency and accuracy. Finally, the structure of the ultra-deep azimuthal EM resistivity LWD tool is designed with a theoretical azimuthal investigation depth of 27.42-29.89 m in classic different isotropic and anisotropic formations. This design serves as a reliable theoretical foundation for efficient geosteering and formation evaluation in high-angle and horizontal (HA/HZ) wells in the future.

High Performance Computing Modeling Advances Accelerator Science for High-Energy Physics

DOE PAGES

Amundson, James; Macridin, Alexandru; Spentzouris, Panagiotis

2014-07-28

The development and optimization of particle accelerators are essential for advancing our understanding of the properties of matter, energy, space, and time. Particle accelerators are complex devices whose behavior involves many physical effects on multiple scales. Therefore, advanced computational tools utilizing high-performance computing are essential for accurately modeling them. In the past decade, the US Department of Energy's SciDAC program has produced accelerator-modeling tools that have been employed to tackle some of the most difficult accelerator science problems. The authors discuss the Synergia framework and its applications to high-intensity particle accelerator physics. Synergia is an accelerator simulation package capable ofmore » handling the entire spectrum of beam dynamics simulations. Our authors present Synergia's design principles and its performance on HPC platforms.« less

Electron Beam Melting and Refining of Metals: Computational Modeling and Optimization

PubMed Central

Vutova, Katia; Donchev, Veliko

2013-01-01

Computational modeling offers an opportunity for a better understanding and investigation of thermal transfer mechanisms. It can be used for the optimization of the electron beam melting process and for obtaining new materials with improved characteristics that have many applications in the power industry, medicine, instrument engineering, electronics, etc. A time-dependent 3D axis-symmetrical heat model for simulation of thermal transfer in metal ingots solidified in a water-cooled crucible at electron beam melting and refining (EBMR) is developed. The model predicts the change in the temperature field in the casting ingot during the interaction of the beam with the material. A modified Pismen-Rekford numerical scheme to discretize the analytical model is developed. These equation systems, describing the thermal processes and main characteristics of the developed numerical method, are presented. In order to optimize the technological regimes, different criteria for better refinement and obtaining dendrite crystal structures are proposed. Analytical problems of mathematical optimization are formulated, discretized and heuristically solved by cluster methods. Using important for the practice simulation results, suggestions can be made for EBMR technology optimization. The proposed tool is important and useful for studying, control, optimization of EBMR process parameters and improving of the quality of the newly produced materials. PMID:28788351

Adjoint-Based Aerodynamic Design of Complex Aerospace Configurations

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.

2016-01-01

An overview of twenty years of adjoint-based aerodynamic design research at NASA Langley Research Center is presented. Adjoint-based algorithms provide a powerful tool for efficient sensitivity analysis of complex large-scale computational fluid dynamics (CFD) simulations. Unlike alternative approaches for which computational expense generally scales with the number of design parameters, adjoint techniques yield sensitivity derivatives of a simulation output with respect to all input parameters at the cost of a single additional simulation. With modern large-scale CFD applications often requiring millions of compute hours for a single analysis, the efficiency afforded by adjoint methods is critical in realizing a computationally tractable design optimization capability for such applications.

Optimum spaceborne computer system design by simulation

NASA Technical Reports Server (NTRS)

Williams, T.; Weatherbee, J. E.; Taylor, D. S.

1972-01-01

A deterministic digital simulation model is described which models the Automatically Reconfigurable Modular Multiprocessor System (ARMMS), a candidate computer system for future manned and unmanned space missions. Use of the model as a tool in configuring a minimum computer system for a typical mission is demonstrated. The configuration which is developed as a result of studies with the simulator is optimal with respect to the efficient use of computer system resources, i.e., the configuration derived is a minimal one. Other considerations such as increased reliability through the use of standby spares would be taken into account in the definition of a practical system for a given mission.

Simulation Software

NASA Technical Reports Server (NTRS)

1996-01-01

Various NASA Small Business Innovation Research grants from Marshall Space Flight Center, Langley Research Center and Ames Research Center were used to develop the 'kernel' of COMCO's modeling and simulation software, the PHLEX finite element code. NASA needed it to model designs of flight vehicles; one of many customized commercial applications is UNISIM, a PHLEX-based code for analyzing underground flows in oil reservoirs for Texaco, Inc. COMCO's products simulate a computational mechanics problem, estimate the solution's error and produce the optimal hp-adapted mesh for the accuracy the user chooses. The system is also used as a research or training tool in universities and in mechanical design in industrial corporations.

Design Time Optimization for Hardware Watermarking Protection of HDL Designs

PubMed Central

Castillo, E.; Morales, D. P.; García, A.; Parrilla, L.; Todorovich, E.; Meyer-Baese, U.

2015-01-01

HDL-level design offers important advantages for the application of watermarking to IP cores, but its complexity also requires tools automating these watermarking algorithms. A new tool for signature distribution through combinational logic is proposed in this work. IPP@HDL, a previously proposed high-level watermarking technique, has been employed for evaluating the tool. IPP@HDL relies on spreading the bits of a digital signature at the HDL design level using combinational logic included within the original system. The development of this new tool for the signature distribution has not only extended and eased the applicability of this IPP technique, but it has also improved the signature hosting process itself. Three algorithms were studied in order to develop this automated tool. The selection of a cost function determines the best hosting solutions in terms of area and performance penalties on the IP core to protect. An 1D-DWT core and MD5 and SHA1 digital signatures were used in order to illustrate the benefits of the new tool and its optimization related to the extraction logic resources. Among the proposed algorithms, the alternative based on simulated annealing reduces the additional resources while maintaining an acceptable computation time and also saving designer effort and time. PMID:25861681

The LSST operations simulator

NASA Astrophysics Data System (ADS)

Delgado, Francisco; Saha, Abhijit; Chandrasekharan, Srinivasan; Cook, Kem; Petry, Catherine; Ridgway, Stephen

2014-08-01

The Operations Simulator for the Large Synoptic Survey Telescope (LSST; http://www.lsst.org) allows the planning of LSST observations that obey explicit science driven observing specifications, patterns, schema, and priorities, while optimizing against the constraints placed by design-specific opto-mechanical system performance of the telescope facility, site specific conditions as well as additional scheduled and unscheduled downtime. It has a detailed model to simulate the external conditions with real weather history data from the site, a fully parameterized kinematic model for the internal conditions of the telescope, camera and dome, and serves as a prototype for an automatic scheduler for the real time survey operations with LSST. The Simulator is a critical tool that has been key since very early in the project, to help validate the design parameters of the observatory against the science requirements and the goals from specific science programs. A simulation run records the characteristics of all observations (e.g., epoch, sky position, seeing, sky brightness) in a MySQL database, which can be queried for any desired purpose. Derivative information digests of the observing history are made with an analysis package called Simulation Survey Tools for Analysis and Reporting (SSTAR). Merit functions and metrics have been designed to examine how suitable a specific simulation run is for several different science applications. Software to efficiently compare the efficacy of different survey strategies for a wide variety of science applications using such a growing set of metrics is under development. A recent restructuring of the code allows us to a) use "look-ahead" strategies that avoid cadence sequences that cannot be completed due to observing constraints; and b) examine alternate optimization strategies, so that the most efficient scheduling algorithm(s) can be identified and used: even few-percent efficiency gains will create substantive scientific opportunity. The enhanced simulator is being used to assess the feasibility of desired observing cadences, study the impact of changing science program priorities and assist with performance margin investigations of the LSST system.

Fast multipurpose Monte Carlo simulation for proton therapy using multi- and many-core CPU architectures

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

Souris, Kevin, E-mail: kevin.souris@uclouvain.be; Lee, John Aldo; Sterpin, Edmond

2016-04-15

Purpose: Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. Methods: A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithmmore » of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the GATE/GEANT4 Monte Carlo application for homogeneous and heterogeneous geometries. Results: Comparisons with GATE/GEANT4 for various geometries show deviations within 2%–1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10{sup 7} primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. Conclusions: MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.« less

Increasing power generation in horizontal axis wind turbines using optimized flow control

NASA Astrophysics Data System (ADS)

Cooney, John A., Jr.

In order to effectively realize future goals for wind energy, the efficiency of wind turbines must increase beyond existing technology. One direct method for achieving increased efficiency is by improving the individual power generation characteristics of horizontal axis wind turbines. The potential for additional improvement by traditional approaches is diminishing rapidly however. As a result, a research program was undertaken to assess the potential of using distributed flow control to increase power generation. The overall objective was the development of validated aerodynamic simulations and flow control approaches to improve wind turbine power generation characteristics. BEM analysis was conducted for a general set of wind turbine models encompassing last, current, and next generation designs. This analysis indicated that rotor lift control applied in Region II of the turbine power curve would produce a notable increase in annual power generated. This was achieved by optimizing induction factors along the rotor blade for maximum power generation. In order to demonstrate this approach and other advanced concepts, the University of Notre Dame established the Laboratory for Enhanced Wind Energy Design (eWiND). This initiative includes a fully instrumented meteorological tower and two pitch-controlled wind turbines. The wind turbines are representative in their design and operation to larger multi-megawatt turbines, but of a scale that allows rotors to be easily instrumented and replaced to explore new design concepts. Baseline data detailing typical site conditions and turbine operation is presented. To realize optimized performance, lift control systems were designed and evaluated in CFD simulations coupled with shape optimization tools. These were integrated into a systematic design methodology involving BEM simulations, CFD simulations and shape optimization, and selected experimental validation. To refine and illustrate the proposed design methodology, a complete design cycle was performed for the turbine model incorporated in the wind energy lab. Enhanced power generation was obtained through passive trailing edge shaping aimed at reaching lift and lift-to-drag goals predicted to optimize performance. These targets were determined by BEM analysis to improve power generation characteristics and annual energy production (AEP) for the wind turbine. A preliminary design was validated in wind tunnel experiments on a 2D rotor section in preparation for testing in the full atmospheric environment of the eWiND Laboratory. These tests were performed for the full-scale geometry and atmospheric conditions. Upon making additional improvements to the shape optimization tools, a series of trailing edge additions were designed to optimize power generation. The trailing edge additions were predicted to increase the AEP by up to 4.2% at the White Field site. The pieces were rapid-prototyped and installed on the wind turbine in March, 2014. Field tests are ongoing.

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

DOE PAGES

Chan, Cy P.; Bachan, John D.; Kenny, Joseph P.; ...

2017-01-26

Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and executionmore » strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.« less

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

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

Chan, Cy P.; Bachan, John D.; Kenny, Joseph P.

Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and executionmore » strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.« less

Coma measurement by use of an alternating phase-shifting mask mark with a specific phase width

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

Qiu Zicheng; Wang Xiangzhao; Yuan Qiongyan

2009-01-10

The correlation between the coma sensitivity of the alternating phase-shifting mask (Alt-PSM) mark and the mark's structure is studied based on the Hopkins theory of partially coherent imaging and positive resist optical lithography (PROLITH) simulation. It is found that an optimized Alt-PSM mark with its phase width being two-thirds its pitch has a higher sensitivity to coma than Alt-PSM marks with the same pitch and the different phase widths. The pitch of the Alt-PSM mark is also optimized by PROLITH simulation, and the structure of p=1.92{lambda}/NA and pw=2p/3 proves to be with the highest sensitivity. The optimized Alt-PSM mark ismore » used as a measurement mark to retrieve coma aberration from the projection optics in lithographic tools. In comparison with an ordinary Alt-PSM mark with its phase width being a half its pitch, the measurement accuracies of Z7 and Z14 apparently increase.« less

Automated design evolution of stereochemically randomized protein foldamers

NASA Astrophysics Data System (ADS)

Ranbhor, Ranjit; Kumar, Anil; Patel, Kirti; Ramakrishnan, Vibin; Durani, Susheel

2018-05-01

Diversification of chain stereochemistry opens up the possibilities of an ‘in principle’ increase in the design space of proteins. This huge increase in the sequence and consequent structural variation is aimed at the generation of smart materials. To diversify protein structure stereochemically, we introduced L- and D-α-amino acids as the design alphabet. With a sequence design algorithm, we explored the usage of specific variables such as chirality and the sequence of this alphabet in independent steps. With molecular dynamics, we folded stereochemically diverse homopolypeptides and evaluated their ‘fitness’ for possible design as protein-like foldamers. We propose a fitness function to prune the most optimal fold among 1000 structures simulated with an automated repetitive simulated annealing molecular dynamics (AR-SAMD) approach. The highly scored poly-leucine fold with sequence lengths of 24 and 30 amino acids were later sequence-optimized using a Dead End Elimination cum Monte Carlo based optimization tool. This paper demonstrates a novel approach for the de novo design of protein-like foldamers.

The MCUCN simulation code for ultracold neutron physics

NASA Astrophysics Data System (ADS)

Zsigmond, G.

2018-02-01

Ultracold neutrons (UCN) have very low kinetic energies 0-300 neV, thereby can be stored in specific material or magnetic confinements for many hundreds of seconds. This makes them a very useful tool in probing fundamental symmetries of nature (for instance charge-parity violation by neutron electric dipole moment experiments) and contributing important parameters for the Big Bang nucleosynthesis (neutron lifetime measurements). Improved precision experiments are in construction at new and planned UCN sources around the world. MC simulations play an important role in the optimization of such systems with a large number of parameters, but also in the estimation of systematic effects, in benchmarking of analysis codes, or as part of the analysis. The MCUCN code written at PSI has been extensively used for the optimization of the UCN source optics and in the optimization and analysis of (test) experiments within the nEDM project based at PSI. In this paper we present the main features of MCUCN and interesting benchmark and application examples.

Optimal design of wide-view-angle waveplate used for polarimetric diagnosis of lithography system

NASA Astrophysics Data System (ADS)

Gu, Honggang; Jiang, Hao; Zhang, Chuanwei; Chen, Xiuguo; Liu, Shiyuan

2016-03-01

The diagnosis and control of the polarization aberrations is one of the main concerns in a hyper numerical aperture (NA) lithography system. Waveplates are basic and indispensable optical components in the polarimetric diagnosis tools for the immersion lithography system. The retardance of a birefringent waveplate is highly sensitive to the incident angle of the light, which makes the conventional waveplate not suitable to be applied in the polarimetric diagnosis for the immersion lithography system with a hyper NA. In this paper, we propose a method for the optimal design of a wideview- angle waveplate by combining two positive waveplates made from magnesium fluoride (MgF2) and two negative waveplates made from sapphire using the simulated annealing algorithm. Theoretical derivations and numerical simulations are performed and the results demonstrate that the maximum variation in the retardance of the optimally designed wide-view-angle waveplate is less than +/- 0.35° for a wide-view-angle range of +/- 20°.

Development of a Scale-up Tool for Pervaporation Processes

PubMed Central

Thiess, Holger; Strube, Jochen

2018-01-01

In this study, an engineering tool for the design and optimization of pervaporation processes is developed based on physico-chemical modelling coupled with laboratory/mini-plant experiments. The model incorporates the solution-diffusion-mechanism, polarization effects (concentration and temperature), axial dispersion, pressure drop and the temperature drop in the feed channel due to vaporization of the permeating components. The permeance, being the key model parameter, was determined via dehydration experiments on a mini-plant scale for the binary mixtures ethanol/water and ethyl acetate/water. A second set of experimental data was utilized for the validation of the model for two chemical systems. The industrially relevant ternary mixture, ethanol/ethyl acetate/water, was investigated close to its azeotropic point and compared to a simulation conducted with the determined binary permeance data. Experimental and simulation data proved to agree very well for the investigated process conditions. In order to test the scalability of the developed engineering tool, large-scale data from an industrial pervaporation plant used for the dehydration of ethanol was compared to a process simulation conducted with the validated physico-chemical model. Since the membranes employed in both mini-plant and industrial scale were of the same type, the permeance data could be transferred. The comparison of the measured and simulated data proved the scalability of the derived model. PMID:29342956

Development of Response Surface Models for Rapid Analysis & Multidisciplinary Optimization of Launch Vehicle Design Concepts

NASA Technical Reports Server (NTRS)

Unal, Resit

1999-01-01

Multdisciplinary design optimization (MDO) is an important step in the design and evaluation of launch vehicles, since it has a significant impact on performance and lifecycle cost. The objective in MDO is to search the design space to determine the values of design parameters that optimize the performance characteristics subject to system constraints. Vehicle Analysis Branch (VAB) at NASA Langley Research Center has computerized analysis tools in many of the disciplines required for the design and analysis of launch vehicles. Vehicle performance characteristics can be determined by the use of these computerized analysis tools. The next step is to optimize the system performance characteristics subject to multidisciplinary constraints. However, most of the complex sizing and performance evaluation codes used for launch vehicle design are stand-alone tools, operated by disciplinary experts. They are, in general, difficult to integrate and use directly for MDO. An alternative has been to utilize response surface methodology (RSM) to obtain polynomial models that approximate the functional relationships between performance characteristics and design variables. These approximation models, called response surface models, are then used to integrate the disciplines using mathematical programming methods for efficient system level design analysis, MDO and fast sensitivity simulations. A second-order response surface model of the form given has been commonly used in RSM since in many cases it can provide an adequate approximation especially if the region of interest is sufficiently limited.

TU-A-17A-02: In Memoriam of Ben Galkin: Virtual Tools for Validation of X-Ray Breast Imaging Systems

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

Myers, K; Bakic, P; Abbey, C

2014-06-15

This symposium will explore simulation methods for the preclinical evaluation of novel 3D and 4D x-ray breast imaging systems – the subject of AAPM taskgroup TG234. Given the complex design of modern imaging systems, simulations offer significant advantages over long and costly clinical studies in terms of reproducibility, reduced radiation exposures, a known reference standard, and the capability for studying patient and disease subpopulations through appropriate choice of simulation parameters. Our focus will be on testing the realism of software anthropomorphic phantoms and virtual clinical trials tools developed for the optimization and validation of breast imaging systems. The symposium willmore » review the stateof- the-science, as well as the advantages and limitations of various approaches to testing realism of phantoms and simulated breast images. Approaches based upon the visual assessment of synthetic breast images by expert observers will be contrasted with approaches based upon comparing statistical properties between synthetic and clinical images. The role of observer models in the assessment of realism will be considered. Finally, an industry perspective will be presented, summarizing the role and importance of virtual tools and simulation methods in product development. The challenges and conditions that must be satisfied in order for computational modeling and simulation to play a significantly increased role in the design and evaluation of novel breast imaging systems will be addressed. Learning Objectives: Review the state-of-the science in testing realism of software anthropomorphic phantoms and virtual clinical trials tools; Compare approaches based upon the visual assessment by expert observers vs. the analysis of statistical properties of synthetic images; Discuss the role of observer models in the assessment of realism; Summarize the industry perspective to virtual methods for breast imaging.« less

A network-based approach for resistance transmission in bacterial populations.

PubMed

Gehring, Ronette; Schumm, Phillip; Youssef, Mina; Scoglio, Caterina

2010-01-07

Horizontal transfer of mobile genetic elements (conjugation) is an important mechanism whereby resistance is spread through bacterial populations. The aim of our work is to develop a mathematical model that quantitatively describes this process, and to use this model to optimize antimicrobial dosage regimens to minimize resistance development. The bacterial population is conceptualized as a compartmental mathematical model to describe changes in susceptible, resistant, and transconjugant bacteria over time. This model is combined with a compartmental pharmacokinetic model to explore the effect of different plasma drug concentration profiles. An agent-based simulation tool is used to account for resistance transfer occurring when two bacteria are adjacent or in close proximity. In addition, a non-linear programming optimal control problem is introduced to minimize bacterial populations as well as the drug dose. Simulation and optimization results suggest that the rapid death of susceptible individuals in the population is pivotal in minimizing the number of transconjugants in a population. This supports the use of potent antimicrobials that rapidly kill susceptible individuals and development of dosage regimens that maintain effective antimicrobial drug concentrations for as long as needed to kill off the susceptible population. Suggestions are made for experiments to test the hypotheses generated by these simulations.

Numerical simulation of thermal stress distributions in Czochralski-grown silicon crystals

NASA Astrophysics Data System (ADS)

Kumar, M. Avinash; Srinivasan, M.; Ramasamy, P.

2018-04-01

Numerical simulation is one of the important tools in the investigation and optimization of the single-crystal silicon grown by the Czochralski (Cz) method. A 2D steady global heat transfer model was used to investigate the temperature distribution and the thermal stress distributions at particular crystal position during the Cz growth process. The computation determines the thermal stress such as von Mises stress and maximum shear stress distribution along grown crystal and shows possible reason for dislocation formation in the Cz-grown single-crystal silicon.

“Elegant Tool” Delivers Genome-Level Science for Electrolytes

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

Keith Arterburn

Now, a ‘disruptive, virtual scientific simulation tool’ delivers a new, genome-level investigation for electrolytes to develop better, more efficient batteries. Dr. Kevin Gering, an Idaho National Laboratory researcher, has developed the Advanced Electrolyte Model (AEM), a copyrighted molecular-based simulation tool that has been scientifically proven and validated using at least a dozen ‘real-world’ physical metrics. Nominated for the 2014 international R&D 100 Award, AEM revolutionizes electrolyte materials selection, optimizing combinations and key design elements to make battery design and experimentation quick, accurate and responsive to specific needs.

Simulation-based comprehensive benchmarking of RNA-seq aligners

PubMed Central

Baruzzo, Giacomo; Hayer, Katharina E; Kim, Eun Ji; Di Camillo, Barbara; FitzGerald, Garret A; Grant, Gregory R

2018-01-01

Alignment is the first step in most RNA-seq analysis pipelines, and the accuracy of downstream analyses depends heavily on it. Unlike most steps in the pipeline, alignment is particularly amenable to benchmarking with simulated data. We performed a comprehensive benchmarking of 14 common splice-aware aligners for base, read, and exon junction-level accuracy and compared default with optimized parameters. We found that performance varied by genome complexity, and accuracy and popularity were poorly correlated. The most widely cited tool underperforms for most metrics, particularly when using default settings. PMID:27941783

I-FORCAST: Rapid Flight Planning Tool

NASA Technical Reports Server (NTRS)

Oaida, Bogdan; Khan, Mohammed; Mercury, Michael B.

2012-01-01

I-FORCAST (Instrument - Field of Regard Coverage Analysis and Simulation Tool) is a flight planning tool specifically designed for quickly verifying the feasibility and estimating the cost of airborne remote sensing campaigns (see figure). Flights are simulated by being broken into three predefined routing algorithms as necessary: mapping in a snaking pattern, mapping the area around a point target (like a volcano) with a star pattern, and mapping the area between a list of points. The tool has been used to plan missions for radar, lidar, and in-situ atmospheric measuring instruments for a variety of aircraft. It has also been used for global and regional scale campaigns and automatically includes landings when refueling is required. The software has been compared to the flight times of known commercial aircraft route travel times, as well as a UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) campaign, and was within 15% of the actual flight time. Most of the discrepancy is due to non-optimal flight paths taken by actual aircraft to avoid restricted airspace and used to follow landing and take-off corridors.

Transparency and Documentation in Simulations of Infectious Disease Outbreaks: Towards Evidence-Based Public Health Decisions and Communications

NASA Astrophysics Data System (ADS)

Ekberg, Joakim; Timpka, Toomas; Morin, Magnus; Jenvald, Johan; Nyce, James M.; Gursky, Elin A.; Eriksson, Henrik

Computer simulations have emerged as important tools in the preparation for outbreaks of infectious disease. To support the collaborative planning and responding to the outbreaks, reports from simulations need to be transparent (accessible) with regard to the underlying parametric settings. This paper presents a design for generation of simulation reports where the background settings used in the simulation models are automatically visualized. We extended the ontology-management system Protégé to tag different settings into categories, and included these in report generation in parallel to the simulation outcomes. The report generator takes advantage of an XSLT specification and collects the documentation of the particular simulation settings into abridged XMLs including also summarized results. We conclude that even though inclusion of critical background settings in reports may not increase the accuracy of infectious disease simulations, it can prevent misunderstandings and less than optimal public health decisions.

Analysis procedures and subjective flight results of a simulator validation and cue fidelity experiment

NASA Technical Reports Server (NTRS)

Carr, Peter C.; Mckissick, Burnell T.

1988-01-01

A joint experiment to investigate simulator validation and cue fidelity was conducted by the Dryden Flight Research Facility of NASA Ames Research Center (Ames-Dryden) and NASA Langley Research Center. The primary objective was to validate the use of a closed-loop pilot-vehicle mathematical model as an analytical tool for optimizing the tradeoff between simulator fidelity requirements and simulator cost. The validation process includes comparing model predictions with simulation and flight test results to evaluate various hypotheses for differences in motion and visual cues and information transfer. A group of five pilots flew air-to-air tracking maneuvers in the Langley differential maneuvering simulator and visual motion simulator and in an F-14 aircraft at Ames-Dryden. The simulators used motion and visual cueing devices including a g-seat, a helmet loader, wide field-of-view horizon, and a motion base platform.

Springback optimization in automotive Shock Absorber Cup with Genetic Algorithm

NASA Astrophysics Data System (ADS)

Kakandikar, Ganesh; Nandedkar, Vilas

2018-02-01

Drawing or forming is a process normally used to achieve a required component form from a metal blank by applying a punch which radially draws the blank into the die by a mechanical or hydraulic action or combining both. When the component is drawn for more depth than the diameter, it is usually seen as deep drawing, which involves complicated states of material deformation. Due to the radial drawing of the material as it enters the die, radial drawing stress occurs in the flange with existence of the tangential compressive stress. This compression generates wrinkles in the flange. Wrinkling is unwanted phenomenon and can be controlled by application of a blank-holding force. Tensile stresses cause thinning in the wall region of the cup. Three main types of the errors occur in such a process are wrinkling, fracturing and springback. This paper reports a work focused on the springback and control. Due to complexity of the process, tool try-outs and experimentation may be costly, bulky and time consuming. Numerical simulation proves to be a good option for studying the process and developing a control strategy for reducing the springback. Finite-element based simulations have been used popularly for such purposes. In this study, the springback in deep drawing of an automotive Shock Absorber Cup is simulated with finite element method. Taguchi design of experiments and analysis of variance are used to analyze the influencing process parameters on the springback. Mathematical relations are developed to relate the process parameters and the resulting springback. The optimization problem is formulated for the springback, referring to the displacement magnitude in the selected sections. Genetic Algorithm is then applied for process optimization with an objective to minimize the springback. The results indicate that a better prediction of the springback and process optimization could be achieved with a combined use of these methods and tools.

Automatic, unstructured mesh optimization for simulation and assessment of tide- and surge-driven hydrodynamics in a longitudinal estuary: St. Johns River

NASA Astrophysics Data System (ADS)

Bacopoulos, Peter

2018-05-01

A localized truncation error analysis with complex derivatives (LTEA+CD) is applied recursively with advanced circulation (ADCIRC) simulations of tides and storm surge for finite element mesh optimization. Mesh optimization is demonstrated with two iterations of LTEA+CD for tidal simulation in the lower 200 km of the St. Johns River, located in northeast Florida, and achieves more than an over 50% decrease in the number of mesh nodes, relating to a twofold increase in efficiency, at a zero cost to model accuracy. The recursively generated meshes using LTEA+CD lead to successive reductions in the global cumulative truncation error associated with the model mesh. Tides are simulated with root mean square error (RMSE) of 0.09-0.21 m and index of agreement (IA) values generally in the 80s and 90s percentage ranges. Tidal currents are simulated with RMSE of 0.09-0.23 m s-1 and IA values of 97% and greater. Storm tide due to Hurricane Matthew 2016 is simulated with RMSE of 0.09-0.33 m and IA values of 75-96%. Analysis of the LTEA+CD results shows the M2 constituent to dominate the node spacing requirement in the St. Johns River, with the M4 and M6 overtides and the STEADY constituent contributing some. Friction is the predominant physical factor influencing the target element size distribution, especially along the main river stem, while frequency (inertia) and Coriolis (rotation) are supplementary contributing factors. The combination of interior- and boundary-type computational molecules, providing near-full coverage of the model domain, renders LTEA+CD an attractive mesh generation/optimization tool for complex coastal and estuarine domains. The mesh optimization procedure using LTEA+CD is automatic and extensible to other finite element-based numerical models. Discussion is provided on the scope of LTEA+CD, the starting point (mesh) of the procedure, the user-specified scaling of the LTEA+CD results, and the iteration (termination) of LTEA+CD for mesh optimization.

FY10 Report on Multi-scale Simulation of Solvent Extraction Processes: Molecular-scale and Continuum-scale Studies

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

Wardle, Kent E.; Frey, Kurt; Pereira, Candido

2014-02-02

This task is aimed at predictive modeling of solvent extraction processes in typical extraction equipment through multiple simulation methods at various scales of resolution. We have conducted detailed continuum fluid dynamics simulation on the process unit level as well as simulations of the molecular-level physical interactions which govern extraction chemistry. Through combination of information gained through simulations at each of these two tiers along with advanced techniques such as the Lattice Boltzmann Method (LBM) which can bridge these two scales, we can develop the tools to work towards predictive simulation for solvent extraction on the equipment scale (Figure 1). Themore » goal of such a tool-along with enabling optimized design and operation of extraction units-would be to allow prediction of stage extraction effrciency under specified conditions. Simulation efforts on each of the two scales will be described below. As the initial application of FELBM in the work performed during FYl0 has been on annular mixing it will be discussed in context of the continuum-scale. In the future, however, it is anticipated that the real value of FELBM will be in its use as a tool for sub-grid model development through highly refined DNS-like multiphase simulations facilitating exploration and development of droplet models including breakup and coalescence which will be needed for the large-scale simulations where droplet level physics cannot be resolved. In this area, it can have a significant advantage over traditional CFD methods as its high computational efficiency allows exploration of significantly greater physical detail especially as computational resources increase in the future.« less

An interactive tool for outdoor computer controlled cultivation of microalgae in a tubular photobioreactor system.

PubMed

Dormido, Raquel; Sánchez, José; Duro, Natividad; Dormido-Canto, Sebastián; Guinaldo, María; Dormido, Sebastián

2014-03-06

This paper describes an interactive virtual laboratory for experimenting with an outdoor tubular photobioreactor (henceforth PBR for short). This virtual laboratory it makes possible to: (a) accurately reproduce the structure of a real plant (the PBR designed and built by the Department of Chemical Engineering of the University of Almería, Spain); (b) simulate a generic tubular PBR by changing the PBR geometry; (c) simulate the effects of changing different operating parameters such as the conditions of the culture (pH, biomass concentration, dissolved O2, inyected CO2, etc.); (d) simulate the PBR in its environmental context; it is possible to change the geographic location of the system or the solar irradiation profile; (e) apply different control strategies to adjust different variables such as the CO2 injection, culture circulation rate or culture temperature in order to maximize the biomass production; (f) simulate the harvesting. In this way, users can learn in an intuitive way how productivity is affected by any change in the design. It facilitates the learning of how to manipulate essential variables for microalgae growth to design an optimal PBR. The simulator has been developed with Easy Java Simulations, a freeware open-source tool developed in Java, specifically designed for the creation of interactive dynamic simulations.

An Interactive Tool for Outdoor Computer Controlled Cultivation of Microalgae in a Tubular Photobioreactor System

PubMed Central

Dormido, Raquel; Sánchez, José; Duro, Natividad; Dormido-Canto, Sebastián; Guinaldo, María; Dormido, Sebastián

2014-01-01

This paper describes an interactive virtual laboratory for experimenting with an outdoor tubular photobioreactor (henceforth PBR for short). This virtual laboratory it makes possible to: (a) accurately reproduce the structure of a real plant (the PBR designed and built by the Department of Chemical Engineering of the University of Almería, Spain); (b) simulate a generic tubular PBR by changing the PBR geometry; (c) simulate the effects of changing different operating parameters such as the conditions of the culture (pH, biomass concentration, dissolved O2, inyected CO2, etc.); (d) simulate the PBR in its environmental context; it is possible to change the geographic location of the system or the solar irradiation profile; (e) apply different control strategies to adjust different variables such as the CO2 injection, culture circulation rate or culture temperature in order to maximize the biomass production; (f) simulate the harvesting. In this way, users can learn in an intuitive way how productivity is affected by any change in the design. It facilitates the learning of how to manipulate essential variables for microalgae growth to design an optimal PBR. The simulator has been developed with Easy Java Simulations, a freeware open-source tool developed in Java, specifically designed for the creation of interactive dynamic simulations. PMID:24662450

Simulations in Medicine and Biology: Insights and perspectives

NASA Astrophysics Data System (ADS)

Spyrou, George M.

2015-01-01

Modern medicine and biology have been transformed into quantitative sciences of high complexity, with challenging objectives. The aims of medicine are related to early diagnosis, effective therapy, accurate intervention, real time monitoring, procedures/systems/instruments optimization, error reduction, and knowledge extraction. Concurrently, following the explosive production of biological data concerning DNA, RNA, and protein biomolecules, a plethora of questions has been raised in relation to their structure and function, the interactions between them, their relationships and dependencies, their regulation and expression, their location, and their thermodynamic characteristics. Furthermore, the interplay between medicine and biology gives rise to fields like molecular medicine and systems biology which are further interconnected with physics, mathematics, informatics, and engineering. Modelling and simulation is a powerful tool in the fields of Medicine and Biology. Simulating the phenomena hidden inside a diagnostic or therapeutic medical procedure, we are able to obtain control on the whole system and perform multilevel optimization. Furthermore, modelling and simulation gives insights in the various scales of biological representation, facilitating the understanding of the huge amounts of derived data and the related mechanisms behind them. Several examples, as well as the insights and the perspectives of simulations in biomedicine will be presented.

Numerical simulation of multi-rifled tube drawing - finding proper feedstock dimensions and tool geometry

NASA Astrophysics Data System (ADS)

Bella, P.; Buček, P.; Ridzoň, M.; Mojžiš, M.; Parilák, L.'

2017-02-01

Production of multi-rifled seamless steel tubes is quite a new technology in Železiarne Podbrezová. Therefore, a lot of technological questions emerges (process technology, input feedstock dimensions, material flow during drawing, etc.) Pilot experiments to fine tune the process cost a lot of time and energy. For this, numerical simulation would be an alternative solution for achieving optimal parameters in production technology. This would reduce the number of experiments needed, lowering the overall costs of development. However, to claim the numerical results to be relevant it is necessary to verify them against the actual plant trials. Searching for optimal input feedstock dimension for drawing of multi-rifled tube with dimensions Ø28.6 mm × 6.3 mm is what makes the main topic of this paper. As a secondary task, effective position of the plug - die couple has been solved via numerical simulation. Comparing the calculated results with actual numbers from plant trials a good agreement was observed.

A silicon sol-gel approach to the development of forensic blood substitutes: Design Considerations for Research and Training

NASA Astrophysics Data System (ADS)

Stotesbury, Theresa E.

The research and development of synthetic blood substitutes is a reported need within the forensic community. This work contributes to the growing body of knowledge in bloodstain pattern analysis by offering a materials science approach to designing, producing and testing synthetic forensic blood substitutes. A key deliverable from this research is the creation of a robust silicon-based material using the solution-gelation technique that has been validated for controlled passive drip and spatter simulation. The work investigates the physical properties (viscosity, surface tension and density) of forensic blood substitute formulations and describes the similarity in the spreading dynamics of the optimized material to whole human blood. It then explores how blood and other fluids behave in impact simulation using high-speed video analysis and supports the use of the optimized material for spatter simulation. Finally, the work highlights the practical value of the material as an educational tool for both basic and advanced bloodstain experimentation and training.

Launch vehicle design and GNC sizing with ASTOS

NASA Astrophysics Data System (ADS)

Cremaschi, Francesco; Winter, Sebastian; Rossi, Valerio; Wiegand, Andreas

2018-03-01

The European Space Agency (ESA) is currently involved in several activities related to launch vehicle designs (Future Launcher Preparatory Program, Ariane 6, VEGA evolutions, etc.). Within these activities, ESA has identified the importance of developing a simulation infrastructure capable of supporting the multi-disciplinary design and preliminary guidance navigation and control (GNC) design of different launch vehicle configurations. Astos Solutions has developed the multi-disciplinary optimization and launcher GNC simulation and sizing tool (LGSST) under ESA contract. The functionality is integrated in the Analysis, Simulation and Trajectory Optimization Software for space applications (ASTOS) and is intended to be used from the early design phases up to phase B1 activities. ASTOS shall enable the user to perform detailed vehicle design tasks and assessment of GNC systems, covering all aspects of rapid configuration and scenario management, sizing of stages, trajectory-dependent estimation of structural masses, rigid and flexible body dynamics, navigation, guidance and control, worst case analysis, launch safety analysis, performance analysis, and reporting.

Introduction to SIMRAND: Simulation of research and development project

NASA Technical Reports Server (NTRS)

Miles, R. F., Jr.

1982-01-01

SIMRAND: SIMulation of Research ANd Development Projects is a methodology developed to aid the engineering and management decision process in the selection of the optimal set of systems or tasks to be funded on a research and development project. A project may have a set of systems or tasks under consideration for which the total cost exceeds the allocated budget. Other factors such as personnel and facilities may also enter as constraints. Thus the project's management must select, from among the complete set of systems or tasks under consideration, a partial set that satisfies all project constraints. The SIMRAND methodology uses analytical techniques and probability theory, decision analysis of management science, and computer simulation, in the selection of this optimal partial set. The SIMRAND methodology is truly a management tool. It initially specifies the information that must be generated by the engineers, thus providing information for the management direction of the engineers, and it ranks the alternatives according to the preferences of the decision makers.

A neural-network-based model for the dynamic simulation of the tire/suspension system while traversing road irregularities.

PubMed

Guarneri, Paolo; Rocca, Gianpiero; Gobbi, Massimiliano

2008-09-01

This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy.

Shortened OR time and decreased patient risk through use of a modular surgical instrument with artificial intelligence.

PubMed

Miller, David J; Nelson, Carl A; Oleynikov, Dmitry

2009-05-01

With a limited number of access ports, minimally invasive surgery (MIS) often requires the complete removal of one tool and reinsertion of another. Modular or multifunctional tools can be used to avoid this step. In this study, soft computing techniques are used to optimally arrange a modular tool's functional tips, allowing surgeons to deliver treatment of improved quality in less time, decreasing overall cost. The investigators watched University Medical Center surgeons perform MIS procedures (e.g., cholecystectomy and Nissen fundoplication) and recorded the procedures to digital video. The video was then used to analyze the types of instruments used, the duration of each use, and the function of each instrument. These data were aggregated with fuzzy logic techniques using four membership functions to quantify the overall usefulness of each tool. This allowed subsequent optimization of the arrangement of functional tips within the modular tool to decrease overall time spent changing instruments during simulated surgical procedures based on the video recordings. Based on a prototype and a virtual model of a multifunction laparoscopic tool designed by the investigators that can interchange six different instrument tips through the tool's shaft, the range of tool change times is approximately 11-13 s. Using this figure, estimated time savings for the procedures analyzed ranged from 2.5 to over 32 min, and on average, total surgery time can be reduced by almost 17% by using the multifunction tool.

Assessment and Verification of SLS Block 1-B Exploration Upper Stage State and Stage Disposal Performance

NASA Technical Reports Server (NTRS)

Patrick, Sean; Oliver, Emerson

2018-01-01

One of the SLS Navigation System's key performance requirements is a constraint on the payload system's delta-v allocation to correct for insertion errors due to vehicle state uncertainty at payload separation. The SLS navigation team has developed a Delta-Delta-V analysis approach to assess the effect on trajectory correction maneuver (TCM) design needed to correct for navigation errors. This approach differs from traditional covariance analysis based methods and makes no assumptions with regard to the propagation of the state dynamics. This allows for consideration of non-linearity in the propagation of state uncertainties. The Delta-Delta-V analysis approach re-optimizes perturbed SLS mission trajectories by varying key mission states in accordance with an assumed state error. The state error is developed from detailed vehicle 6-DOF Monte Carlo analysis or generated using covariance analysis. These perturbed trajectories are compared to a nominal trajectory to determine necessary TCM design. To implement this analysis approach, a tool set was developed which combines the functionality of a 3-DOF trajectory optimization tool, Copernicus, and a detailed 6-DOF vehicle simulation tool, Marshall Aerospace Vehicle Representation in C (MAVERIC). In addition to delta-v allocation constraints on SLS navigation performance, SLS mission requirement dictate successful upper stage disposal. Due to engine and propellant constraints, the SLS Exploration Upper Stage (EUS) must dispose into heliocentric space by means of a lunar fly-by maneuver. As with payload delta-v allocation, upper stage disposal maneuvers must place the EUS on a trajectory that maximizes the probability of achieving a heliocentric orbit post Lunar fly-by considering all sources of vehicle state uncertainty prior to the maneuver. To ensure disposal, the SLS navigation team has developed an analysis approach to derive optimal disposal guidance targets. This approach maximizes the state error covariance prior to the maneuver to develop and re-optimize a nominal disposal maneuver (DM) target that, if achieved, would maximize the potential for successful upper stage disposal. For EUS disposal analysis, a set of two tools was developed. The first considers only the nominal pre-disposal maneuver state, vehicle constraints, and an a priori estimate of the state error covariance. In the analysis, the optimal nominal disposal target is determined. This is performed by re-formulating the trajectory optimization to consider constraints on the eigenvectors of the error ellipse applied to the nominal trajectory. A bisection search methodology is implemented in the tool to refine these dispersions resulting in the maximum dispersion feasible for successful disposal via lunar fly-by. Success is defined based on the probability that the vehicle will not impact the lunar surface and will achieve a characteristic energy (C3) relative to the Earth such that it is no longer in the Earth-Moon system. The second tool propagates post-disposal maneuver states to determine the success of disposal for provided trajectory achieved states. This is performed using the optimized nominal target within the 6-DOF vehicle simulation. This paper will discuss the application of the Delta-Delta-V analysis approach for performance evaluation as well as trajectory re-optimization so as to demonstrate the system's capability in meeting performance constraints. Additionally, further discussion of the implementation of assessing disposal analysis will be provided.

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model

PubMed Central

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694

Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

NASA Technical Reports Server (NTRS)

McMillan, Michelle L.; Mackie, Scott A.; Gissen, Abe; Vukasinovic, Bojan; Lakebrink, Matthew T.; Glezer, Ari; Mani, Mori; Mace, James L.

2011-01-01

Fail-safe, hybrid, flow control (HFC) is a promising technology for meeting high-speed cruise efficiency, low-noise signature, and reduced fuel-burn goals for future, Hybrid-Wing-Body (HWB) aircraft with embedded engines. This report details the development of HFC technology that enables improved inlet performance in HWB vehicles with highly integrated inlets and embedded engines without adversely affecting vehicle performance. In addition, new test techniques for evaluating Boundary-Layer-Ingesting (BLI)-inlet flow-control technologies developed and demonstrated through this program are documented, including the ability to generate a BLI-like inlet-entrance flow in a direct-connect, wind-tunnel facility, as well as, the use of D-optimal, statistically designed experiments to optimize test efficiency and enable interpretation of results. Validated improvements in numerical analysis tools and methods accomplished through this program are also documented, including Reynolds-Averaged Navier-Stokes CFD simulations of steady-state flow physics for baseline, BLI-inlet diffuser flow, as well as, that created by flow-control devices. Finally, numerical methods were employed in a ground-breaking attempt to directly simulate dynamic distortion. The advances in inlet technologies and prediction tools will help to meet and exceed "N+2" project goals for future HWB aircraft.

Study of a Simulation Tool to Determine Achievable Control Dynamics and Control Power Requirements with Perfect Tracking

NASA Technical Reports Server (NTRS)

Ostroff, Aaron J.

1998-01-01

This paper contains a study of two methods for use in a generic nonlinear simulation tool that could be used to determine achievable control dynamics and control power requirements while performing perfect tracking maneuvers over the entire flight envelope. The two methods are NDI (nonlinear dynamic inversion) and the SOFFT(Stochastic Optimal Feedforward and Feedback Technology) feedforward control structure. Equivalent discrete and continuous SOFFT feedforward controllers have been developed. These equivalent forms clearly show that the closed-loop plant model loop is a plant inversion and is the same as the NDI formulation. The main difference is that the NDI formulation has a closed-loop controller structure whereas SOFFT uses an open-loop command model. Continuous, discrete, and hybrid controller structures have been developed and integrated into the formulation. Linear simulation results show that seven different configurations all give essentially the same response, with the NDI hybrid being slightly different. The SOFFT controller gave better tracking performance compared to the NDI controller when a nonlinear saturation element was added. Future plans include evaluation using a nonlinear simulation.

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.

A Simulation Tool for Dynamic Contrast Enhanced MRI

PubMed Central

Mauconduit, Franck; Christen, Thomas; Barbier, Emmanuel Luc

2013-01-01

The quantification of bolus-tracking MRI techniques remains challenging. The acquisition usually relies on one contrast and the analysis on a simplified model of the various phenomena that arise within a voxel, leading to inaccurate perfusion estimates. To evaluate how simplifications in the interstitial model impact perfusion estimates, we propose a numerical tool to simulate the MR signal provided by a dynamic contrast enhanced (DCE) MRI experiment. Our model encompasses the intrinsic and relaxations, the magnetic field perturbations induced by susceptibility interfaces (vessels and cells), the diffusion of the water protons, the blood flow, the permeability of the vessel wall to the the contrast agent (CA) and the constrained diffusion of the CA within the voxel. The blood compartment is modeled as a uniform compartment. The different blocks of the simulation are validated and compared to classical models. The impact of the CA diffusivity on the permeability and blood volume estimates is evaluated. Simulations demonstrate that the CA diffusivity slightly impacts the permeability estimates ( for classical blood flow and CA diffusion). The effect of long echo times is investigated. Simulations show that DCE-MRI performed with an echo time may already lead to significant underestimation of the blood volume (up to 30% lower for brain tumor permeability values). The potential and the versatility of the proposed implementation are evaluated by running the simulation with realistic vascular geometry obtained from two photons microscopy and with impermeable cells in the extravascular environment. In conclusion, the proposed simulation tool describes DCE-MRI experiments and may be used to evaluate and optimize acquisition and processing strategies. PMID:23516414

Advanced construction management for lunar base construction - Surface operations planner

NASA Technical Reports Server (NTRS)

Kehoe, Robert P.

1992-01-01

The study proposes a conceptual solution and lays the framework for developing a new, sophisticated and intelligent tool for a lunar base construction crew to use. This concept integrates expert systems for critical decision making, virtual reality for training, logistics and laydown optimization, automated productivity measurements, and an advanced scheduling tool to form a unique new planning tool. The concept features extensive use of computers and expert systems software to support the actual work, while allowing the crew to control the project from the lunar surface. Consideration is given to a logistics data base, laydown area management, flexible critical progress scheduler, video simulation of assembly tasks, and assembly information and tracking documentation.

A UVM simulation environment for the study, optimization and verification of HL-LHC digital pixel readout chips

NASA Astrophysics Data System (ADS)

Marconi, S.; Conti, E.; Christiansen, J.; Placidi, P.

2018-05-01

The operating conditions of the High Luminosity upgrade of the Large Hadron Collider are very demanding for the design of next generation hybrid pixel readout chips in terms of particle rate, radiation level and data bandwidth. To this purpose, the RD53 Collaboration has developed for the ATLAS and CMS experiments a dedicated simulation and verification environment using industry-consolidated tools and methodologies, such as SystemVerilog and the Universal Verification Methodology (UVM). This paper presents how the so-called VEPIX53 environment has first guided the design of digital architectures, optimized for processing and buffering very high particle rates, and secondly how it has been reused for the functional verification of the first large scale demonstrator chip designed by the collaboration, which has recently been submitted.

Integration of Dakota into the NEAMS Workbench

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

Swiler, Laura Painton; Lefebvre, Robert A.; Langley, Brandon R.

2017-07-01

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on integrating Dakota into the NEAMS Workbench. The NEAMS Workbench, developed at Oak Ridge National Laboratory, is a new software framework that provides a graphical user interface, input file creation, parsing, validation, job execution, workflow management, and output processing for a variety of nuclear codes. Dakota is a tool developed at Sandia National Laboratories that provides a suite of uncertainty quantification and optimization algorithms. Providing Dakota within the NEAMS Workbench allows users of nuclear simulation codes to perform uncertainty and optimization studies on their nuclear codes frommore » within a common, integrated environment. Details of the integration and parsing are provided, along with an example of Dakota running a sampling study on the fuels performance code, BISON, from within the NEAMS Workbench.« less

A near-optimal guidance for cooperative docking maneuvers

NASA Astrophysics Data System (ADS)

Ciarcià, Marco; Grompone, Alessio; Romano, Marcello

2014-09-01

In this work we study the problem of minimum energy docking maneuvers between two Floating Spacecraft Simulators. The maneuvers are planar and conducted autonomously in a cooperative mode. The proposed guidance strategy is based on the direct method known as Inverse Dynamics in the Virtual Domain, and the nonlinear programming solver known as Sequential Gradient-Restoration Algorithm. The combination of these methods allows for the quick prototyping of near-optimal trajectories, and results in an implementable tool for real-time closed-loop maneuvering. The experimental results included in this paper were obtained by exploiting the recently upgraded Floating Spacecraft-Simulator Testbed of the Spacecraft Robotics Laboratory at the Naval Postgraduate School. A direct performances comparison, in terms of maneuver energy and propellant mass, between the proposed guidance strategy and a LQR controller, demonstrates the effectiveness of the method.

Modelisation et optimisation des systemes energetiques a l'aide d'algorithmes evolutifs

NASA Astrophysics Data System (ADS)

Hounkonnou, Sessinou M. William

Optimization of thermal and nuclear plant has many economics advantages as well as environmentals. Therefore new operating points research and use of new tools to achieve those kind of optimization are the subject of many studies. In this momentum, this project is intended to optimize energetic systems precisely the secondary loop of Gentilly 2 nuclear plant using both the extraction of the high and low pressure turbine as well as the extraction of the mixture coming from the steam generator. A detailed thermodynamic model of the various equipment of the secondary loop such as the feed water heaters, the moisture separator-reheater, the dearator, the condenser and the turbine is carried out. We use Matlab software (version R2007b, 2007) with the library for the thermodynamic properties of water and steam (XSteam pour Matlab, Holmgren, 2006). A model of the secondary loop is than obtained thanks to the assembly of the different equipments. A simulation of the equipment and the complete cycle enabled us to release two objectifs functions knowing as the net output and the efficiency which evolve in an opposite way according to the variation of the extractions. Due to the complexity of the problem, we use a method based on the genetic algorithms for the optimization. More precisely we used a tool which was developed at the "Institut de genie nucleaire" named BEST (Boundary Exploration Search Technique) developed in VBA* (Visual BASIC for Application) for its ability to converge more quickly and to carry out a more exhaustive search at the border of the optimal solutions. The use of the DDE (Dynamic Data Exchange) enables us to link the simulator and the optimizer. The results obtained show us that they still exists several combinations of extractions which make it possible to obtain a better point of operation for the improvement of the performance of Gentilly 2 power station secondary loop. *Trademark of Microsoft

Analysis of Aurora's Performance Simulation Engine for Three Systems

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

Freeman, Janine; Simon, Joseph

2015-07-07

Aurora Solar Inc. is building a cloud-based optimization platform to automate the design, engineering, and permit generation process of solar photovoltaic (PV) installations. They requested that the National Renewable Energy Laboratory (NREL) validate the performance of the PV system performance simulation engine of Aurora Solar’s solar design platform, Aurora. In previous work, NREL performed a validation of multiple other PV modeling tools 1, so this study builds upon that work by examining all of the same fixed-tilt systems with available module datasheets that NREL selected and used in the aforementioned study. Aurora Solar set up these three operating PV systemsmore » in their modeling platform using NREL-provided system specifications and concurrent weather data. NREL then verified the setup of these systems, ran the simulations, and compared the Aurora-predicted performance data to measured performance data for those three systems, as well as to performance data predicted by other PV modeling tools.« less

Numerically stable finite difference simulation for ultrasonic NDE in anisotropic composites

NASA Astrophysics Data System (ADS)

Leckey, Cara A. C.; Quintanilla, Francisco Hernando; Cole, Christina M.

2018-04-01

Simulation tools can enable optimized inspection of advanced materials and complex geometry structures. Recent work at NASA Langley is focused on the development of custom simulation tools for modeling ultrasonic wave behavior in composite materials. Prior work focused on the use of a standard staggered grid finite difference type of mathematical approach, by implementing a three-dimensional (3D) anisotropic Elastodynamic Finite Integration Technique (EFIT) code. However, observations showed that the anisotropic EFIT method displays numerically unstable behavior at the locations of stress-free boundaries for some cases of anisotropic materials. This paper gives examples of the numerical instabilities observed for EFIT and discusses the source of instability. As an alternative to EFIT, the 3D Lebedev Finite Difference (LFD) method has been implemented. The paper briefly describes the LFD approach and shows examples of stable behavior in the presence of stress-free boundaries for a monoclinic anisotropy case. The LFD results are also compared to experimental results and dispersion curves.

MuSim, a Graphical User Interface for Multiple Simulation Programs

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

Roberts, Thomas; Cummings, Mary Anne; Johnson, Rolland

2016-06-01

MuSim is a new user-friendly program designed to interface to many different particle simulation codes, regardless of their data formats or geometry descriptions. It presents the user with a compelling graphical user interface that includes a flexible 3-D view of the simulated world plus powerful editing and drag-and-drop capabilities. All aspects of the design can be parametrized so that parameter scans and optimizations are easy. It is simple to create plots and display events in the 3-D viewer (with a slider to vary the transparency of solids), allowing for an effortless comparison of different simulation codes. Simulation codes: G4beamline, MAD-X,more » and MCNP; more coming. Many accelerator design tools and beam optics codes were written long ago, with primitive user interfaces by today's standards. MuSim is specifically designed to make it easy to interface to such codes, providing a common user experience for all, and permitting the construction and exploration of models with very little overhead. For today's technology-driven students, graphical interfaces meet their expectations far better than text-based tools, and education in accelerator physics is one of our primary goals.« less

Using spatial principles to optimize distributed computing for enabling the physical science discoveries

PubMed Central

Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

2011-01-01

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century. PMID:21444779

Using spatial principles to optimize distributed computing for enabling the physical science discoveries.

PubMed

Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

2011-04-05

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century.

TU-EF-204-07: Add Tube Current Modulation to a Low Dose Simulation Tool for CT Systems

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

Ding, Y.; Department of Physics, University of Arizona, Tucson, AZ; Wen, G.

2015-06-15

Purpose: We extended the capabilities of a low dose simulation tool to model Tube-Current Modulation (TCM). TCM is widely used in clinical practice to reduce radiation dose in CT scans. We expect the tool to be valuable for various clinical applications (e.g., optimize protocols, compare reconstruction techniques and evaluate TCM methods). Methods: The tube current is input as a function of z location, instead of a fixed value. Starting from the line integrals of a scan, a new Poisson noise realization at a lower dose is generated for each view. To validate the new functionality, we compared simulated scans withmore » real scans in image space. Results: First we assessed noise in the difference between the low-dose simulations and the original high-dose scan. When the simulated tube current is a step function of z location, the noise at each segment matches the noise of 3 separate constant-tube-current-simulations. Secondly, with a phantom that forces TCM, we compared a low-dose simulation with an equivalent real low-dose scan. The mean CT number of the simulated scan and the real low-dose scan were 137.7±0.6 and 137.8±0.5 respectively. Furthermore, with 240 ROIs, the noise of the simulated scan and the real low-dose scan were 24.03±0.45 and 23.99±0.43 respectively, and they were not statistically different (2-sample t-test, p-value=0.28). The facts that the noise reflected the trend of the TCM curve, and that the absolute noise measurements were not statistically different validated the TCM function. Conclusion: We successfully added tube-current modulation functionality in an existing low dose simulation tool. We demonstrated that the noise reflected an input tube-current modulation curve. In addition, we verified that the noise and mean CT number of our simulation agreed with a real low dose scan. The authors are all employees of Philips. Yijun Ding is also supported by NIBIB P41EB002035 and NIBIB R01EB000803.« less

Optimization techniques applied to passive measures for in-orbit spacecraft survivability

NASA Technical Reports Server (NTRS)

Mog, Robert A.; Helba, Michael J.; Hill, Janeil B.

1992-01-01

The purpose of this research is to provide Space Station Freedom protective structures design insight through the coupling of design/material requirements, hypervelocity impact phenomenology, meteoroid and space debris environment sensitivities, optimization techniques and operations research strategies, and mission scenarios. The goals of the research are: (1) to develop a Monte Carlo simulation tool which will provide top level insight for Space Station protective structures designers; (2) to develop advanced shielding concepts relevant to Space Station Freedom using unique multiple bumper approaches; and (3) to investigate projectile shape effects on protective structures design.

Simulation of diurnal thermal energy storage systems: Preliminary results

NASA Astrophysics Data System (ADS)

Katipamula, S.; Somasundaram, S.; Williams, H. R.

1994-12-01

This report describes the results of a simulation of thermal energy storage (TES) integrated with a simple-cycle gas turbine cogeneration system. Integrating TES with cogeneration can serve the electrical and thermal loads independently while firing all fuel in the gas turbine. The detailed engineering and economic feasibility of diurnal TES systems integrated with cogeneration systems has been described in two previous PNL reports. The objective of this study was to lay the ground work for optimization of the TES system designs using a simulation tool called TRNSYS (TRaNsient SYstem Simulation). TRNSYS is a transient simulation program with a sequential-modular structure developed at the Solar Energy Laboratory, University of Wisconsin-Madison. The two TES systems selected for the base-case simulations were: (1) a one-tank storage model to represent the oil/rock TES system; and (2) a two-tank storage model to represent the molten nitrate salt TES system. Results of the study clearly indicate that an engineering optimization of the TES system using TRNSYS is possible. The one-tank stratified oil/rock storage model described here is a good starting point for parametric studies of a TES system. Further developments to the TRNSYS library of available models (economizer, evaporator, gas turbine, etc.) are recommended so that the phase-change processes is accurately treated.

Spot and Runway Departure Advisor (SARDA)

NASA Technical Reports Server (NTRS)

Jung, Yoon

2016-01-01

Spot and Runway Departure Advisor (SARDA) is a decision support tool to assist airline ramp controllers and ATC tower controllers to manage traffic on the airport surface to significantly improve efficiency and predictability in surface operations. The core function of the tool is the runway scheduler which generates an optimal solution for runway sequence and schedule of departure aircraft, which would minimize system delay and maximize runway throughput. The presentation also discusses the latest status of NASA's current surface research through a collaboration with an airline partner, where a tool is developed for airline ramp operators to assist departure pushback operations. The presentation describes the concept of the SARDA tool and results from human-in-the-loop simulations conducted in 2012 for Dallas-Ft. Worth International Airport and 2014 for Charlotte airport ramp tower.

Nonparametric variational optimization of reaction coordinates

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

Banushkina, Polina V.; Krivov, Sergei V., E-mail: s.krivov@leeds.ac.uk

State of the art realistic simulations of complex atomic processes commonly produce trajectories of large size, making the development of automated analysis tools very important. A popular approach aimed at extracting dynamical information consists of projecting these trajectories into optimally selected reaction coordinates or collective variables. For equilibrium dynamics between any two boundary states, the committor function also known as the folding probability in protein folding studies is often considered as the optimal coordinate. To determine it, one selects a functional form with many parameters and trains it on the trajectories using various criteria. A major problem with such anmore » approach is that a poor initial choice of the functional form may lead to sub-optimal results. Here, we describe an approach which allows one to optimize the reaction coordinate without selecting its functional form and thus avoiding this source of error.« less

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

PubMed Central

Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; Sirimulla, Suman; Clayton, Andrew H.A.; Hlavacek, William S.; Posner, Richard G.

2016-01-01

Summary: Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive. Availability and implementation: BioNetFit can be used on stand-alone Mac, Windows/Cygwin, and Linux platforms and on Linux-based clusters running SLURM, Torque/PBS, or SGE. The BioNetFit source code (Perl) is freely available (http://bionetfit.nau.edu). Supplementary information: Supplementary data are available at Bioinformatics online. Contact: bionetgen.help@gmail.com PMID:26556387

Designing and encoding models for synthetic biology.

PubMed

Endler, Lukas; Rodriguez, Nicolas; Juty, Nick; Chelliah, Vijayalakshmi; Laibe, Camille; Li, Chen; Le Novère, Nicolas

2009-08-06

A key component of any synthetic biology effort is the use of quantitative models. These models and their corresponding simulations allow optimization of a system design, as well as guiding their subsequent analysis. Once a domain mostly reserved for experts, dynamical modelling of gene regulatory and reaction networks has been an area of growth over the last decade. There has been a concomitant increase in the number of software tools and standards, thereby facilitating model exchange and reuse. We give here an overview of the model creation and analysis processes as well as some software tools in common use. Using markup language to encode the model and associated annotation, we describe the mining of components, their integration in relational models, formularization and parametrization. Evaluation of simulation results and validation of the model close the systems biology 'loop'.

New developments in the McStas neutron instrument simulation package

NASA Astrophysics Data System (ADS)

Willendrup, P. K.; Knudsen, E. B.; Klinkby, E.; Nielsen, T.; Farhi, E.; Filges, U.; Lefmann, K.

2014-07-01

The McStas neutron ray-tracing software package is a versatile tool for building accurate simulators of neutron scattering instruments at reactors, short- and long-pulsed spallation sources such as the European Spallation Source. McStas is extensively used for design and optimization of instruments, virtual experiments, data analysis and user training. McStas was founded as a scientific, open-source collaborative code in 1997. This contribution presents the project at its current state and gives an overview of the main new developments in McStas 2.0 (December 2012) and McStas 2.1 (expected fall 2013), including many new components, component parameter uniformisation, partial loss of backward compatibility, updated source brilliance descriptions, developments toward new tools and user interfaces, web interfaces and a new method for estimating beam losses and background from neutron optics.

Optimization of cell seeding in a 2D bio-scaffold system using computational models.

PubMed

Ho, Nicholas; Chua, Matthew; Chui, Chee-Kong

2017-05-01

The cell expansion process is a crucial part of generating cells on a large-scale level in a bioreactor system. Hence, it is important to set operating conditions (e.g. initial cell seeding distribution, culture medium flow rate) to an optimal level. Often, the initial cell seeding distribution factor is neglected and/or overlooked in the design of a bioreactor using conventional seeding distribution methods. This paper proposes a novel seeding distribution method that aims to maximize cell growth and minimize production time/cost. The proposed method utilizes two computational models; the first model represents cell growth patterns whereas the second model determines optimal initial cell seeding positions for adherent cell expansions. Cell growth simulation from the first model demonstrates that the model can be a representation of various cell types with known probabilities. The second model involves a combination of combinatorial optimization, Monte Carlo and concepts of the first model, and is used to design a multi-layer 2D bio-scaffold system that increases cell production efficiency in bioreactor applications. Simulation results have shown that the recommended input configurations obtained from the proposed optimization method are the most optimal configurations. The results have also illustrated the effectiveness of the proposed optimization method. The potential of the proposed seeding distribution method as a useful tool to optimize the cell expansion process in modern bioreactor system applications is highlighted. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling chemical vapor deposition of silicon dioxide in microreactors at atmospheric pressure

NASA Astrophysics Data System (ADS)

Konakov, S. A.; Krzhizhanovskaya, V. V.

2015-01-01

We developed a multiphysics mathematical model for simulation of silicon dioxide Chemical Vapor Deposition (CVD) from tetraethyl orthosilicate (TEOS) and oxygen mixture in a microreactor at atmospheric pressure. Microfluidics is a promising technology with numerous applications in chemical synthesis due to its high heat and mass transfer efficiency and well-controlled flow parameters. Experimental studies of CVD microreactor technology are slow and expensive. Analytical solution of the governing equations is impossible due to the complexity of intertwined non-linear physical and chemical processes. Computer simulation is the most effective tool for design and optimization of microreactors. Our computational fluid dynamics model employs mass, momentum and energy balance equations for a laminar transient flow of a chemically reacting gas mixture at low Reynolds number. Simulation results show the influence of microreactor configuration and process parameters on SiO2 deposition rate and uniformity. We simulated three microreactors with the central channel diameter of 5, 10, 20 micrometers, varying gas flow rate in the range of 5-100 microliters per hour and temperature in the range of 300-800 °C. For each microchannel diameter we found an optimal set of process parameters providing the best quality of deposited material. The model will be used for optimization of the microreactor configuration and technological parameters to facilitate the experimental stage of this research.

Planning, Implementation and Optimization of Future space Missions using an Immersive Visualization Environement (IVE) Machine

NASA Astrophysics Data System (ADS)

Harris, E.

Planning, Implementation and Optimization of Future Space Missions using an Immersive Visualization Environment (IVE) Machine E. N. Harris, Lockheed Martin Space Systems, Denver, CO and George.W. Morgenthaler, U. of Colorado at Boulder History: A team of 3-D engineering visualization experts at the Lockheed Martin Space Systems Company have developed innovative virtual prototyping simulation solutions for ground processing and real-time visualization of design and planning of aerospace missions over the past 6 years. At the University of Colorado, a team of 3-D visualization experts are developing the science of 3-D visualization and immersive visualization at the newly founded BP Center for Visualization, which began operations in October, 2001. (See IAF/IAA-01-13.2.09, "The Use of 3-D Immersive Visualization Environments (IVEs) to Plan Space Missions," G. A. Dorn and G. W. Morgenthaler.) Progressing from Today's 3-D Engineering Simulations to Tomorrow's 3-D IVE Mission Planning, Simulation and Optimization Techniques: 3-D (IVEs) and visualization simulation tools can be combined for efficient planning and design engineering of future aerospace exploration and commercial missions. This technology is currently being developed and will be demonstrated by Lockheed Martin in the (IVE) at the BP Center using virtual simulation for clearance checks, collision detection, ergonomics and reach-ability analyses to develop fabrication and processing flows for spacecraft and launch vehicle ground support operations and to optimize mission architecture and vehicle design subject to realistic constraints. Demonstrations: Immediate aerospace applications to be demonstrated include developing streamlined processing flows for Reusable Space Transportation Systems and Atlas Launch Vehicle operations and Mars Polar Lander visual work instructions. Long-range goals include future international human and robotic space exploration missions such as the development of a Mars Reconnaissance Orbiter and Lunar Base construction scenarios. Innovative solutions utilizing Immersive Visualization provide the key to streamlining the mission planning and optimizing engineering design phases of future aerospace missions.

Method for decreasing CT simulation time of complex phantoms and systems through separation of material specific projection data

NASA Astrophysics Data System (ADS)

Divel, Sarah E.; Christensen, Soren; Wintermark, Max; Lansberg, Maarten G.; Pelc, Norbert J.

2017-03-01

Computer simulation is a powerful tool in CT; however, long simulation times of complex phantoms and systems, especially when modeling many physical aspects (e.g., spectrum, finite detector and source size), hinder the ability to realistically and efficiently evaluate and optimize CT techniques. Long simulation times primarily result from the tracing of hundreds of line integrals through each of the hundreds of geometrical shapes defined within the phantom. However, when the goal is to perform dynamic simulations or test many scan protocols using a particular phantom, traditional simulation methods inefficiently and repeatedly calculate line integrals through the same set of structures although only a few parameters change in each new case. In this work, we have developed a new simulation framework that overcomes such inefficiencies by dividing the phantom into material specific regions with the same time attenuation profiles, acquiring and storing monoenergetic projections of the regions, and subsequently scaling and combining the projections to create equivalent polyenergetic sinograms. The simulation framework is especially efficient for the validation and optimization of CT perfusion which requires analysis of many stroke cases and testing hundreds of scan protocols on a realistic and complex numerical brain phantom. Using this updated framework to conduct a 31-time point simulation with 80 mm of z-coverage of a brain phantom on two 16-core Linux serves, we have reduced the simulation time from 62 hours to under 2.6 hours, a 95% reduction.

Future missions for observing Earth's changing gravity field: a closed-loop simulation tool

NASA Astrophysics Data System (ADS)

Visser, P. N.

2008-12-01

The GRACE mission has successfully demonstrated the observation from space of the changing Earth's gravity field at length and time scales of typically 1000 km and 10-30 days, respectively. Many scientific communities strongly advertise the need for continuity of observing Earth's gravity field from space. Moreover, a strong interest is being expressed to have gravity missions that allow a more detailed sampling of the Earth's gravity field both in time and in space. Designing a gravity field mission for the future is a complicated process that involves making many trade-offs, such as trade-offs between spatial, temporal resolution and financial budget. Moreover, it involves the optimization of many parameters, such as orbital parameters (height, inclination), distinction between which gravity sources to observe or correct for (for example are gravity changes due to ocean currents a nuisance or a signal to be retrieved?), observation techniques (low-low satellite-to-satellite tracking, satellite gravity gradiometry, accelerometers), and satellite control systems (drag-free?). A comprehensive tool has been developed and implemented that allows the closed-loop simulation of gravity field retrievals for different satellite mission scenarios. This paper provides a description of this tool. Moreover, its capabilities are demonstrated by a few case studies. Acknowledgments. The research that is being done with the closed-loop simulation tool is partially funded by the European Space Agency (ESA). An important component of the tool is the GEODYN software, kindly provided by NASA Goddard Space Flight Center in Greenbelt, Maryland.

Managing and learning with multiple models: Objectives and optimization algorithms

USGS Publications Warehouse

Probert, William J. M.; Hauser, C.E.; McDonald-Madden, E.; Runge, M.C.; Baxter, P.W.J.; Possingham, H.P.

2011-01-01

The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. ?? 2010 Elsevier Ltd.

Simulation based planning of surgical interventions in pediatric cardiology

NASA Astrophysics Data System (ADS)

Marsden, Alison L.

2013-10-01

Hemodynamics plays an essential role in the progression and treatment of cardiovascular disease. However, while medical imaging provides increasingly detailed anatomical information, clinicians often have limited access to hemodynamic data that may be crucial to patient risk assessment and treatment planning. Computational simulations can now provide detailed hemodynamic data to augment clinical knowledge in both adult and pediatric applications. There is a particular need for simulation tools in pediatric cardiology, due to the wide variation in anatomy and physiology in congenital heart disease patients, necessitating individualized treatment plans. Despite great strides in medical imaging, enabling extraction of flow information from magnetic resonance and ultrasound imaging, simulations offer predictive capabilities that imaging alone cannot provide. Patient specific simulations can be used for in silico testing of new surgical designs, treatment planning, device testing, and patient risk stratification. Furthermore, simulations can be performed at no direct risk to the patient. In this paper, we outline the current state of the art in methods for cardiovascular blood flow simulation and virtual surgery. We then step through pressing challenges in the field, including multiscale modeling, boundary condition selection, optimization, and uncertainty quantification. Finally, we summarize simulation results of two representative examples from pediatric cardiology: single ventricle physiology, and coronary aneurysms caused by Kawasaki disease. These examples illustrate the potential impact of computational modeling tools in the clinical setting.

Optimization methods applied to hybrid vehicle design

NASA Technical Reports Server (NTRS)

Donoghue, J. F.; Burghart, J. H.

1983-01-01

The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.

Optimization of illumination schemes in a head-mounted display integrated with eye tracking capabilities

NASA Astrophysics Data System (ADS)

Pansing, Craig W.; Hua, Hong; Rolland, Jannick P.

2005-08-01

Head-mounted display (HMD) technologies find a variety of applications in the field of 3D virtual and augmented environments, 3D scientific visualization, as well as wearable displays. While most of the current HMDs use head pose to approximate line of sight, we propose to investigate approaches and designs for integrating eye tracking capability into HMDs from a low-level system design perspective and to explore schemes for optimizing system performance. In this paper, we particularly propose to optimize the illumination scheme, which is a critical component in designing an eye tracking-HMD (ET-HMD) integrated system. An optimal design can improve not only eye tracking accuracy, but also robustness. Using LightTools, we present the simulation of a complete eye illumination and imaging system using an eye model along with multiple near infrared LED (IRLED) illuminators and imaging optics, showing the irradiance variation of the different eye structures. The simulation of dark pupil effects along with multiple 1st-order Purkinje images will be presented. A parametric analysis is performed to investigate the relationships between the IRLED configurations and the irradiance distribution at the eye, and a set of optimal configuration parameters is recommended. The analysis will be further refined by actual eye image acquisition and processing.

Method optimization for drug impurity profiling in supercritical fluid chromatography: Application to a pharmaceutical mixture.

PubMed

Muscat Galea, Charlene; Didion, David; Clicq, David; Mangelings, Debby; Vander Heyden, Yvan

2017-12-01

A supercritical chromatographic method for the separation of a drug and its impurities has been developed and optimized applying an experimental design approach and chromatogram simulations. Stationary phase screening was followed by optimization of the modifier and injection solvent composition. A design-of-experiment (DoE) approach was then used to optimize column temperature, back-pressure and the gradient slope simultaneously. Regression models for the retention times and peak widths of all mixture components were built. The factor levels for different grid points were then used to predict the retention times and peak widths of the mixture components using the regression models and the best separation for the worst separated peak pair in the experimental domain was identified. A plot of the minimal resolutions was used to help identifying the factor levels leading to the highest resolution between consecutive peaks. The effects of the DoE factors were visualized in a way that is familiar to the analytical chemist, i.e. by simulating the resulting chromatogram. The mixture of an active ingredient and seven impurities was separated in less than eight minutes. The approach discussed in this paper demonstrates how SFC methods can be developed and optimized efficiently using simple concepts and tools. Copyright © 2017 Elsevier B.V. All rights reserved.

Simulating a Measurement of the 2nd Knee in the Cosmic Ray Spectrum with an Atmospheric Fluorescence Telescope Tower Array

PubMed Central

Liu, Jiali; Yang, Qunyu; Bai, Yunxiang; Cao, Zhen

2014-01-01

A fluorescence telescope tower array has been designed to measure cosmic rays in the energy range of 1017–1018 eV. A full Monte Carlo simulation, including air shower production, light generation and propagation, detector response, electronics, and trigger system, has been developed for that purpose. Using such a simulation tool, the detector configuration, which includes one main tower array and two side-trigger arrays, 24 telescopes in total, has been optimized. The aperture and the event rate have been estimated. Furthermore, the performance of the X max⁡ technique in measuring composition has also been studied. PMID:24737964

Power System Simulations For The Globalstar2 Mission Using The PowerCap Software

NASA Astrophysics Data System (ADS)

Defoug, S.; Pin, R.

2011-10-01

The Globalstar system aims to enable customers to communicate all around the world thanks to its constellation of 48 LEO satellites. Thales Alenia Space is in charge of the design and manufacturing of the second generation of the Globalstar satellites. For such a long duration mission (15 years) and with a payload power consumption varying incessantly, the optimization of the solar arrays and battery has to be consolidated by an accurate power simulation tool. After a general overview of the Globalstar power system and of the PowerCap software, this paper presents the dedicated version elaborated for the GlobalStar2 mission, the simulations results and their correlation with the tests.

Development of a Platform for Simulating and Optimizing Thermoelectric Energy Systems

NASA Astrophysics Data System (ADS)

Kreuder, John J.

Thermoelectrics are solid state devices that can convert thermal energy directly into electrical energy. They have historically been used only in niche applications because of their relatively low efficiencies. With the advent of nanotechnology and improved manufacturing processes thermoelectric materials have become less costly and more efficient As next generation thermoelectric materials become available there is a need for industries to quickly and cost effectively seek out feasible applications for thermoelectric heat recovery platforms. Determining the technical and economic feasibility of such systems requires a model that predicts performance at the system level. Current models focus on specific system applications or neglect the rest of the system altogether, focusing on only module design and not an entire energy system. To assist in screening and optimizing entire energy systems using thermoelectrics, a novel software tool, Thermoelectric Power System Simulator (TEPSS), is developed for system level simulation and optimization of heat recovery systems. The platform is designed for use with a generic energy system so that most types of thermoelectric heat recovery applications can be modeled. TEPSS is based on object-oriented programming in MATLABRTM. A modular, shell based architecture is developed to carry out concept generation, system simulation and optimization. Systems are defined according to the components and interconnectivity specified by the user. An iterative solution process based on Newton's Method is employed to determine the system's steady state so that an objective function representing the cost of the system can be evaluated at the operating point. An optimization algorithm from MATLAB's Optimization Toolbox uses sequential quadratic programming to minimize this objective function with respect to a set of user specified design variables and constraints. During this iterative process many independent system simulations are executed and the optimal operating condition of the system is determined. A comprehensive guide to using the software platform is included. TEPSS is intended to be expandable so that users can add new types of components and implement component models with an adequate degree of complexity for a required application. Special steps are taken to ensure that the system of nonlinear algebraic equations presented in the system engineering model is square and that all equations are independent. In addition, the third party program FluidProp is leveraged to allow for simulations of systems with a range of fluids. Sequential unconstrained minimization techniques are used to prevent physical variables like pressure and temperature from trending to infinity during optimization. Two case studies are performed to verify and demonstrate the simulation and optimization routines employed by TEPSS. The first is of a simple combined cycle in which the size of the heat exchanger and fuel rate are optimized. The second case study is the optimization of geometric parameters of a thermoelectric heat recovery platform in a regenerative Brayton Cycle. A basic package of components and interconnections are verified and provided as well.

Evacuation simulation using Hybrid Space Discretisation and Application to Large Underground Rail Tunnel Station

NASA Astrophysics Data System (ADS)

Chooramun, N.; Lawrence, P. J.; Galea, E. R.

2017-08-01

In all evacuation simulation tools, the space through which agents navigate and interact is represented by one the following methods, namely Coarse regions, Fine nodes and Continuous regions. Each of the spatial representation methods has its benefits and limitations. For instance, the Coarse approach allows simulations to be processed very rapidly, but is unable to represent the interactions of the agents from an individual perspective; the Continuous approach provides a detailed representation of agent movement and interaction but suffers from relatively poor computational performance. The Fine nodal approach presents a compromise between the Continuous and Coarse approaches such that it allows agent interaction to be modelled while providing good computational performance. Our approach for representing space in an evacuation simulation tool differs such that it allows evacuation simulations to be run using a combination of Coarse regions, Fine nodes and Continuous regions. This approach, which we call Hybrid Spatial Discretisation (HSD), is implemented within the buildingEXODUS evacuation simulation software. The HSD incorporates the benefits of each of the spatial representation methods whilst providing an optimal environment for representing agent movement and interaction. In this work, we demonstrate the effectiveness of the HSD through its application to a moderately large case comprising of an underground rail tunnel station with a population of 2,000 agents.

Ionospheric Simulation System for Satellite Observations and Global Assimilative Modeling Experiments (ISOGAME)

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Mannucci, Anthony J.; Verkhoglyadova, Olga P.; Stephens, Philip; Wilson, Brian D.; Akopian, Vardan; Komjathy, Attila; Lijima, Byron A.

2013-01-01

ISOGAME is designed and developed to assess quantitatively the impact of new observation systems on the capability of imaging and modeling the ionosphere. With ISOGAME, one can perform observation system simulation experiments (OSSEs). A typical OSSE using ISOGAME would involve: (1) simulating various ionospheric conditions on global scales; (2) simulating ionospheric measurements made from a constellation of low-Earth-orbiters (LEOs), particularly Global Navigation Satellite System (GNSS) radio occultation data, and from ground-based global GNSS networks; (3) conducting ionospheric data assimilation experiments with the Global Assimilative Ionospheric Model (GAIM); and (4) analyzing modeling results with visualization tools. ISOGAME can provide quantitative assessment of the accuracy of assimilative modeling with the interested observation system. Other observation systems besides those based on GNSS are also possible to analyze. The system is composed of a suite of software that combines the GAIM, including a 4D first-principles ionospheric model and data assimilation modules, an Internal Reference Ionosphere (IRI) model that has been developed by international ionospheric research communities, observation simulator, visualization software, and orbit design, simulation, and optimization software. The core GAIM model used in ISOGAME is based on the GAIM++ code (written in C++) that includes a new high-fidelity geomagnetic field representation (multi-dipole). New visualization tools and analysis algorithms for the OSSEs are now part of ISOGAME.

Effect of resection depth of early glottic cancer on vocal outcome: An optimized finite element simulation

PubMed Central

Mau, Ted; Palaparthi, Anil; Riede, Tobias; Titze, Ingo R.

2015-01-01

Objectives/Hypothesis To test the hypothesis that subligamental cordectomy produces superior acoustic outcome than subepithelial cordectomy for early (T1-2) glottic cancer that requires complete removal of the superficial lamina propria but does not involve the vocal ligament. Study Design Computer simulation Methods A computational tool for vocal fold surgical planning and simulation (the National Center for Voice and Speech Phonosurgery Optimizer-Simulator) was used to evaluate the acoustic output of alternative vocal fold morphologies. Four morphologies were simulated: normal, subepithelial cordectomy, subligamental cordectomy, and transligamental cordectomy (partial ligament resection). The primary outcome measure was the range of fundamental frequency (F0) and sound pressure level (SPL). A more restricted F0-SPL range was considered less favorable because of reduced acoustic possibilities given the same range of driving subglottic pressure and identical vocal fold posturing. Results Subligamental cordectomy generated solutions covering an F0-SPL range 82% of normal for a rectangular vocal fold. In contrast, transligamental and subepithelial cordectomies produced significantly smaller F0-SPL ranges, 57% and 19% of normal, respectively. Conclusion This study illustrates the use of the Phonosurgery Optimizer-Simulator to test a specific hypothesis regarding the merits of two surgical alternatives. These simulation results provide theoretical support for vocal ligament excision with maximum muscle preservation when superficial lamina propria resection is necessary but the vocal ligament can be spared on oncological grounds. The resection of more tissue may paradoxically allow the eventual recovery of a better speaking voice, assuming glottal width is restored. Application of this conclusion to surgical practice will require confirmatory clinical data. PMID:26010240

Optimization for energy efficiency of underground building envelope thermal performance in different climate zones of China

NASA Astrophysics Data System (ADS)

Shi, Luyang; Liu, Jing; Zhang, Huibo

2017-11-01

The object of this article is to investigate the influence of thermal performance of envelopes in shallow-buried buildings on energy consumption for different climate zones of China. For the purpose of this study, an effective building energy simulation tool (DeST) developed by Tsinghua University was chosen to model the heat transfer in underground buildings. Based on the simulative results, energy consumption for heating and cooling for the whole year was obtained. The results showed that the relationship between energy consumption and U-value of envelopes for underground buildings is different compared with above-ground buildings: improving thermal performance of exterior walls cannot reduce energy consumption, on the contrary, may result in more energy cost. Besides, it is can be derived that optimized U-values of underground building envelopes vary with climate zones of China in this study. For severe cold climate zone, the optimized U-value of underground building envelopes is 0.8W/(m2·K); for cold climate zone, the optimized U-value is 1.5W/(m2·K); for warm climate zone, the U-value is 2.0W/(m2·K).

Design-Based Comparison of Spine Surgery Simulators: Optimizing Educational Features of Surgical Simulators.

PubMed

Ryu, Won Hyung A; Mostafa, Ahmed E; Dharampal, Navjit; Sharlin, Ehud; Kopp, Gail; Jacobs, W Bradley; Hurlbert, R John; Chan, Sonny; Sutherland, Garnette R

2017-10-01

Simulation-based education has made its entry into surgical residency training, particularly as an adjunct to hands-on clinical experience. However, one of the ongoing challenges to wide adoption is the capacity of simulators to incorporate educational features required for effective learning. The aim of this study was to identify strengths and limitations of spine simulators to characterize design elements that are essential in enhancing resident education. We performed a mixed qualitative and quantitative cohort study with a focused survey and interviews of stakeholders in spine surgery pertaining to their experiences on 3 spine simulators. Ten participants were recruited spanning all levels of training and expertise until qualitative analysis reached saturation of themes. Participants were asked to perform lumbar pedicle screw insertion on 3 simulators. Afterward, a 10-item survey was administrated and a focused interview was conducted to explore topics pertaining to the design features of the simulators. Overall impressions of the simulators were positive with regards to their educational benefit, but our qualitative analysis revealed differing strengths and limitations. Main design strengths of the computer-based simulators were incorporation of procedural guidance and provision of performance feedback. The synthetic model excelled in achieving more realistic haptic feedback and incorporating use of actual surgical tools. Stakeholders from trainees to experts acknowledge the growing role of simulation-based education in spine surgery. However, different simulation modalities have varying design elements that augment learning in distinct ways. Characterization of these design characteristics will allow for standardization of simulation curricula in spinal surgery, optimizing educational benefit. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimization of Equation of State and Burn Model Parameters for Explosives

NASA Astrophysics Data System (ADS)

Bergh, Magnus; Wedberg, Rasmus; Lundgren, Jonas

2017-06-01

A reactive burn model implemented in a multi-dimensional hydrocode can be a powerful tool for predicting non-ideal effects as well as initiation phenomena in explosives. Calibration against experiment is, however, critical and non-trivial. Here, a procedure is presented for calibrating the Ignition and Growth Model utilizing hydrocode simulation in conjunction with the optimization program LS-OPT. The model is applied to the explosive PBXN-109. First, a cylinder expansion test is presented together with a new automatic routine for product equation of state calibration. Secondly, rate stick tests and instrumented gap tests are presented. Data from these experiments are used to calibrate burn model parameters. Finally, we discuss the applicability and development of this optimization routine.

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

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

He, Xu; Tuo, Rui; Jeff Wu, C. F.

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

DOE PAGES

He, Xu; Tuo, Rui; Jeff Wu, C. F.

2017-01-31

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

The perceived value of using BIM for energy simulation

NASA Astrophysics Data System (ADS)

Lewis, Anderson M.

Building Information Modeling (BIM) is becoming an increasingly important tool in the Architectural, Engineering & Construction (AEC) industries. Some of the benefits associated with BIM include but are not limited to cost and time savings through greater trade and design coordination, and more accurate estimating take-offs. BIM is a virtual 3D, parametric design software that allows users to store information of a model within and can be used as a communication platform between project stakeholders. Likewise, energy simulation is an integral tool for predicting and optimizing a building's performance during design. Creating energy models and running energy simulations can be a time consuming activity due to the large number of parameters and assumptions that must be addressed to achieve reasonably accurate results. However, leveraging information imbedded within Building Information Models (BIMs) has the potential to increase accuracy and reduce the amount of time required to run energy simulations and can facilitate continuous energy simulations throughout the design process, thus optimizing building performance. Although some literature exists on how design stakeholders perceive the benefits associated with leveraging BIM for energy simulation, little is known about how perceptions associated with leveraging BIM for energy simulation differ between various green design stakeholder user groups. Through an e-survey instrument, this study seeks to determine how perceptions of using BIMs to inform energy simulation differ among distinct design stakeholder groups, which include BIM-only users, energy simulation-only users and BIM and energy simulation users. Additionally, this study seeks to determine what design stakeholders perceive as the main barriers and benefits of implementing BIM-based energy simulation. Results from this study suggest that little to no correlation exists between green design stakeholders' perceptions of the value associated with using information from BIMs to inform energy simulation and their engagement level with BIM and/or energy simulation. However, green design stakeholder perceptions of the value associated with using information from BIMs to inform energy simulation and their engagement with BIM and/or energy simulation may differ between different user groups (i.e. BIM users only, energy simulation users only, and BIM and energy simulation users). For example, the BIM-only user groups appeared to have a strong positive correlation between the perceptions of the value associated with using information from BIMs to inform energy simulation and their engagement with BIM. Additionally, this study suggests that the top perceived benefits of using BIMs to inform energy simulations among green design stakeholders are: facilitation of communication, reducing of process related costs, and giving users the ability examine more design options. The main perceived barrier of using BIMs to inform energy simulations among green design stakeholders was a lack of BIM standards for model integration with multidisciplinary teams. Results from this study will help readers understand how to better implement BIM-based energy simulation while mitigating barriers and optimizing benefits. Additionally, examining discrepancies between user groups can lead the identification and improvement of shortfalls in current BIM-based energy simulation processes. Understanding how perceptions and engagement levels differ among different software user groups will help in developing a strategies for implementing BIM-based energy simulation that are tailored to each specific user group.

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

Flory, John Andrew; Padilla, Denise D.; Gauthier, John H.

Upcoming weapon programs require an aggressive increase in Application Specific Integrated Circuit (ASIC) production at Sandia National Laboratories (SNL). SNL has developed unique modeling and optimization tools that have been instrumental in improving ASIC production productivity and efficiency, identifying optimal operational and tactical execution plans under resource constraints, and providing confidence in successful mission execution. With ten products and unprecedented levels of demand, a single set of shared resources, highly variable processes, and the need for external supplier task synchronization, scheduling is an integral part of successful manufacturing. The scheduler uses an iterative multi-objective genetic algorithm and a multi-dimensional performancemore » evaluator. Schedule feasibility is assessed using a discrete event simulation (DES) that incorporates operational uncertainty, variability, and resource availability. The tools provide rapid scenario assessments and responses to variances in the operational environment, and have been used to inform major equipment investments and workforce planning decisions in multiple SNL facilities.« less

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

TU-EF-304-03: 4D Monte Carlo Robustness Test for Proton Therapy

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

Souris, K; Sterpin, E; Lee, J

Purpose: Breathing motion and approximate dose calculation engines may increase proton range uncertainties. We address these two issues using a comprehensive 4D robustness evaluation tool based on an efficient Monte Carlo (MC) engine, which can simulate breathing with no significant increase in computation time. Methods: To assess the robustness of the treatment plan, multiple scenarios of uncertainties are simulated, taking into account the systematic and random setup errors, range uncertainties, and organ motion. Our fast MC dose engine, called MCsquare, implements optimized models on a massively-parallel computation architecture and allows us to accurately simulate a scenario in less than onemore » minute. The deviations of the uncertainty scenarios are then reported on a DVH-band and compared to the nominal plan.The robustness evaluation tool is illustrated in a lung case by comparing three 60Gy treatment plans. First, a plan is optimized on a PTV obtained by extending the CTV with an 8mm margin, in order to take into account systematic geometrical uncertainties, like in our current practice in radiotherapy. No specific strategy is employed to correct for tumor and organ motions. The second plan involves a PTV generated from the ITV, which encompasses the tumor volume in all breathing phases. The last plan results from robust optimization performed on the ITV, with robustness parameters of 3% for tissue density and 8 mm for positioning errors. Results: The robustness test revealed that the first two plans could not properly cover the target in the presence of uncertainties. CTV-coverage (D95) in the three plans ranged respectively between 39.4–55.5Gy, 50.2–57.5Gy, and 55.1–58.6Gy. Conclusion: A realistic robustness verification tool based on a fast MC dose engine has been developed. This test is essential to assess the quality of proton therapy plan and very useful to study various planning strategies for mobile tumors. This work is partly funded by IBA (Louvain-la-Neuve, Belgium)« less

INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING

PubMed Central

Kibira, Deogratias; Hatim, Qais; Kumara, Soundar; Shao, Guodong

2017-01-01

Modern manufacturing systems are installed with smart devices such as sensors that monitor system performance and collect data to manage uncertainties in their operations. However, multiple parameters and variables affect system performance, making it impossible for a human to make informed decisions without systematic methodologies and tools. Further, the large volume and variety of streaming data collected is beyond simulation analysis alone. Simulation models are run with well-prepared data. Novel approaches, combining different methods, are needed to use this data for making guided decisions. This paper proposes a methodology whereby parameters that most affect system performance are extracted from the data using data analytics methods. These parameters are used to develop scenarios for simulation inputs; system optimizations are performed on simulation data outputs. A case study of a machine shop demonstrates the proposed methodology. This paper also reviews candidate standards for data collection, simulation, and systems interfaces. PMID:28690363

Teaching and assessing procedural skills using simulation: metrics and methodology.

PubMed

Lammers, Richard L; Davenport, Moira; Korley, Frederick; Griswold-Theodorson, Sharon; Fitch, Michael T; Narang, Aneesh T; Evans, Leigh V; Gross, Amy; Rodriguez, Elliot; Dodge, Kelly L; Hamann, Cara J; Robey, Walter C

2008-11-01

Simulation allows educators to develop learner-focused training and outcomes-based assessments. However, the effectiveness and validity of simulation-based training in emergency medicine (EM) requires further investigation. Teaching and testing technical skills require methods and assessment instruments that are somewhat different than those used for cognitive or team skills. Drawing from work published by other medical disciplines as well as educational, behavioral, and human factors research, the authors developed six research themes: measurement of procedural skills; development of performance standards; assessment and validation of training methods, simulator models, and assessment tools; optimization of training methods; transfer of skills learned on simulator models to patients; and prevention of skill decay over time. The article reviews relevant and established educational research methodologies and identifies gaps in our knowledge of how physicians learn procedures. The authors present questions requiring further research that, once answered, will advance understanding of simulation-based procedural training and assessment in EM.

Towards Automatic Processing of Virtual City Models for Simulations

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Building complex simulations rapidly using MATRIX(x): The Space Station redesign

NASA Technical Reports Server (NTRS)

Carrington, C. K.

1994-01-01

MSFC's quick response to the Space Station redesign effort last year required the development of a computer simulation to model the attitude and station-keeping dynamics of a complex body with rotating solar arrays in orbit around the Earth. The simulation was written using a rapid-prototyping graphical simulation and design tool called MATRIX(x) and provided the capability to quickly remodel complex configuration changes by icon manipulation using a mouse. The simulation determines time-dependent inertia properties, and models forces and torques from gravity-gradient, solar radiation, and aerodynamic disturbances. Surface models are easily built from a selection of beams, plates, tetrahedrons, and cylinders. An optimization scheme was written to determine the torque equilibrium attitudes that balance gravity-gradient and aerodynamic torques over an orbit, and propellant-usage estimates were determined. The simulation has been adapted to model the attitude dynamics for small spacecraft.

Standing wave design and optimization of a simulated moving bed chromatography for separation of xylobiose and xylose under the constraints on product concentration and pressure drop.

PubMed

Lee, Chung-Gi; Choi, Jae-Hwan; Park, Chanhun; Wang, Nien-Hwa Linda; Mun, Sungyong

2017-12-08

The feasibility of a simulated moving bed (SMB) technology for the continuous separation of high-purity xylobiose (X2) from the output of a β-xylosidase X1→X2 reaction has recently been confirmed. To ensure high economical efficiency of the X2 production method based on the use of xylose (X1) as a starting material, it is essential to accomplish the comprehensive optimization of the X2-separation SMB process in such a way that its X2 productivity can be maximized while maintaining the X2 product concentration from the SMB as high as possible in consideration of a subsequent lyophilization step. To address this issue, a suitable SMB optimization tool for the aforementioned task was prepared based on standing wave design theory. The prepared tool was then used to optimize the SMB operation parameters, column configuration, total column number, adsorbent particle size, and X2 yield while meeting the constraints on X2 purity, X2 product concentration, and pressure drop. The results showed that the use of a larger particle size caused the productivity to be limited by the constraint on X2 product concentration, and a maximum productivity was attained by choosing the particle size such that the effect of the X2-concentration limiting factor could be balanced with that of pressure-drop limiting factor. If the target level of X2 product concentration was elevated, higher productivity could be achieved by decreasing particle size, raising the level of X2 yield, and increasing the column number in the zones containing the front and rear of X2 solute band. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimal allocation in annual plants and its implications for drought response

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Smith, Matthew; Purves, Drew

2015-04-01

The concept of plant optimality refers to the plastic behaviour of plants that results in lifetime and offspring fitness. Optimality concepts have been used in vegetation models for a variety of processes, including stomatal conductance, leaf phenology and biomass allocation. Including optimality in vegetation models has the advantages of creating process based models with a relatively low complexity in terms of parameter numbers but which are capable of reproducing complex plant behaviour. We present a general model of plant growth for annual plants based on the hypothesis that plants allocate biomass to aboveground and belowground vegetative organs in order to maintain an optimal C:N ratio. The model also represents reproductive growth through a second optimality criteria, which states that plants flower when they reach peak nitrogen uptake. We apply this model to wheat and maize crops at 15 locations corresponding to FLUXNET cropland sites. The model parameters are data constrained using a Bayesian fitting algorithm to eddy covariance data, satellite derived vegetation indices, specifically the MODIS fAPAR product and field level crop yield data. We use the model to simulate the plant drought response under the assumption of plant optimality and show that the plants maintain unstressed total biomass levels under drought for a reduction in precipitation of up to 40%. Beyond that level plant response stops being plastic and growth decreases sharply. This behaviour results simply from the optimal allocation criteria as the model includes no explicit drought sensitivity component. Models that use plant optimality concepts are a useful tool for simulation plant response to stress without the addition of artificial thresholds and parameters.

Leaders by example: Best practices and advice on establishing a state-of-the art surgical simulation center that optimizes available resources.

PubMed

Gardner, A K; Ritter, E M; Dunkin, B J; Smink, D S; Lau, J N; Paige, J T; Phitayakorn, R; Acton, R D; Stefanidis, D; Gee, D W

2018-02-01

The role of simulation-based education continues to expand exponentially. To excel in this environment as a surgical simulation leader requires unique knowledge, skills, and abilities that are different from those used in traditional clinically-based education. Leaders in surgical simulation were invited to participate as discussants in a pre-conference course offered by the Association for Surgical Education. Highlights from their discussions were recorded. Recommendations were provided on topics such as building a simulation team, preparing for accreditation requirements, what to ask for during early stages of development, identifying tools and resources needed to meet educational goals, expanding surgical simulation programming, and building educational curricula. These recommendations provide new leaders in simulation with a unique combination of up-to-date best practices in simulation-based education, as well as valuable advice gained from lessons learned from the personal experiences of national leaders in the field of surgical simulation and education. Copyright © 2017 Elsevier Inc. All rights reserved.

The role of simulation in continuing medical education for acute care physicians: a systematic review.

PubMed

Khanduja, P Kristina; Bould, M Dylan; Naik, Viren N; Hladkowicz, Emily; Boet, Sylvain

2015-01-01

We systematically reviewed the effectiveness of simulation-based education, targeting independently practicing qualified physicians in acute care specialties. We also describe how simulation is used for performance assessment in this population. Data source included: DataMEDLINE, Embase, Cochrane Database of Systematic Reviews, Cochrane CENTRAL Database of Controlled Trials, and National Health Service Economic Evaluation Database. The last date of search was January 31, 2013. All original research describing simulation-based education for independently practicing physicians in anesthesiology, critical care, and emergency medicine was reviewed. Data analysis was performed in duplicate with further review by a third author in cases of disagreement until consensus was reached. Data extraction was focused on effectiveness according to Kirkpatrick's model. For simulation-based performance assessment, tool characteristics and sources of validity evidence were also collated. Of 39 studies identified, 30 studies focused on the effectiveness of simulation-based education and nine studies evaluated the validity of simulation-based assessment. Thirteen studies (30%) targeted the lower levels of Kirkpatrick's hierarchy with reliance on self-reporting. Simulation was unanimously described as a positive learning experience with perceived impact on clinical practice. Of the 17 remaining studies, 10 used a single group or "no intervention comparison group" design. The majority (n = 17; 44%) were able to demonstrate both immediate and sustained improvements in educational outcomes. Nine studies reported the psychometric properties of simulation-based performance assessment as their sole objective. These predominantly recruited independent practitioners as a convenience sample to establish whether the tool could discriminate between experienced and inexperienced operators and concentrated on a single aspect of validity evidence. Simulation is perceived as a positive learning experience with limited evidence to support improved learning. Future research should focus on the optimal modality and frequency of exposure, quality of assessment tools and on the impact of simulation-based education beyond the individuals toward improved patient care.

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.

Optimization of Gate, Runner and Sprue in Two-Plate Family Plastic Injection Mould

NASA Astrophysics Data System (ADS)

Amran, M. A.; Hadzley, M.; Amri, S.; Izamshah, R.; Hassan, A.; Samsi, S.; Shahir, K.

2010-03-01

This paper describes the optimization size of gate, runner and sprue in two-plate family plastic injection mould. An Electronic Cash Register (ECR) plastic product was used in this study, which there are three components in electronic cast register plastic product consist of top casing, bottom casing and paper holder. The objectives of this paper are to find out the optimum size of gate, runner and sprue, to locate the optimum layout of cavities and to recognize the defect problems due to the wrong size of gate, runner and sprue. Three types of software were used in this study, which Unigraphics software as CAD tool was used to design 3D modeling, Rhinoceros software as post processing tool was used to design gate, runner and sprue and Moldex software as simulation tool was used to analyze the plastic flow. As result, some modifications were made on size of feeding system and location of cavity to eliminate the short- shot, over filling and welding line problems in two-plate family plastic injection mould.

Application of an improved minimum entropy deconvolution method for railway rolling element bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Yao; Zhou, Ning; Zhang, Weihua; Wang, Zhiwei

2018-07-01

Minimum entropy deconvolution is a widely-used tool in machinery fault diagnosis, because it enhances the impulse component of the signal. The filter coefficients that greatly influence the performance of the minimum entropy deconvolution are calculated by an iterative procedure. This paper proposes an improved deconvolution method for the fault detection of rolling element bearings. The proposed method solves the filter coefficients by the standard particle swarm optimization algorithm, assisted by a generalized spherical coordinate transformation. When optimizing the filters performance for enhancing the impulses in fault diagnosis (namely, faulty rolling element bearings), the proposed method outperformed the classical minimum entropy deconvolution method. The proposed method was validated in simulation and experimental signals from railway bearings. In both simulation and experimental studies, the proposed method delivered better deconvolution performance than the classical minimum entropy deconvolution method, especially in the case of low signal-to-noise ratio.

Simulations of Scatterometry Down to 22 nm Structure Sizes and Beyond with Special Emphasis on LER

NASA Astrophysics Data System (ADS)

Osten, W.; Ferreras Paz, V.; Frenner, K.; Schuster, T.; Bloess, H.

2009-09-01

In recent years, scatterometry has become one of the most commonly used methods for CD metrology. With decreasing structure size for future technology nodes, the search for optimized scatterometry measurement configurations gets more important to exploit maximum sensitivity. As widespread industrial scatterometry tools mainly still use a pre-set measurement configuration, there are still free parameters to improve sensitivity. Our current work uses a simulation based approach to predict and optimize sensitivity of future technology nodes. Since line edge roughness is getting important for such small structures, these imperfections of the periodic continuation cannot be neglected. Using fourier methods like e.g. rigorous coupled wave approach (RCWA) for diffraction calculus, nonperiodic features are hard to reach. We show that in this field certain types of fieldstitching methods show nice numerical behaviour and lead to useful results.

A Visual Basic simulation software tool for performance analysis of a membrane-based advanced water treatment plant.

PubMed

Pal, P; Kumar, R; Srivastava, N; Chaudhuri, J

2014-02-01

A Visual Basic simulation software (WATTPPA) has been developed to analyse the performance of an advanced wastewater treatment plant. This user-friendly and menu-driven software is based on the dynamic mathematical model for an industrial wastewater treatment scheme that integrates chemical, biological and membrane-based unit operations. The software-predicted results corroborate very well with the experimental findings as indicated in the overall correlation coefficient of the order of 0.99. The software permits pre-analysis and manipulation of input data, helps in optimization and exhibits performance of an integrated plant visually on a graphical platform. It allows quick performance analysis of the whole system as well as the individual units. The software first of its kind in its domain and in the well-known Microsoft Excel environment is likely to be very useful in successful design, optimization and operation of an advanced hybrid treatment plant for hazardous wastewater.

Support vector machine firefly algorithm based optimization of lens system.

PubMed

Shamshirband, Shahaboddin; Petković, Dalibor; Pavlović, Nenad T; Ch, Sudheer; Altameem, Torki A; Gani, Abdullah

2015-01-01

Lens system design is an important factor in image quality. The main aspect of the lens system design methodology is the optimization procedure. Since optimization is a complex, nonlinear task, soft computing optimization algorithms can be used. There are many tools that can be employed to measure optical performance, but the spot diagram is the most useful. The spot diagram gives an indication of the image of a point object. In this paper, the spot size radius is considered an optimization criterion. Intelligent soft computing scheme support vector machines (SVMs) coupled with the firefly algorithm (FFA) are implemented. The performance of the proposed estimators is confirmed with the simulation results. The result of the proposed SVM-FFA model has been compared with support vector regression (SVR), artificial neural networks, and generic programming methods. The results show that the SVM-FFA model performs more accurately than the other methodologies. Therefore, SVM-FFA can be used as an efficient soft computing technique in the optimization of lens system designs.

Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

PubMed

Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V

2016-01-01

Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

Nonparametric density estimation and optimal bandwidth selection for protein unfolding and unbinding data

NASA Astrophysics Data System (ADS)

Bura, E.; Zhmurov, A.; Barsegov, V.

2009-01-01

Dynamic force spectroscopy and steered molecular simulations have become powerful tools for analyzing the mechanical properties of proteins, and the strength of protein-protein complexes and aggregates. Probability density functions of the unfolding forces and unfolding times for proteins, and rupture forces and bond lifetimes for protein-protein complexes allow quantification of the forced unfolding and unbinding transitions, and mapping the biomolecular free energy landscape. The inference of the unknown probability distribution functions from the experimental and simulated forced unfolding and unbinding data, as well as the assessment of analytically tractable models of the protein unfolding and unbinding requires the use of a bandwidth. The choice of this quantity is typically subjective as it draws heavily on the investigator's intuition and past experience. We describe several approaches for selecting the "optimal bandwidth" for nonparametric density estimators, such as the traditionally used histogram and the more advanced kernel density estimators. The performance of these methods is tested on unimodal and multimodal skewed, long-tailed distributed data, as typically observed in force spectroscopy experiments and in molecular pulling simulations. The results of these studies can serve as a guideline for selecting the optimal bandwidth to resolve the underlying distributions from the forced unfolding and unbinding data for proteins.

Design of a multifiber light delivery system for photoacoustic-guided surgery.

PubMed

Eddins, Blackberrie; Bell, Muyinatu A Lediju

2017-04-01

This work explores light delivery optimization for photoacoustic-guided minimally invasive surgeries, such as the endonasal transsphenoidal approach. Monte Carlo simulations were employed to study three-dimensional light propagation in tissue, comprising one or two 4-mm diameter arteries located 3 mm below bone, an absorbing metallic drill contacting the bone surface, and a single light source placed next to the 2.4-mm diameter drill shaft with a 2.9-mm diameter spherical drill tip. The optimal fiber distance from the drill shaft was determined from the maximum normalized fluence to the underlying artery. Using this optimal fiber-to-drill shaft distance, Zemax simulations were employed to propagate Gaussian beams through one or more 600 micron-core diameter optical fibers for detection on the bone surface. When the number of equally spaced fibers surrounding the drill increased, a single merged optical profile formed with seven or more fibers, determined by thresholding the resulting light profile images at 1 / e times the maximum intensity. We used these simulations to inform design requirements, build a one to seven multifiber light delivery prototype to surround a surgical drill, and demonstrate its ability to simultaneously visualize the tool tip and blood vessel targets in the absence and presence of bone. The results and methodology are generalizable to multiple interventional photoacoustic applications.

Design of a multifiber light delivery system for photoacoustic-guided surgery

NASA Astrophysics Data System (ADS)

Eddins, Blackberrie; Bell, Muyinatu A. Lediju

2017-04-01

This work explores light delivery optimization for photoacoustic-guided minimally invasive surgeries, such as the endonasal transsphenoidal approach. Monte Carlo simulations were employed to study three-dimensional light propagation in tissue, comprising one or two 4-mm diameter arteries located 3 mm below bone, an absorbing metallic drill contacting the bone surface, and a single light source placed next to the 2.4-mm diameter drill shaft with a 2.9-mm diameter spherical drill tip. The optimal fiber distance from the drill shaft was determined from the maximum normalized fluence to the underlying artery. Using this optimal fiber-to-drill shaft distance, Zemax simulations were employed to propagate Gaussian beams through one or more 600 micron-core diameter optical fibers for detection on the bone surface. When the number of equally spaced fibers surrounding the drill increased, a single merged optical profile formed with seven or more fibers, determined by thresholding the resulting light profile images at 1/e times the maximum intensity. We used these simulations to inform design requirements, build a one to seven multifiber light delivery prototype to surround a surgical drill, and demonstrate its ability to simultaneously visualize the tool tip and blood vessel targets in the absence and presence of bone. The results and methodology are generalizable to multiple interventional photoacoustic applications.

Aerospace Toolbox---a flight vehicle design, analysis, simulation ,and software development environment: I. An introduction and tutorial

NASA Astrophysics Data System (ADS)

Christian, Paul M.; Wells, Randy

2001-09-01

This paper presents a demonstrated approach to significantly reduce the cost and schedule of non real-time modeling and simulation, real-time HWIL simulation, and embedded code development. The tool and the methodology presented capitalize on a paradigm that has become a standard operating procedure in the automotive industry. The tool described is known as the Aerospace Toolbox, and it is based on the MathWorks Matlab/Simulink framework, which is a COTS application. Extrapolation of automotive industry data and initial applications in the aerospace industry show that the use of the Aerospace Toolbox can make significant contributions in the quest by NASA and other government agencies to meet aggressive cost reduction goals in development programs. The part I of this paper provides a detailed description of the GUI based Aerospace Toolbox and how it is used in every step of a development program; from quick prototyping of concept developments that leverage built-in point of departure simulations through to detailed design, analysis, and testing. Some of the attributes addressed include its versatility in modeling 3 to 6 degrees of freedom, its library of flight test validated library of models (including physics, environments, hardware, and error sources), and its built-in Monte Carlo capability. Other topics to be covered in this part include flight vehicle models and algorithms, and the covariance analysis package, Navigation System Covariance Analysis Tools (NavSCAT). Part II of this paper, to be published at a later date, will conclude with a description of how the Aerospace Toolbox is an integral part of developing embedded code directly from the simulation models by using the Mathworks Real Time Workshop and optimization tools. It will also address how the Toolbox can be used as a design hub for Internet based collaborative engineering tools such as NASA's Intelligent Synthesis Environment (ISE) and Lockheed Martin's Interactive Missile Design Environment (IMD).

Flight control optimization from design to assessment application on the Cessna Citation X business aircraft =

NASA Astrophysics Data System (ADS)

Boughari, Yamina

New methodologies have been developed to optimize the integration, testing and certification of flight control systems, an expensive process in the aerospace industry. This thesis investigates the stability of the Cessna Citation X aircraft without control, and then optimizes two different flight controllers from design to validation. The aircraft's model was obtained from the data provided by the Research Aircraft Flight Simulator (RAFS) of the Cessna Citation business aircraft. To increase the stability and control of aircraft systems, optimizations of two different flight control designs were performed: 1) the Linear Quadratic Regulation and the Proportional Integral controllers were optimized using the Differential Evolution algorithm and the level 1 handling qualities as the objective function. The results were validated for the linear and nonlinear aircraft models, and some of the clearance criteria were investigated; and 2) the Hinfinity control method was applied on the stability and control augmentation systems. To minimize the time required for flight control design and its validation, an optimization of the controllers design was performed using the Differential Evolution (DE), and the Genetic algorithms (GA). The DE algorithm proved to be more efficient than the GA. New tools for visualization of the linear validation process were also developed to reduce the time required for the flight controller assessment. Matlab software was used to validate the different optimization algorithms' results. Research platforms of the aircraft's linear and nonlinear models were developed, and compared with the results of flight tests performed on the Research Aircraft Flight Simulator. Some of the clearance criteria of the optimized H-infinity flight controller were evaluated, including its linear stability, eigenvalues, and handling qualities criteria. Nonlinear simulations of the maneuvers criteria were also investigated during this research to assess the Cessna Citation X's flight controller clearance, and therefore, for its anticipated certification.

Performance Trades Study for Robust Airfoil Shape Optimization

NASA Technical Reports Server (NTRS)

Li, Wu; Padula, Sharon

2003-01-01

From time to time, existing aircraft need to be redesigned for new missions with modified operating conditions such as required lift or cruise speed. This research is motivated by the needs of conceptual and preliminary design teams for smooth airfoil shapes that are similar to the baseline design but have improved drag performance over a range of flight conditions. The proposed modified profile optimization method (MPOM) modifies a large number of design variables to search for nonintuitive performance improvements, while avoiding off-design performance degradation. Given a good initial design, the MPOM generates fairly smooth airfoils that are better than the baseline without making drastic shape changes. Moreover, the MPOM allows users to gain valuable information by exploring performance trades over various design conditions. Four simulation cases of airfoil optimization in transonic viscous ow are included to demonstrate the usefulness of the MPOM as a performance trades study tool. Simulation results are obtained by solving fully turbulent Navier-Stokes equations and the corresponding discrete adjoint equations using an unstructured grid computational fluid dynamics code FUN2D.

Development of a simplified urban water balance model (WABILA).

PubMed

Henrichs, M; Langner, J; Uhl, M

2016-01-01

During the last decade, water sensitive urban design (WSUD) has become more and more accepted. However, there is not any simple tool or option available to evaluate the influence of these measures on the local water balance. To counteract the impact of new settlements, planners focus on mitigating increases in runoff through installation of infiltration systems. This leads to an increasing non-natural groundwater recharge and decreased evapotranspiration. Simple software tools which evaluate or simulate the effect of WSUD on the local water balance are still needed. The authors developed a tool named WABILA (Wasserbilanz) that could support planners for optimal WSUD. WABILA is an easy-to-use planning tool that is based on simplified regression functions for established measures and land covers. Results show that WSUD has to be site-specific, based on climate conditions and the natural water balance.

Online optimal obstacle avoidance for rotary-wing autonomous unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Keeryun

This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic. The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle. The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. The flight test evaluations were extended to the benchmark tests for 3D avoidance capability over the virtual obstacles, and finally it was demonstrated on real obstacles located at the McKenna MOUT site in Fort Benning, Georgia. Simulations and flight test evaluations demonstrate the feasibility of the developed framework for UAV applications involving low-altitude flight in an urban area.

Molecular simulation and experimental validation of resorcinol adsorption on Ordered Mesoporous Carbon (OMC).

PubMed

Ahmad, Zaki Uddin; Chao, Bing; Konggidinata, Mas Iwan; Lian, Qiyu; Zappi, Mark E; Gang, Daniel Dianchen

2018-04-27

Numerous research works have been devoted in the adsorption area using experimental approaches. All these approaches are based on trial and error process and extremely time consuming. Molecular simulation technique is a new tool that can be used to design and predict the performance of an adsorbent. This research proposed a simulation technique that can greatly reduce the time in designing the adsorbent. In this study, a new Rhombic ordered mesoporous carbon (OMC) model is proposed and constructed with various pore sizes and oxygen contents using Materials Visualizer Module to optimize the structure of OMC for resorcinol adsorption. The specific surface area, pore volume, small angle X-ray diffraction pattern, and resorcinol adsorption capacity were calculated by Forcite and Sorption module in Materials Studio Package. The simulation results were validated experimentally through synthesizing OMC with different pore sizes and oxygen contents prepared via hard template method employing SBA-15 silica scaffold. Boric acid was used as the pore expanding reagent to synthesize OMC with different pore sizes (from 4.6 to 11.3 nm) and varying oxygen contents (from 11.9% to 17.8%). Based on the simulation and experimental validation, the optimal pore size was found to be 6 nm for maximum adsorption of resorcinol. Copyright © 2018 Elsevier B.V. All rights reserved.

Simulations of ultrafast x-ray laser experiments

NASA Astrophysics Data System (ADS)

Fortmann-Grote, C.; Andreev, A. A.; Appel, K.; Branco, J.; Briggs, R.; Bussmann, M.; Buzmakov, A.; Garten, M.; Grund, A.; Huebl, A.; Jurek, Z.; Loh, N. D.; Nakatsutsumi, M.; Samoylova, L.; Santra, R.; Schneidmiller, E. A.; Sharma, A.; Steiniger, K.; Yakubov, S.; Yoon, C. H.; Yurkov, M. V.; Zastrau, U.; Ziaja-Motyka, B.; Mancuso, A. P.

2017-06-01

Simulations of experiments at modern light sources, such as optical laser laboratories, synchrotrons, and free electron lasers, become increasingly important for the successful preparation, execution, and analysis of these experiments investigating ever more complex physical systems, e.g. biomolecules, complex materials, and ultra-short lived states of matter at extreme conditions. We have implemented a platform for complete start-to-end simulations of various types of photon science experiments, tracking the radiation from the source through the beam transport optics to the sample or target under investigation, its interaction with and scattering from the sample, and registration in a photon detector. This tool allows researchers and facility operators to simulate their experiments and instruments under real life conditions, identify promising and unattainable regions of the parameter space and ultimately make better use of valuable beamtime. In this paper, we present an overview about status and future development of the simulation platform and discuss three applications: 1.) Single-particle imaging of biomolecules using x-ray free electron lasers and optimization of x-ray pulse properties, 2.) x-ray scattering diagnostics of hot dense plasmas in high power laser-matter interaction and identification of plasma instabilities, and 3.) x-ray absorption spectroscopy in warm dense matter created by high energy laser-matter interaction and pulse shape optimization for low-isentrope dynamic compression.

Liner Optimization Studies Using the Ducted Fan Noise Prediction Code TBIEM3D

NASA Technical Reports Server (NTRS)

Dunn, M. H.; Farassat, F.

1998-01-01

In this paper we demonstrate the usefulness of the ducted fan noise prediction code TBIEM3D as a liner optimization design tool. Boundary conditions on the interior duct wall allow for hard walls or a locally reacting liner with axially segmented, circumferentially uniform impedance. Two liner optimization studies are considered in which farfield noise attenuation due to the presence of a liner is maximized by adjusting the liner impedance. In the first example, the dependence of optimal liner impedance on frequency and liner length is examined. Results show that both the optimal impedance and attenuation levels are significantly influenced by liner length and frequency. In the second example, TBIEM3D is used to compare radiated sound pressure levels between optimal and non-optimal liner cases at conditions designed to simulate take-off. It is shown that significant noise reduction is achieved for most of the sound field by selecting the optimal or near optimal liner impedance. Our results also indicate that there is relatively large region of the impedance plane over which optimal or near optimal liner behavior is attainable. This is an important conclusion for the designer since there are variations in liner characteristics due to manufacturing imprecisions.

PlasmaPy: beginning a community developed Python package for plasma physics

NASA Astrophysics Data System (ADS)

Murphy, Nicholas A.; Huang, Yi-Min; PlasmaPy Collaboration

2016-10-01

In recent years, researchers in several disciplines have collaborated on community-developed open source Python packages such as Astropy, SunPy, and SpacePy. These packages provide core functionality, common frameworks for data analysis and visualization, and educational tools. We propose that our community begins the development of PlasmaPy: a new open source core Python package for plasma physics. PlasmaPy could include commonly used functions in plasma physics, easy-to-use plasma simulation codes, Grad-Shafranov solvers, eigenmode solvers, and tools to analyze both simulations and experiments. The development will include modern programming practices such as version control, embedding documentation in the code, unit tests, and avoiding premature optimization. We will describe early code development on PlasmaPy, and discuss plans moving forward. The success of PlasmaPy depends on active community involvement and a welcoming and inclusive environment, so anyone interested in joining this collaboration should contact the authors.

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments.

PubMed

Thomas, Brandon R; Chylek, Lily A; Colvin, Joshua; Sirimulla, Suman; Clayton, Andrew H A; Hlavacek, William S; Posner, Richard G

2016-03-01

Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive. BioNetFit can be used on stand-alone Mac, Windows/Cygwin, and Linux platforms and on Linux-based clusters running SLURM, Torque/PBS, or SGE. The BioNetFit source code (Perl) is freely available (http://bionetfit.nau.edu). Supplementary data are available at Bioinformatics online. bionetgen.help@gmail.com. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

American Society of Composites, 32nd Technical Conference

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

Aitharaju, Venkat; Yu, Hang; Zhao, Selina

Resin transfer molding (RTM) has become increasingly popular for the manufacturing of composite parts. To enable high volume manufacturing and obtain good quality parts at an acceptable cost to automotive industry, accurate process simulation tools are necessary to optimize the process conditions. Towards that goal, General Motors and the ESI-group are involved in developing a state of the art process simulation tool for composite manufacturing in a project supported by the Department of Energy. This paper describes the modeling of various stages in resin transfer molding such as resin injection, resin curing, and part distortion. An instrumented RTM system locatedmore » at the General Motors Research and Development center was used to perform flat plaque molding experiments. The experimental measurements of fill time, in-mold pressure versus time, cure variation with time, and part deformation were compared with the model predictions and very good correlations were observed.« less

Planning additional drilling campaign using two-space genetic algorithm: A game theoretical approach

NASA Astrophysics Data System (ADS)

Kumral, Mustafa; Ozer, Umit

2013-03-01

Grade and tonnage are the most important technical uncertainties in mining ventures because of the use of estimations/simulations, which are mostly generated from drill data. Open pit mines are planned and designed on the basis of the blocks representing the entire orebody. Each block has different estimation/simulation variance reflecting uncertainty to some extent. The estimation/simulation realizations are submitted to mine production scheduling process. However, the use of a block model with varying estimation/simulation variances will lead to serious risk in the scheduling. In the medium of multiple simulations, the dispersion variances of blocks can be thought to regard technical uncertainties. However, the dispersion variance cannot handle uncertainty associated with varying estimation/simulation variances of blocks. This paper proposes an approach that generates the configuration of the best additional drilling campaign to generate more homogenous estimation/simulation variances of blocks. In other words, the objective is to find the best drilling configuration in such a way as to minimize grade uncertainty under budget constraint. Uncertainty measure of the optimization process in this paper is interpolation variance, which considers data locations and grades. The problem is expressed as a minmax problem, which focuses on finding the best worst-case performance i.e., minimizing interpolation variance of the block generating maximum interpolation variance. Since the optimization model requires computing the interpolation variances of blocks being simulated/estimated in each iteration, the problem cannot be solved by standard optimization tools. This motivates to use two-space genetic algorithm (GA) approach to solve the problem. The technique has two spaces: feasible drill hole configuration with minimization of interpolation variance and drill hole simulations with maximization of interpolation variance. Two-space interacts to find a minmax solution iteratively. A case study was conducted to demonstrate the performance of approach. The findings showed that the approach could be used to plan a new drilling campaign.

An online tool for tracking soil nitrogen

NASA Astrophysics Data System (ADS)

Wang, J.; Umar, M.; Banger, K.; Pittelkow, C. M.; Nafziger, E. D.

2016-12-01

Near real-time crop models can be useful tools for optimizing agricultural management practices. For example, model simulations can potentially provide current estimates of nitrogen availability in soil, helping growers decide whether more nitrogen needs to be applied in a given season. Traditionally, crop models have been used at point locations (i.e. single fields) with homogenous soil, climate and initial conditions. However, nitrogen availability across fields with varied weather and soil conditions at a regional or national level is necessary to guide better management decisions. This study presents the development of a publicly available, online tool that automates the integration of high-spatial-resolution forecast and past weather and soil data in DSSAT to estimate nitrogen availability for individual fields in Illinois. The model has been calibrated with field experiments from past year at six research corn fields across Illinois. These sites were treated with applications of different N fertilizer timings and amounts. The tool requires minimal management information from growers and yet has the capability to simulate nitrogen-water-crop interactions with calibrated parameters that are more appropriate for Illinois. The results from the tool will be combined with incoming field experiment data from 2016 for model validation and further improvement of model's predictive accuracy. The tool has the potential to help guide better nitrogen management practices to maximize economic and environmental benefits.

Augmenting Parametric Optimal Ascent Trajectory Modeling with Graph Theory

NASA Technical Reports Server (NTRS)

Dees, Patrick D.; Zwack, Matthew R.; Edwards, Stephen; Steffens, Michael

2016-01-01

It has been well documented that decisions made in the early stages of Conceptual and Pre-Conceptual design commit up to 80% of total Life-Cycle Cost (LCC) while engineers know the least about the product they are designing [1]. Once within Preliminary and Detailed design however, making changes to the design becomes far more difficult to enact in both cost and schedule. Primarily this has been due to a lack of detailed data usually uncovered later during the Preliminary and Detailed design phases. In our current budget-constrained environment, making decisions within Conceptual and Pre-Conceptual design which minimize LCC while meeting requirements is paramount to a program's success. Within the arena of launch vehicle design, optimizing the ascent trajectory is critical for minimizing the costs present within such concerns as propellant, aerodynamic, aeroheating, and acceleration loads while meeting requirements such as payload delivered to a desired orbit. In order to optimize the vehicle design its constraints and requirements must be known, however as the design cycle proceeds it is all but inevitable that the conditions will change. Upon that change, the previously optimized trajectory may no longer be optimal, or meet design requirements. The current paradigm for adjusting to these updates is generating point solutions for every change in the design's requirements [2]. This can be a tedious, time-consuming task as changes in virtually any piece of a launch vehicle's design can have a disproportionately large effect on the ascent trajectory, as the solution space of the trajectory optimization problem is both non-linear and multimodal [3]. In addition, an industry standard tool, Program to Optimize Simulated Trajectories (POST), requires an expert analyst to produce simulated trajectories that are feasible and optimal [4]. In a previous publication the authors presented a method for combatting these challenges [5]. In order to bring more detailed information into Conceptual and Pre-Conceptual design, knowledge of the effects originating from changes to the vehicle must be calculated. In order to do this, a model capable of quantitatively describing any vehicle within the entire design space under consideration must be constructed. This model must be based upon analysis of acceptable fidelity, which in this work comes from POST. Design space interrogation can be achieved with surrogate modeling, a parametric, polynomial equation representing a tool. A surrogate model must be informed by data from the tool with enough points to represent the solution space for the chosen number of variables with an acceptable level of error. Therefore, Design Of Experiments (DOE) is used to select points within the design space to maximize information gained on the design space while minimizing number of data points required. To represent a design space with a non-trivial number of variable parameters the number of points required still represent an amount of work which would take an inordinate amount of time via the current paradigm of manual analysis, and so an automated method was developed. The best practices of expert trajectory analysts working within NASA Marshall's Advanced Concepts Office (ACO) were implemented within a tool called multiPOST. These practices include how to use the output data from a previous run of POST to inform the next, determining whether a trajectory solution is feasible from a real-world perspective, and how to handle program execution errors. The tool was then augmented with multiprocessing capability to enable analysis on multiple trajectories simultaneously, allowing throughput to scale with available computational resources. In this update to the previous work the authors discuss issues with the method and solutions.

Aerodynamic Optimization of Rocket Control Surface Geometry Using Cartesian Methods and CAD Geometry

NASA Technical Reports Server (NTRS)

Nelson, Andrea; Aftosmis, Michael J.; Nemec, Marian; Pulliam, Thomas H.

2004-01-01

Aerodynamic design is an iterative process involving geometry manipulation and complex computational analysis subject to physical constraints and aerodynamic objectives. A design cycle consists of first establishing the performance of a baseline design, which is usually created with low-fidelity engineering tools, and then progressively optimizing the design to maximize its performance. Optimization techniques have evolved from relying exclusively on designer intuition and insight in traditional trial and error methods, to sophisticated local and global search methods. Recent attempts at automating the search through a large design space with formal optimization methods include both database driven and direct evaluation schemes. Databases are being used in conjunction with surrogate and neural network models as a basis on which to run optimization algorithms. Optimization algorithms are also being driven by the direct evaluation of objectives and constraints using high-fidelity simulations. Surrogate methods use data points obtained from simulations, and possibly gradients evaluated at the data points, to create mathematical approximations of a database. Neural network models work in a similar fashion, using a number of high-fidelity database calculations as training iterations to create a database model. Optimal designs are obtained by coupling an optimization algorithm to the database model. Evaluation of the current best design then gives either a new local optima and/or increases the fidelity of the approximation model for the next iteration. Surrogate methods have also been developed that iterate on the selection of data points to decrease the uncertainty of the approximation model prior to searching for an optimal design. The database approximation models for each of these cases, however, become computationally expensive with increase in dimensionality. Thus the method of using optimization algorithms to search a database model becomes problematic as the number of design variables is increased.

A global carbon assimilation system based on a dual optimization method

NASA Astrophysics Data System (ADS)

Zheng, H.; Li, Y.; Chen, J. M.; Wang, T.; Huang, Q.; Huang, W. X.; Wang, L. H.; Li, S. M.; Yuan, W. P.; Zheng, X.; Zhang, S. P.; Chen, Z. Q.; Jiang, F.

2015-02-01

Ecological models are effective tools for simulating the distribution of global carbon sources and sinks. However, these models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) to an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a dual optimization method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state simultaneously. We use GCAS-DOM to estimate the global distribution of the CO2 flux on 1° × 1° grid cells for the period from 2001 to 2007. Results show that land and ocean absorb -3.63 ± 0.50 and -1.82 ± 0.16 Pg C yr-1, respectively. North America, Europe and China contribute -0.98 ± 0.15, -0.42 ± 0.08 and -0.20 ± 0.29 Pg C yr-1, respectively. The uncertainties in the flux after optimization by GCAS-DOM have been remarkably reduced by more than 60%. Through parameter optimization, GCAS-DOM can provide improved estimates of the carbon flux for each PFT. Coniferous forest (-0.97 ± 0.27 Pg C yr-1) is the largest contributor to the global carbon sink. Fluxes of once-dominant deciduous forest generated by the Boreal Ecosystems Productivity Simulator (BEPS) are reduced to -0.78 ± 0.23 Pg C yr-1, the third largest carbon sink.

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

PubMed

Aprasoff, Jonathan; Donchin, Opher

2012-04-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

Simulation and Application of GPOPS for a Trajectory Optimization and Mission Planning Tool

DTIC Science & Technology

2010-03-01

12,000lbf) vaccum Specific Impulse 269 s 455 s 316 s Burn Time 124 s 480 s 1250s Fuel Solid LOX/ LH2 MMH/N2O4 Height 184 ft Diameter 28.5 ft...285,000 lb Engine 2 J-2S Linear Aerospikes Thrust 410,000 lbf Fuel LOX/ LH2 20 Figure 9: Minuteman Launch [29] Currently the main missile

Quasi-Phasematched Nonlinear Optics: Materials and Devices

DTIC Science & Technology

2012-02-29

effects all contribute, and that the group velocity dispersion in the vicinity of the pump wavelength and are important factors influencing the breadth...for the physics underlying χ(2) SC generation, so the work was purely empirical, but still resulted in octave-class SC and envelop locking with...specific goals, e.g soliton self-frequency shift, SC generation, etc. emerged, and could then be optimized with the numerical simulation tool

Flow Simulations: The Lagrangian Averaged Navier-stokes Equations and Optimization

DTIC Science & Technology

2009-05-19

S) 12. DISTRIBUTION/AVAILABILITY STATEMENT DISTRIBUTION A: APPROVED FOR PUBLIC RELEASE 13. SUPPLEMENTARY NOTES 14. ABSTRACT This project had two...Structures can be an important tool in achieving this goal. As we will demonstate, LCS can be very usefull in identifying the separation manifolds...s) financially responsible for and monitoring the work. 10. SPONSOR/MONITOR’S ACRONYM(S). Enter, if available, e.g. BRL, ARDEC, NADC. 11. SPONSOR

Agent-Based Framework for Discrete Entity Simulations

DTIC Science & Technology

2006-11-01

Postgres database server for environment queries of neighbors and continuum data. As expected for raw database queries (no database optimizations in...form. Eventually the code was ported to GNU C++ on the same single Intel Pentium 4 CPU running RedHat Linux 9.0 and Postgres database server...Again Postgres was used for environmental queries, and the tool remained relatively slow because of the immense number of queries necessary to assess

A finite element model of rigid body structures actuated by dielectric elastomer actuators

NASA Astrophysics Data System (ADS)

Simone, F.; Linnebach, P.; Rizzello, G.; Seelecke, S.

2018-06-01

This paper presents on finite element (FE) modeling and simulation of dielectric elastomer actuators (DEAs) coupled with articulated structures. DEAs have proven to represent an effective transduction technology for the realization of large deformation, low-power consuming, and fast mechatronic actuators. However, the complex dynamic behavior of the material, characterized by nonlinearities and rate-dependent phenomena, makes it difficult to accurately model and design DEA systems. The problem is further complicated in case the DEA is used to activate articulated structures, which increase both system complexity and implementation effort of numerical simulation models. In this paper, we present a model based tool which allows to effectively implement and simulate complex articulated systems actuated by DEAs. A first prototype of a compact switch actuated by DEA membranes is chosen as reference study to introduce the methodology. The commercially available FE software COMSOL is used for implementing and coupling a physics-based dynamic model of the DEA with the external structure, i.e., the switch. The model is then experimentally calibrated and validated in both quasi-static and dynamic loading conditions. Finally, preliminary results on how to use the simulation tool to optimize the design are presented.

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

NASA Technical Reports Server (NTRS)

Lee, Hanbong

2016-01-01

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

An efficient 3-D eddy-current solver using an independent impedance method for transcranial magnetic stimulation.

PubMed

De Geeter, Nele; Crevecoeur, Guillaume; Dupre, Luc

2011-02-01

In many important bioelectromagnetic problem settings, eddy-current simulations are required. Examples are the reduction of eddy-current artifacts in magnetic resonance imaging and techniques, whereby the eddy currents interact with the biological system, like the alteration of the neurophysiology due to transcranial magnetic stimulation (TMS). TMS has become an important tool for the diagnosis and treatment of neurological diseases and psychiatric disorders. A widely applied method for simulating the eddy currents is the impedance method (IM). However, this method has to contend with an ill conditioned problem and consequently a long convergence time. When dealing with optimal design problems and sensitivity control, the convergence rate becomes even more crucial since the eddy-current solver needs to be evaluated in an iterative loop. Therefore, we introduce an independent IM (IIM), which improves the conditionality and speeds up the numerical convergence. This paper shows how IIM is based on IM and what are the advantages. Moreover, the method is applied to the efficient simulation of TMS. The proposed IIM achieves superior convergence properties with high time efficiency, compared to the traditional IM and is therefore a useful tool for accurate and fast TMS simulations.

Topology of modified helical gears and Tooth Contact Analysis (TCA) program

NASA Technical Reports Server (NTRS)

Litvin, Faydor L.; Zhang, Jiao

1989-01-01

The contents of this report covers: (1) development of optimal geometries for crowned helical gears; (2) a method for their generation; (3) tooth contact analysis (TCA) computer programs for the analysis of meshing and bearing contact of the crowned helical gears; and (4) modelling and simulation of gear shaft deflection. The developed method for synthesis was used to determine the optimal geometry for a crowned helical pinion surface and was directed to localize the bearing contact and guarantee favorable shape and a low level of transmission errors. Two new methods for generation of the crowned helical pinion surface are proposed. One is based on the application of a tool with a surface of revolution that slightly deviates from a regular cone surface. The tool can be used as a grinding wheel or as a shaver. The other is based on a crowning pinion tooth surface with predesigned transmission errors. The pinion tooth surface can be generated by a computer-controlled automatic grinding machine. The TCA program simulates the meshing and bearing contact of the misaligned gears. The transmission errors are also determined. The gear shaft deformation was modelled and investigated. It was found that the deflection of gear shafts has the same effect as gear misalignment.

An Accurate and Computationally Efficient Model for Membrane-Type Circular-Symmetric Micro-Hotplates

PubMed Central

Khan, Usman; Falconi, Christian

2014-01-01

Ideally, the design of high-performance micro-hotplates would require a large number of simulations because of the existence of many important design parameters as well as the possibly crucial effects of both spread and drift. However, the computational cost of FEM simulations, which are the only available tool for accurately predicting the temperature in micro-hotplates, is very high. As a result, micro-hotplate designers generally have no effective simulation-tools for the optimization. In order to circumvent these issues, here, we propose a model for practical circular-symmetric micro-hot-plates which takes advantage of modified Bessel functions, computationally efficient matrix-approach for considering the relevant boundary conditions, Taylor linearization for modeling the Joule heating and radiation losses, and external-region-segmentation strategy in order to accurately take into account radiation losses in the entire micro-hotplate. The proposed model is almost as accurate as FEM simulations and two to three orders of magnitude more computationally efficient (e.g., 45 s versus more than 8 h). The residual errors, which are mainly associated to the undesired heating in the electrical contacts, are small (e.g., few degrees Celsius for an 800 °C operating temperature) and, for important analyses, almost constant. Therefore, we also introduce a computationally-easy single-FEM-compensation strategy in order to reduce the residual errors to about 1 °C. As illustrative examples of the power of our approach, we report the systematic investigation of a spread in the membrane thermal conductivity and of combined variations of both ambient and bulk temperatures. Our model enables a much faster characterization of micro-hotplates and, thus, a much more effective optimization prior to fabrication. PMID:24763214

Commnity Petascale Project for Accelerator Science And Simulation: Advancing Computational Science for Future Accelerators And Accelerator Technologies

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

Spentzouris, Panagiotis; /Fermilab; Cary, John

The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors.« less

Numerical simulations of epitaxial growth process in MOVPE reactor as a tool for design of modern semiconductors for high power electronics

NASA Astrophysics Data System (ADS)

Skibinski, Jakub; Caban, Piotr; Wejrzanowski, Tomasz; Kurzydlowski, Krzysztof J.

2014-10-01

In the present study numerical simulations of epitaxial growth of gallium nitride in Metal Organic Vapor Phase Epitaxy reactor AIX-200/4RF-S is addressed. Epitaxial growth means crystal growth that progresses while inheriting the laminar structure and the orientation of substrate crystals. One of the technological problems is to obtain homogeneous growth rate over the main deposit area. Since there are many agents influencing reaction on crystal area such as temperature, pressure, gas flow or reactor geometry, it is difficult to design optimal process. According to the fact that it's impossible to determine experimentally the exact distribution of heat and mass transfer inside the reactor during crystal growth, modeling is the only solution to understand the process precisely. Numerical simulations allow to understand the epitaxial process by calculation of heat and mass transfer distribution during growth of gallium nitride. Including chemical reactions in numerical model allows to calculate the growth rate of the substrate and estimate the optimal process conditions for obtaining the most homogeneous product.

Layout optimization of DRAM cells using rigorous simulation model for NTD

NASA Astrophysics Data System (ADS)

Jeon, Jinhyuck; Kim, Shinyoung; Park, Chanha; Yang, Hyunjo; Yim, Donggyu; Kuechler, Bernd; Zimmermann, Rainer; Muelders, Thomas; Klostermann, Ulrich; Schmoeller, Thomas; Do, Mun-hoe; Choi, Jung-Hoe

2014-03-01

DRAM chip space is mainly determined by the size of the memory cell array patterns which consist of periodic memory cell features and edges of the periodic array. Resolution Enhancement Techniques (RET) are used to optimize the periodic pattern process performance. Computational Lithography such as source mask optimization (SMO) to find the optimal off axis illumination and optical proximity correction (OPC) combined with model based SRAF placement are applied to print patterns on target. For 20nm Memory Cell optimization we see challenges that demand additional tool competence for layout optimization. The first challenge is a memory core pattern of brick-wall type with a k1 of 0.28, so it allows only two spectral beams to interfere. We will show how to analytically derive the only valid geometrically limited source. Another consequence of two-beam interference limitation is a "super stable" core pattern, with the advantage of high depth of focus (DoF) but also low sensitivity to proximity corrections or changes of contact aspect ratio. This makes an array edge correction very difficult. The edge can be the most critical pattern since it forms the transition from the very stable regime of periodic patterns to non-periodic periphery, so it combines the most critical pitch and highest susceptibility to defocus. Above challenge makes the layout correction to a complex optimization task demanding a layout optimization that finds a solution with optimal process stability taking into account DoF, exposure dose latitude (EL), mask error enhancement factor (MEEF) and mask manufacturability constraints. This can only be achieved by simultaneously considering all criteria while placing and sizing SRAFs and main mask features. The second challenge is the use of a negative tone development (NTD) type resist, which has a strong resist effect and is difficult to characterize experimentally due to negative resist profile taper angles that perturb CD at bottom characterization by scanning electron microscope (SEM) measurements. High resist impact and difficult model data acquisition demand for a simulation model that hat is capable of extrapolating reliably beyond its calibration dataset. We use rigorous simulation models to provide that predictive performance. We have discussed the need of a rigorous mask optimization process for DRAM contact cell layout yielding mask layouts that are optimal in process performance, mask manufacturability and accuracy. In this paper, we have shown the step by step process from analytical illumination source derivation, a NTD and application tailored model calibration to layout optimization such as OPC and SRAF placement. Finally the work has been verified with simulation and experimental results on wafer.

Optimization-Based Calibration of FAST.Farm Parameters Against SOWFA: Preprint

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

Moreira, Paula D; Annoni, Jennifer; Jonkman, Jason

2018-01-04

FAST.Farm is a medium-delity wind farm modeling tool that can be used to assess power and loads contributions of wind turbines in a wind farm. The objective of this paper is to undertake a calibration procedure to set the user parameters of FAST.Farm to accurately represent results from large-eddy simulations. The results provide an in- depth analysis of the comparison of FAST.Farm and large-eddy simulations before and after calibration. The comparison of FAST.Farm and large-eddy simulation results are presented with respect to streamwise and radial velocity components as well as wake-meandering statistics (mean and standard deviation) in the lateral andmore » vertical directions under different atmospheric and turbine operating conditions.« less

Simulation of the Simbol-X Telescope

NASA Astrophysics Data System (ADS)

Chauvin, M.; Roques, J. P.

2009-05-01

We have developed a simulation tool for a Wolter I telescope operating in formation flight. The aim is to understand and predict the behavior of the Simbol-X instrument. As the geometry is variable, formation flight introduces new challenges and complex implications. Our code, based on Monte Carlo ray tracing, computes the full photon trajectories up to the detector plane, along with the relative drifts of the two spacecrafts. It takes into account angle and energy dependent interactions of the photons with the mirrors and applies to any grazing incidence telescope. The resulting images of simulated sources from 0.1 keV to 100 keV allow us to optimize the configuration of the instrument and to assess the performance of the Simbol-X telescope.

Advancing the LSST Operations Simulator

NASA Astrophysics Data System (ADS)

Saha, Abhijit; Ridgway, S. T.; Cook, K. H.; Delgado, F.; Chandrasekharan, S.; Petry, C. E.; Operations Simulator Group

2013-01-01

The Operations Simulator for the Large Synoptic Survey Telescope (LSST; http://lsst.org) allows the planning of LSST observations that obey explicit science driven observing specifications, patterns, schema, and priorities, while optimizing against the constraints placed by design-specific opto-mechanical system performance of the telescope facility, site specific conditions (including weather and seeing), as well as additional scheduled and unscheduled downtime. A simulation run records the characteristics of all observations (e.g., epoch, sky position, seeing, sky brightness) in a MySQL database, which can be queried for any desired purpose. Derivative information digests of the observing history database are made with an analysis package called Simulation Survey Tools for Analysis and Reporting (SSTAR). Merit functions and metrics have been designed to examine how suitable a specific simulation run is for several different science applications. This poster reports recent work which has focussed on an architectural restructuring of the code that will allow us to a) use "look-ahead" strategies that avoid cadence sequences that cannot be completed due to observing constraints; and b) examine alternate optimization strategies, so that the most efficient scheduling algorithm(s) can be identified and used: even few-percent efficiency gains will create substantive scientific opportunity. The enhanced simulator will be used to assess the feasibility of desired observing cadences, study the impact of changing science program priorities, and assist with performance margin investigations of the LSST system.