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At least 1,315 records · Page 73

An investigation of surface parameter estimation from surface models

In surface scattering problems, scattering models are used to estimate the surface parameters by comparing model predictions to data. The meaning of such a procedure is examined using computer simulated scattering data from statistically known surfaces. Numerically exact scattering computations based on the moment method are conducted, and standard surface scattering models are applied to these simulated data. It is shown that such an approach usually leads to effective surface parameters as opposed to real surface parameters, except for a limited frequency region. It is also shown that if a surface scattering model is valid over all frequencies, then it is possible to recover the real surface parameters regardless of whether the surface is single scale or two scale.

Fung, A. K.↗

Machine learning strategies for systems with invariance properties

Here, in many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds-Averaged Navier-Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high-performance computing has led to a growing availability of high-fidelity simulation data, which open up the possibility of using machine learning algorithms, such as random forests or neural networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first , a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance with significantly reduced computational training costs.

97 MATHEMATICS AND COMPUTING↗

Metallographic Cooling Rate of IVA Irons Revisited

There is long standing problem reconciling the chemical evidence that the IVA iron meteorites formed in a core with the diverse cooling rates reported by several researchers. This large inferred range of cooling rates suggests that the IVA irons were distributed at different depths in a parent body with a complex structure when the Widmanstatten pattern formed. On the other hand, some researchers argued that the diverse cooling rates in group IVA result from inaccurate model parameters such as phase diagram, interdiffusion coefficients, and kamacite nucleation and growth mechanisms. In addition, the measured cooling rates may not apply for the same cooling temperature ranges, and the variation in the crystallographic orientations of the Widmanstatten plates on the analysis surface may result in inaccurate measurements of widths needed for the computer simulation models. We have revaluated the major parameters in computer model developed by Hopfe and Goldstein and measured cooling rates for the IVA irons. Such data are useful in evaluating whether these meteorites were part of a single core of a parent body during the formation of the Widmanstatten pattern.

Yang, J.↗

Developing a Model Component

The Spaceport Command and Control System (SCCS) Simulation Computer Software Configuration Item (CSCI) is responsible for providing simulations to support test and verification of SCCS hardware and software. The Universal Coolant Transporter System (UCTS) was a Space Shuttle Orbiter support piece of the Ground Servicing Equipment (GSE). The initial purpose of the UCTS was to provide two support services to the Space Shuttle Orbiter immediately after landing at the Shuttle Landing Facility. The UCTS is designed with the capability of servicing future space vehicles; including all Space Station Requirements necessary for the MPLM Modules. The Simulation uses GSE Models to stand in for the actual systems to support testing of SCCS systems during their development. As an intern at Kennedy Space Center (KSC), my assignment was to develop a model component for the UCTS. I was given a fluid component (dryer) to model in Simulink. I completed training for UNIX and Simulink. The dryer is a Catch All replaceable core type filter-dryer. The filter-dryer provides maximum protection for the thermostatic expansion valve and solenoid valve from dirt that may be in the system. The filter-dryer also protects the valves from freezing up. I researched fluid dynamics to understand the function of my component. The filter-dryer was modeled by determining affects it has on the pressure and velocity of the system. I used Bernoulli's Equation to calculate the pressure and velocity differential through the dryer. I created my filter-dryer model in Simulink and wrote the test script to test the component. I completed component testing and captured test data. The finalized model was sent for peer review for any improvements. I participated in Simulation meetings and was involved in the subsystem design process and team collaborations. I gained valuable work experience and insight into a career path as an engineer.

Fields, Christina M.↗

Developing a Model Component

The Spaceport Command and Control System (SCCS) Simulation Computer Software Configuration Item (CSCI) is,. responsible for providing simulations to support test and verification of SCCS hardware and software. The Universal Coolant Transporter System (UCTS) is a Space Shuttle Orbiter support piece of the Ground Servicing Equipment (GSE). The purpose of the UCTS is to provide two support services to the Space Shuttle Orbiter immediately after landing at the Shuttle Landing Facility. The Simulation uses GSE Models to stand in for the actual systems to support testing of SCCS systems s:luring their development. As an intern at KSC, my assignment was to develop a model component for the UCTS. I was given a fluid component (drier) to model in Matlab. The drier was a Catch All replaceable core type filter-drier. The filter-drier provides maximum protection for the thermostatic expansion valve and solenoid valve from dirt that may be in the system. The filter-drier also protects the valves from freezing up. I researched fluid dynamics to understand the function of my component. I completed training for UNIX and Simulink to help aid in my assignment. The filter-drier was modeled by determining affects it has on the pressure, velocity and temperature of the system. I used Bernoulli's Equation to calculate the pressure and velocity differential through the dryer. I created my model filter-drier in Simulink and wrote the test script to test the component. I completed component testing and captured test data. The finalized model was sent for peer review for any improvements.

Fields, Christina M.↗

Simulation of a G-tolerance curve using the pulsatile cardiovascular model

A computer simulation study, performed to assess the ability of the cardiovascular model to reproduce the G tolerance curve (G level versus tolerance time) is reported. A composite strength duration curve derived from experimental data obtained in human centrifugation studies was used for comparison. The effects of abolishing automomic control and of blood volume loss on G tolerance were also simulated. The results provide additional validation of the model. The need for the presence of autonomic reflexes even at low levels of G is pointed out. The low margin of safety with a loss of blood volume indicated by the simulation results underscores the necessity for protective measures during Shuttle reentry.

Solomon, M.↗

Wall interference and boundary simulation in a transonic wind tunnel with a discretely slotted test section

A computational simulation of a transonic wind tunnel test section with longitudinally slotted walls is developed and described herein. The nonlinear slot model includes dynamic pressure effects and a plenum pressure constraint, and each slot is treated individually. The solution is performed using a finite-difference method that solves an extended transonic small disturbance equation. The walls serve as the outer boundary conditions in the relaxation technique, and an interaction procedure is used at the slotted walls. Measured boundary pressures are not required to establish the wall conditions but are currently used to assess the accuracy of the simulation. This method can also calculate a free-air solution as well as solutions that employ the classical homogeneous wall conditions. The simulation is used to examine two commercial transport aircraft models at a supercritical Mach number for zero-lift and cruise conditions. Good agreement between measured and calculated wall pressures is obtained for the model geometries and flow conditions examined herein. Some localized disagreement is noted, which is attributed to improper simulation of viscous effects in the slots.

Al-Saadi, Jassim A.↗

Probabilistic Simulation of the Human Factor in Structural Reliability

The formal approach described herein computationally simulates the probable ranges of uncertainties for the human factor in probabilistic assessments of structural reliability. Human factors such as marital status, professional status, home life, job satisfaction, work load, and health are studied by using a multifactor interaction equation (MFIE) model to demonstrate the approach. Parametric studies in conjunction with judgment are used to select reasonable values for the participating factors (primitive variables). Subsequently performed probabilistic sensitivity studies assess the suitability of the MFIE as well as the validity of the whole approach. Results show that uncertainties range from 5 to 30 percent for the most optimistic case, assuming 100 percent for no error (perfect performance).

Chamis, Christos C.↗

Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation: Second Year Progress Report

Mesh generation has long been recognized as a bottleneck in the CFD process. While much research on automating the volume mesh generation process have been relatively successful,these methods rely on appropriate initial surface triangulation to work properly. Surface discretization has been one of the least automated steps in computational simulation due to its dependence on implicitly defined CAD surfaces and curves. Differences in CAD peometry engines manifest themselves in discrepancies in their interpretation of the same entities. This lack of "good" geometry causes significant problems for mesh generators, requiring users to "repair" the CAD geometry before mesh generation. The problem is exacerbated when CAD geometry is translated to other forms (e.g., IGES )which do not include important topological and construction information in addition to entity geometry. One technique to avoid these problems is to access the CAD geometry directly from the mesh generating software, rather than through files. By accessing the geometry model (not a discretized version) in its native environment, t h s a proach avoids translation to a format which can deplete the model of topological information. Our approach to enable models developed in the Denali software environment to directly access CAD geometry and functions is through an Application Programming Interface (API) known as CAPRI. CAPRI provides a layer of indirection through which CAD-specific data may be accessed by an application program using CAD-system neutral C and FORTRAN language function calls. CAPRI supports a general set of CAD operations such as truth testing, geometry construction and entity queries.

Afjeh, Abdollah A.↗

NASA Multidimensional Stirling Convertor Code Developed

A high-efficiency Stirling Radioisotope Generator (SRG) for use on potential NASA Space Science missions is being developed by the Department of Energy, Lockheed Martin, Stirling Technology Company, and the NASA Glenn Research Center. These missions may include providing spacecraft onboard electric power for deep space missions or power for unmanned Mars rovers. Glenn is also developing advanced technology for Stirling convertors, aimed at substantially improving the specific power and efficiency of the convertor and the overall power system. Performance and mass improvement goals have been established for second- and third-generation Stirling radioisotope power systems. Multiple efforts are underway to achieve these goals, both in house at Glenn and under various grants and contracts. These efforts include the development of a multidimensional Stirling computational fluid dynamics code, high-temperature materials, advanced controllers, an end-to-end system dynamics model, low-vibration techniques, advanced regenerators, and a lightweight convertor. Under a NASA grant, Cleveland State University (CSU) and its subcontractors, the University of Minnesota (UMN) and Gedeon Associates, have developed a twodimensional computer simulation of a CSUmod Stirling convertor. The CFD-ACE commercial software developed by CFD Research Corp. of Huntsville, Alabama, is being used. The CSUmod is a scaled version of the Stirling Technology Demonstrator Convertor (TDC), which was designed and fabricated by the Stirling Technology Company and is being tested by NASA. The schematic illustrates the structure of this model. Modeled are the fluid-flow and heat-transfer phenomena that occur in the expansion space, the heater, the regenerator, the cooler, the compression space, the surrounding walls, and the moving piston and displacer. In addition, the overall heat transfer, the indicated power, and the efficiency can be calculated. The CSUmod model is being converted to a two-dimensional model of the TDC at NASA Glenn. Validation of the multidimensional Stirling code is an important part of the grant effort. UMN has been generating data in an oscillating-flow test facility using two different test sections: a 90 turn and a cooler/regenerator/heater test section. CSU has created computational fluid dynamics models of both these test sections and has been making comparisons with the data, then improving their models to improve the agreement with the test data. CSU has also been using data available in the literature for code validation. UMN is now preparing to begin fabrication of a new 180 turn test section that will be more representative of certain portions of the Stirling engine geometry. Simulations to almost periodic steady state with the two-dimensional CSUmod model indicate that, to reach periodic steady state on a single 2-GHz desktop computer, 75 to 100 complete simulation cycles would be required and between 1 and 2 months of computer time. Therefore, Glenn has purchased the first 8 computers, of a 64-computer cluster, to be run in parallel to accelerate the simulation. On the basis of CFD Research Corp.'s experience with running the parallelized version of CFD-ACE on their clusters, we estimate that the complete 64-computer cluster will reduce simulation computing time by a factor of about 40. Plans are to continue development of these multidimensional Stirling codes and to use them to study the fluid-flow and heat-transfer phenomena that occur inside Stirling convertors. This is expected to lead to improved thermodynamic loss understanding, onedimensional design and performance codes, and engine performance.

Tew, Roy C.↗

Constant-depth circuits for dynamic simulations of materials on quantum computers

Abstract Dynamic simulation of materials is a promising application for near-term quantum computers. Current algorithms for Hamiltonian simulation, however, produce circuits that grow in depth with increasing simulation time, limiting feasible simulations to short-time dynamics. Here, we present a method for generating circuits that are constant in depth with increasing simulation time for a specific subset of one-dimensional (1D) materials Hamiltonians, thereby enabling simulations out to arbitrarily long times. Furthermore, by removing the effective limit on the number of feasibly simulatable time-steps, the constant-depth circuits enable Trotter error to be made negligibly small by allowing simulations to be broken into arbitrarily many time-steps. For an N -spin system, the constant-depth circuit contains only $\mathcal {O}(N^{2})$ O ( N 2 ) CNOT gates. Such compact circuits enable us to successfully execute long-time dynamic simulation of ubiquitous models, such as the transverse field Ising and XY models, on current quantum hardware for systems of up to 5 qubits without the need for complex error mitigation techniques. Aside from enabling long-time dynamic simulations with minimal Trotter error for a specific subset of 1D Hamiltonians, our constant-depth circuits can advance materials simulations on quantum computers more broadly in a number of indirect ways.

Materials simulation↗

WE-H-BRA-04: Biological Geometries for the Monte Carlo Simulation Toolkit TOPASNBio

Purpose: New advances in radiation therapy are most likely to come from the complex interface of physics, chemistry and biology. Computational simulations offer a powerful tool for quantitatively investigating radiation interactions with biological tissue and can thus help bridge the gap between physics and biology. The aim of TOPAS-nBio is to provide a comprehensive tool to generate advanced radiobiology simulations. Methods: TOPAS wraps and extends the Geant4 Monte Carlo (MC) simulation toolkit. TOPAS-nBio is an extension to TOPAS which utilizes the physics processes in Geant4-DNA to model biological damage from very low energy secondary electrons. Specialized cell, organelle and molecular geometries were designed for the toolkit. Results: TOPAS-nBio gives the user the capability of simulating biological geometries, ranging from the micron-scale (e.g. cells and organelles) to complex nano-scale geometries (e.g. DNA and proteins). The user interacts with TOPAS-nBio through easy-to-use input parameter files. For example, in a simple cell simulation the user can specify the cell type and size as well as the type, number and size of included organelles. For more detailed nuclear simulations, the user can specify chromosome territories containing chromatin fiber loops, the later comprised of nucleosomes on a double helix. The chromatin fibers can be arranged in simple rigid geometries or within factual globules, mimicking realistic chromosome territories. TOPAS-nBio also provides users with the capability of reading protein data bank 3D structural files to simulate radiation damage to proteins or nucleic acids e.g. histones or RNA. TOPAS-nBio has been validated by comparing results to other track structure simulation software and published experimental measurements. Conclusion: TOPAS-nBio provides users with a comprehensive MC simulation tool for radiobiological simulations, giving users without advanced programming skills the ability to design and run complex simulations.

60 APPLIED LIFE SCIENCES↗

Visual Computing Environment Workshop

The Visual Computing Environment (VCE) is a framework for intercomponent and multidisciplinary computational simulations. Many current engineering analysis codes simulate various aspects of aircraft engine operation. For example, existing computational fluid dynamics (CFD) codes can model the airflow through individual engine components such as the inlet, compressor, combustor, turbine, or nozzle. Currently, these codes are run in isolation, making intercomponent and complete system simulations very difficult to perform. In addition, management and utilization of these engineering codes for coupled component simulations is a complex, laborious task, requiring substantial experience and effort. To facilitate multicomponent aircraft engine analysis, the CFD Research Corporation (CFDRC) is developing the VCE system. This system, which is part of NASA's Numerical Propulsion Simulation System (NPSS) program, can couple various engineering disciplines, such as CFD, structural analysis, and thermal analysis.

Lawrence, Charles↗

Progressive Fracture of Fiber Composite Build-Up Structures

Damage progression and fracture of built-up composite structures is evaluated by using computational simulation. The objective is to examine the behavior and response of a stiffened composite (0/ +/- 45/90)(sub s6) laminate panel by simulating the damage initiation, growth, accumulation, progression and propagation to structural collapse. An integrated computer code, CODSTRAN, was augmented for the simulation of the progressive damage and fracture of built-up composite structures under mechanical loading. Results show that damage initiation and progression have significant effect on the structural response. Influence of the type of loading is investigated on the damage initiation, propagation and final fracture of the build-up composite panel.

Gotsis, Pascal K.↗

Progressive Fracture of Fiber Composite Build-Up Structures

Damage progression and fracture of built-up composite structures is evaluated by using computational simulation. The objective is to examine the behavior and response of a stiffened composite (0 +/-45/90)(sub s6) laminate panel by simulating the damage initiation, growth, accumulation, progression and propagation to structural collapse. An integrated computer code CODSTRAN was augmented for the simulation of the progressive damage and fracture of built-up composite structures under mechanical loading. Results show that damage initiation and progression to have significant effect on the structural response. Influence of the type of loading is investigated on the damage initiation, propagation and final fracture of the build-up composite panel.

Minnetyan, Levon↗

Detached Eddy Simulation Results for a Space Launch System Configuration at Liftoff Conditions and Comparison with Experiment

Computational simulations for a Space Launch System configuration at liftoff conditions for incidence angles from 0 to 90 degrees were conducted in order to generate integrated force and moment data and longitudinal lineloads. While the integrated force and moment coefficients can be obtained from wind tunnel testing, computational analyses are indispensable in obtaining the extensive amount of surface information required to generate proper lineloads. However, beyond an incidence angle of about 15 degrees, the effects of massive flow separation on the leeward pressure field is not well captured with state of the art Reynolds Averaged Navier-Stokes methods, necessitating the employment of a Detached Eddy Simulation method. Results from these simulations are compared to the liftoff force and moment database and surface pressure data derived from a test in the NASA Langley 14- by 22-Foot Subsonic Wind Tunnel.

Computational fluid dynamics↗

On Characterization of Flow Disturbances in Arc-Jet Testing

This paper reports computational simulations and analysis of flow characterization tests in high enthalpy arc-jet facilities at NASA Ames Research Center. Flow disturbances and their characterization are presented through case studies, and their implications for testing are discussed. The case studies include free-jet test configurations from three different arc heaters and nozzles: the 60-MW IHF 30-inch conical nozzle, the 10-MW TP3 15-inch conical nozzle, and the 20-MW AHF 12-inch conical nozzle. For all cases, test articles are placed in the jet exiting the conical nozzle, and the existence of a flow disturbance is confirmed through flow survey data using pitot pressure and heat flux probes and accompanying analysis. The paper focuses on cases where the effects of the disturbances on test article surface quantities are important. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzles and test box, including the models tested. Comparisons of computations with the experimental measurements are presented. The computations that reproduce the probe sweep data approximately are essential to interpret the arc-jet test data accurately, while providing insights into several observed calorimeter anomalies caused by flow disturbances.

Arc-jet testing↗