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At least 1,099 records · Page 61

Towards Autonomous Experiments by Connecting High Performance Microscopy with High Performance Computing

The digitization of controls, data, and analysis in microscopy is bringing the idea of autonomous microscopes closer to reality than ever before. Automated transmission electron microscopy (TEM) is already fairly routine for some experiments the only require simple repetitive tasks such as imaging biological macromolecules for single particle cryoEM [1], tilt series for electron tomography [2], and movies for crystallography [3]. The vast majority of TEM experiments are conducted completely by human operators who choose the regions of interest, optimize experimental parameters, and make decisions about data quality visually during an experiment. The field is still a long way from having completely autonomous TEMs that can adapt to sample difficulties and tune experimental parameters based on data quality and desired experimental outcomes. Part of the issue is the lack of capability for feeding information learned from on-line, live data analysis back into the on-going experiment [4]. Furthermore, this presentation will discuss current capabilities for large scale data reduction and analysis using high performance computing (i.e. supercomputing) and progress towards developing a true feed-back loop that places data analysis and theory in the experimental loop.

97 MATHEMATICS AND COMPUTING↗

A computational study of the flowfield surrounding the Aeroassist Flight Experiment vehicle

A symmetric total variation diminishing (STVD) algorithm has been applied to the solution of the three-dimensional hypersonic flowfield surrounding the Aeroassist Flight Experiment (AFE) vehicle. Both perfect-gas and chemical nonequilibrium models have been used. The perfect-gas flows were computed at two different Reynolds numbers, including a flight trajectory point at maximum dynamic pressure, and on two different grids. Procedures for coupling the solution of the species continuity equations with the Navier-Stokes equations in the presence of chemical nonequilibrium are reviewed and tested on the forebody of the AFE and on the complete flowfield assuming noncatalytic wall and no species diffusion. Problems with the STVD algorithm unique to flows with variable thermodynamic properties (real gas) are identified and algorithm modifications are suggested. A potential heating problem caused by strong flow impingement on the nozzle lip in the near wake at 0-deg angle of attack has been identified.

Gnoffo, Peter A.↗

PQML: Enabling the Predictive Reproducibility on NISQ Machines for Quantum ML Applications

Quantum computing represents a groundbreaking approach to high-performance computing. In recent years, quantum computers have progressed from single-qubit processors to systems boasting over 400 qubits. The presence of such a large number of qubits offers significant advantages, including enhanced computational speed—a capability beyond classical computing methods. However, the current stage of quantum computing is referred to as the noisy intermediate-scale quantum (NISQ) era. The existence of noise in this era presents challenges in testing quantum computing applications, leading to considerable variance in application results. Furthermore, the diverse noise characteristics observed across different machines exacerbate this issue, complicating the selection of the appropriate machine for application execution. In response to these challenges, we introduce our Predictive Quantum Machine Learning (PQML) tool. This tool is designed to predict outcomes when executing identical quantum machine learning applications—specifically, a critical suite of variational quantum algorithms—across various quantum computers during the NISQ era. This effort relies on data collected over a 12-month period. To the best of our knowledge, this study represents the first attempt to ensure reproducibility across quantum computers for complex circuits. Additionally, we have developed a model capable of forecasting the accuracy of quantum computers for variational quantum algorithms, with a particular emphasis on quantum machine learning as a case study.

Senapati, Priyabrata [Kent State University]↗

Mechanical Prototyping and Manufacturing Internship

The internship was located at the Johnson Space Center (JSC) Innovation Design Center (IDC), which is a facility where the JSC workforce can meet and conduct hands-on innovative design, fabrication, evaluation, and testing of ideas and concepts relevant to NASA's mission. The tasks of the internship included mechanical prototyping design and manufacturing projects in service of research and development as well as assisting the users of the IDC in completing their manufacturing projects. The first project was to manufacture hatch mechanisms for a team in the Systems Engineering and Project Advancement Program (SETMAP) hexacopter competition. These mechanisms were intended to improve the performance of the servomotors and offer an access point that would also seal to prevent cross-contamination. I also assisted other teams as they were constructing and modifying their hexacopters. The success of this competition demonstrated a proof of concept for aerial reconnaissance and sample return to be potentially used in future NASA missions. I also worked with Dr. Kumar Krishen to prototype an improved thermos and a novel, portable solar array. Computer-aided design (CAD) software was used to model the parts for both of these projects. Then, 3D printing as well as conventional techniques were used to produce the parts. These prototypes were then subjected to trials to determine the success of the designs. The solar array is intended to work in a cluster that is easy to set up and take down and doesn't require powered servomechanisms. It could be used terrestrially in areas not serviced by power grids. Both projects improve planetary exploration capabilities to future astronauts. Other projects included manufacturing custom rail brackets for EG-2, assisting engineers working on underwater instrument and tool cases for the NEEMO project, and helping to create mock-up parts for Space Center Houston. The use of the IDC enabled efficient completion of these projects at significantly reduced cost. I acquired and improved manufacturing and prototyping skills during my tour including learning about a CAD (Computer-Aided Design) program called Creo (Creo Parametric; design software), gaining valuable conventional machining experience with lathes, CNC (Computer Numerical Control) milling machines and various other tools, and improving my engineering project communication and collaboration skills. The internship also allowed me to better understand operations at NASA. I plan to work in the aerospace industry or do academic research benefitting space science and exploration, and this internship experience will enable me to have insight into manufacturing processes for research and development.

Grenfell, Peter↗

Non-smooth Bayesian optimization in tuning scientific applications

Tuning algorithmic parameters to optimize the performance of large, complicated computational codes is an important problem involving finding the optima and identifying regimes defined by non-smooth boundaries in black-box functions. Within the Bayesian optimization framework, the Gaussian process surrogate model produces smooth mean functions, but functions in the tuning problem are often non-smooth, which is exacerbated by the fact that we usually have limited sequential samples from the black-box function. Here, motivated by these issues encountered in tuning, we propose a novel Gaussian process model called a clustered Gaussian process (cGP), where the components are dynamically updated by clustering. In our studies, the performance of cGP can be better than stationary GPs in nearly 90% of the experiments and better than non-stationary GPs in nearly 70% of the repeated experiments while requiring less computational cost. cGP provides a novel approach for dynamic GP, computes more efficiently than recursive partitioning, and discovers non-smoothness regimes. We provide extensive experiments including high-performance computing (HPC) and industrial simulation functions to show the effectiveness of our methods.

97 MATHEMATICS AND COMPUTING↗

Why Dissolving Salt in Water Decreases Its Dielectric Permittivity

The dielectric permittivity of salt water decreases on dissolving more salt. For nearly a century, this phenomenon has been explained by invoking saturation in the dielectric response of the solvent water molecules. Herein, we employ an advanced deep neural network (DNN), built using data from density functional theory, to study the dielectric permittivity of sodium chloride solutions. Notably, the decrease in the dielectric permittivity as a function of concentration, computed using the DNN approach, agrees well with experiments. Detailed analysis of the computations reveals that the dominant effect, caused by the intrusion of ionic hydration shells into the solvent hydrogen-bond network, is the disruption of dipolar correlations among water molecules. Accordingly, the observed decrease in the dielectric permittivity is mostly due to increasing suppression of the collective response of solvent waters.

74 ATOMIC AND MOLECULAR PHYSICS↗

Big PanDa Workflow Management on Titan for High Energy and Nuclear Physics and for Future Extreme Scale Scientific Application

Over a three year period, from 2016-2019, this project demonstrated the scientific benefits of integrating the Titan supercomputer at Oak Ridge Leadership Computing Facility into traditional high throughput grid based distributed computing systems managed by PanDA, the workflow management system used for the execution of all distributed computing applications by the ATLAS experiment at the Large Hadron Collider. PanDA manages millions of batch jobs daily at hundreds of clusters worldwide on request by thousands of physicist users, and processes more than an exabyte of data annually using grid middleware. High levels of operational use of Titan was sustained by PanDA in order to meet the physics goals of ATLAS. The success of this project led to the use of other supercomputers worldwide by ATLAS, and to the adoption of PanDA by other experiments and other scientists. Multiple innovative operational and computer science research goals were achieved supporting the use of supercomputers for scientific domains with large scale distributed data and distributed processing needs.

97 MATHEMATICS AND COMPUTING↗

Theoretical study of the dissociation energy and the red and violet band systems of CN

The dissociation energy (D sub O) of CN is determined to be 7.65 + or - 0.06 eV. This corresponds to delta H sub f (CN) = 105.3 + or - 1.5 kcal/mole, in excellent agreement with Engleman and Rouse (1975), but considerably larger than the recent value deduced from shock-tube studies by Colket (1984). The result is obtained not only from extensive ab initio MRCI calculations using a very large Gaussian basis set, but also from extrapolation of the directly computed value by comparison of computed and experimental results fo NO, C2, and N2. As an additional calibration of the methods, the D sub O value for CN was computed from the corresponding value for CN(-) using the experimental electron affinity data. The lifetime of the nu prime = 0 level of the violet (B 2 sigma + yields X 2 sigma +) system was computed to be 62.4 ns, in good agreement with both experiment and previous calculations. Lifetimes for the red (A 2 pi yields X 2 sigma +) system decrease with increasing nu prime, which is consistent both with the recent experiment and calculations. While the computed lifetimes are significantly longer that those obtained from the experiment, they are shorter than those deduced from an analysis of the solar spectrum. However the D sub O and f (sub OO) are consistent with Lambert's model for the solar spectrum.

Bauschlicher, Charles W., Jr.↗

DUNE Software and High Performance Computing

DUNE, like other HEP experiments, faces a challenge related to matching execution patterns of our production simulation and data processing software to the limitations imposed by modern high-performance computing facilities. In order to efficiently exploit these new architectures, particularly those with high CPU core counts and GPU accelerators, our existing software execution models require adaptation. In addition, the large size of individual units of raw data from the far detector modules pose an additional challenge somewhat unique to DUNE. Here we describe some of these problems and how we begin to solve them today with existing software frameworks and toolkits. We also describe ways we may leverage these existing software architectures to attack remaining problems going forward. This whitepaper is a contribution to the Computational Frontier of Snowmass21.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Numerical Evaluation of Icing Effects on a Natural Laminar Flow Airfoil

As a part of CFD code validation efforts within the Icing Branch of NASA Glenn Research Center, computations were performed for natural laminar flow (NLF) airfoil, NLF-0414. with 6 and 22.5 minute ice accretions. Both 3-D ice castings and 2-D machine-generated ice shapes were used in wind tunnel tests to study the effects of natural ice is well as simulated ice. They were mounted in the test section of the Low Turbulence Pressure Tunnel (LTPT) at NASA Langley that the 2-dimensionality of the flow can be maintained. Aerodynamic properties predicted by computations were compared to data obtained through the experiment by the authors at the LTPT. Computations were performed only in 2-D and in the case of 3-D ice, the digitized ice shape obtained at one spanwise location was used. The comparisons were mainly concentrated on the lift characteristics over Reynolds numbers ranging from 3 to 10 million and Mach numbers ranging from 0.12 to 0.29. WIND code computations indicated that the predicted stall angles were in agreement with experiment within one or two degrees. The maximum lift values obtained by computations were in good agreement with those of the experiment for the 6 minute ice shapes and the minute 3-D ice, but were somewhat lower in the case of the 22.5 minute 2-D ice. In general, the Reynolds number variation did not cause much change in the lift values while the variation of Mach number showed more change in the lift. The Spalart-Allmaras (S-A) turbulence model was the best performing model for the airfoil with the 22.5 minute ice and the Shear Stress Turbulence (SST) turbulence model was the best for the airfoil with the 6 minute ice and also for the clean airfoil. The pressure distribution on the surface of the iced airfoil showed good agreement for the 6 minute ice. However, relatively poor agreement of the pressure distribution on the upper surface aft of the leading edge horn for the 22.5 minute ice suggests that improvements are needed in the grid or turbulence models.

Chung, James J.↗

Open-Loop HIRF Experiments Performed on a Fault Tolerant Flight Control Computer

During the third quarter of 1996, the Closed-Loop Systems Laboratory was established at the NASA Langley Research Center (LaRC) to study the effects of High Intensity Radiated Fields on complex avionic systems and control system components. This new facility provided a link and expanded upon the existing capabilities of the High Intensity Radiated Fields Laboratory at LaRC that were constructed and certified during 1995-96. The scope of the Closed-Loop Systems Laboratory is to place highly integrated avionics instrumentation into a high intensity radiated field environment, interface the avionics to a real-time flight simulation that incorporates aircraft dynamics, engines, sensors, actuators and atmospheric turbulence, and collect, analyze, and model aircraft performance. This paper describes the layout and functionality of the Closed-Loop Systems Laboratory, and the open-loop calibration experiments that led up to the commencement of closed-loop real-time flight experiments.

Koppen, Daniel M.↗

Monte Carlo Simulations of the Water Draining Experiment of Giacint Critical Assembly

The MCNP6 computer program has been successfully extended to simulate reactor dynamics problems with moving parts of the geometries. Different from the dynamic method developed in other Monte Carlo codes, a movement scheme has been developed to account for the geometrical parts motion during the particle random walk. The MCNP6 computer program has been used to simulate two transient experiments of the Giacint critical assembly. The MCNP6 calculated total neutron flux was compared with that from the Serpent simulation. An excellent agreement was obtained between the results of the two Monte Caro computer programs. The MCNP6 calculated total neutron flux was also compared with the two measured transients. The MCNP6 results predicted a faster transient than the experimental data. The MCNP6 transient simulation was improved with an adjusted geometrical model which shifts the fuel rods slightly to match the measured reactivity worth due to the drained water. (c) 2021 Elsevier Ltd. All rights reserved.

MCNP, Moving Geometries, Monte Carlo Reactor Trans↗

RANS Modeling of Benchmark Shockwave / Boundary Layer Interaction Experiments

This presentation summarizes the computations of a set of shock wave / turbulent boundary layer interaction (SWTBLI) test cases using the Wind-US code, as part of the 2010 American Institute of Aeronautics and Astronautics (AIAA) shock / boundary layer interaction workshop. The experiments involve supersonic flows in wind tunnels with a shock generator that directs an oblique shock wave toward the boundary layer along one of the walls of the wind tunnel. The Wind-US calculations utilized structured grid computations performed in Reynolds-averaged Navier-Stokes mode. Three turbulence models were investigated: the Spalart-Allmaras one-equation model, the Menter Shear Stress Transport wavenumber-angular frequency two-equation model, and an explicit algebraic stress wavenumber-angular frequency formulation. Effects of grid resolution and upwinding scheme were also considered. The results from the CFD calculations are compared to particle image velocimetry (PIV) data from the experiments. As expected, turbulence model effects dominated the accuracy of the solutions with upwinding scheme selection indicating minimal effects.!

Georgiadis, Nick↗

A learning controller for nonrepetitive robotic operation

A practical learning control system is described which is applicable to complex robotic and telerobotic systems involving multiple feedback sensors and multiple command variables. In the controller, the learning algorithm is used to learn to reproduce the nonlinear relationship between the sensor outputs and the system command variables over particular regions of the system state space, rather than learning the actuator commands required to perform a specific task. The learned information is used to predict the command signals required to produce desired changes in the sensor outputs. The desired sensor output changes may result from automatic trajectory planning or may be derived from interactive input from a human operator. The learning controller requires no a priori knowledge of the relationships between the sensor outputs and the command variables. The algorithm is well suited for real time implementation, requiring only fixed point addition and logical operations. The results of learning experiments using a General Electric P-5 manipulator interfaced to a VAX-11/730 computer are presented. These experiments involved interactive operator control, via joysticks, of the position and orientation of an object in the field of view of a video camera mounted on the end of the robot arm.

Miller, W. T., III↗

Finite-difference fluid dynamics computer mathematical models for the design and interpretation of experiments for space flight

Numerical methods are used to design a spherical baroclinic flow model experiment of the large scale atmosphere flow for Spacelab. The dielectric simulation of radial gravity is only dominant in a low gravity environment. Computer codes are developed to study the processes at work in crystal growing systems which are also candidates for space flight. Crystalline materials rarely achieve their potential properties because of imperfections and component concentration variations. Thermosolutal convection in the liquid melt can be the cause of these imperfections. Such convection is suppressed in a low gravity environment. Two and three dimensional finite difference codes are being used for this work. Nonuniform meshes and implicit iterative methods are used. The iterative method for steady solutions is based on time stepping but has the options of different time steps for velocity and temperature and of a time step varying smoothly with position according to specified powers of the mesh spacings. This allows for more rapid convergence. The code being developed for the crystal growth studies allows for growth of the crystal as the solid-liquid interface. The moving interface is followed using finite differences; shape variations are permitted. For convenience in applying finite differences in the solid and liquid, a time dependent coordinate transformation is used to make this interface a coordinate surface.

Roberts, G. O.↗

Simulations of the monthly mean atmosphere for February 1976 with the GISS model

Monthly mean simulations of the global atmosphere were computed for February 1976 with the GISS model from observed initial conditions. In a replication experiment, two of these computations generated slightly different monthly mean states, apparently due to the schedule of interruptions on the computer. The root-mean-square errors of replication over the Northern Hemisphere were found to be about 2 mb, 20 m, and 1 K for sea-level pressure, 500 mb height, and 850 mb temperature, respectively. The monthly mean 500 mb forecast results for February 1976 over the Northern Hemisphere were consistent with those from earlier GISS model experiments.

Spar, J.↗

NASCAP simulation of PIX 2 experiments

The latest version of the NASCAP/LEO digital computer code used to simulate the PIX 2 experiment is discussed. NASCAP is a finite-element code and previous versions were restricted to a single fixed mesh size. As a consequence the resolution was dictated by the largest physical dimension to be modeled. The latest version of NASCAP/LEO can subdivide selected regions. This permitted the modeling of the overall Delta launch vehicle in the primary computational grid at a coarse resolution, with subdivided regions at finer resolution being used to pick up the details of the experiment module configuration. Langmuir probe data from the flight were used to estimate the space plasma density and temperature and the Delta ground potential relative to the space plasma. This information is needed for input to NASCAP. Because of the uncertainty or variability in the values of these parameters, it was necessary to explore a range around the nominal value in order to determine the variation in current collection. The flight data from PIX 2 were also compared with the results of the NASCAP simulation.

Roche, J. C.↗