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At least 1,045 records · Page 58

High-thermal-gradient Superalloy Crystal Growth

Single, (001)-oriented crystals of PWA 1480 were processed in alumina/silica shell molds in a laboratory high gradient furnace. The furnace employs a graphite resistance heated element, a radiation baffle, and a water cooled radiation trap below the baffle. All crystals were grown in vacuum (10 torr) and all heat transfer was radiative. The element is constructed with a variable cross section that is tapered just above the baffle to maximize heat input and therefore thermal gradient. A maximum alloy temperature of 1600 C was used. A thermal gradient of 130 deg C/cm was recorded at 1370 C just above the solidus of the PWA 1480 alloys. Crystal bars with 14.4 and 17.5 mm diameters were grown in alumina/silica shell molds. Each crystal was started from a 1.6 mm pencil seed at a rate of 76 mm/hr and slowly accelerated to a rate of 200 mm/hr under computer control. Volume percent porosity and average pore size were measured as functions of distance in representative bars. Low cycle fatigue behavior and stress rupture properties were determined.

Pearson, D. D.↗

Recursive Newton-Euler formulation of manipulator dynamics

A recursive Newton-Euler procedure is presented for the formulation and solution of manipulator dynamical equations. The procedure includes rotational and translational joints and a topological tree. This model was verified analytically using a planar two-link manipulator. Also, the model was tested numerically against the Walker-Orin model using the Shuttle Remote Manipulator System data. The hinge accelerations obtained from both models were identical. The computational requirements of the model vary linearly with the number of joints. The computational efficiency of this method exceeds that of Walker-Orin methods. This procedure may be viewed as a considerable generalization of Armstrong's method. A six-by-six formulation is adopted which enhances both the computational efficiency and simplicity of the model.

Nasser, M. G.↗

Computed torque control of a free-flying cooperat ing-arm robot

The unified approach to solving free-floating space robot manipulator end-point control problems is presented using a control formulation based on an extension of computed torque. Once the desired end-point accelerations have been specified, the kinematic equations are used with momentum conservation equations to solve for the joint accelerations in any of the robot's possible configurations: fixed base or free-flying with open/closed chain grasp. The joint accelerations can then be used to calculate the arm control torques and internal forces using a recursive order N algorithm. Initial experimental verification of these techniques has been performed using a laboratory model of a two-armed space robot. This fully autonomous spacecraft system experiences the drag-free, zero G characteristics of space in two dimensions through the use of an air cushion support system. Results of these initial experiments are included which validate the correctness of the proposed methodology. The further problem of control in the large where not only the manipulator tip positions but the entire system consisting of base and arms must be controlled is also presented. The availability of a physical testbed has brought a keener insight into the subtleties of the problem at hand.

Koningstein, Ross↗

Detailed analysis of Honeywell In-Space Accelerometer data - STS-32

The Honeywell In-Space Accelerometer (HISA) system collected data in the mid-deck area of the Shuttle Columbia during the flight of STS-32, January 1990. The resulting data were to be used to investigate the response of crystal microstructure to different types of residual acceleration. The HISA is designed to detect and record transient and oscillatory accelerations. The sampling and electronics package stored averaged accelerations over two sampling periods; two sampling rates were available: 1 Hz and 50 Hz. Analysis of the HISA data followed the CMMR Acceleration Data Processing Guide, considering in-house computer modelling of a float-zone indium crystal growth experiment. Characteristic examples of HISA data showing the response to the primary reaction control system, Orbiter Maneuvering System operations, and crew treadmill activity are presented. Various orbiter structural modes are excited by these and other activities.

Rogers, Melissa J. B.↗

Three-dimensional transient flow of spin-up in a filled cylinder with oblique gravity force

Three-dimensional transient flow profiles of spin-up in a fully liquid filled cylinder from rest with gravity acceleration at various direction are numerically simulated and studied. Particular interests are concentrated on the development of temporary reverse flow zones and Ekman layer right after the impulsive start of spin-up from rest, and decay before the flow reaching to the solid rotation. Relationship of these flow developments and differences in the Reynolds numbers of the flow and its size selection of grid points concerning the numerical instabilities of flow computations are also discussed. In addition to the gravitational acceleration along the axial direction of the cylindrical container, a series of complicated flow profiles accompanied by three-dimensional transient flows with oblique gravitational acceleration has been studies.

Hung, R. J.↗

An experimental study of the Richtmyer-Meshkov instability in microgravity

Richtmyer-Meshkov (RM) instability occurs when a planar interface separating two fluids of different density is impulsively accelerated in the direction of its normal. It is one of the most fundamental fluid instabilities and is of importance to the fields of astrophysics and inertial confinement fusion. Because RM instability experiments are normally carried out in shock tubes, where the generation of a sharp, well-controlled interface between gases is difficult, there is a scarcity of good experimental results. The experiments presented here use a novel technique that circumvents many of the experimental difficulties that have previously limited the study of RM instability in shock tubes. In these experiments, the instability is generated incompressibly, by bouncing a rectangular tank containing two liquids off of a fixed spring. These experiments, which utilize PLIF flow visualization, yield time-motion image sequences of the nonlinear development and transition to turbulence of the instability that are of a quality unattainable in shock tube experiments. Measurements obtained from these images, therefore, provide benchmark data for the evaluation of nonlinear models for the late-time growth of the instability. Because the run time in these experiments is limited, new experiments in the NASA Glenn 2.2 second drop tower, capable of achieving longer run times, are currently under way.

Rheology/methods↗

Total energy based flight control system

An integrated aircraft longitudinal flight control system uses a generalized thrust and elevator command computation (38), which accepts flight path angle, longitudinal acceleration command signals, along with associated feedback signals, to form energy rate error (20) and energy rate distribution error (18) signals. The engine thrust command is developed (22) as a function of the energy rate distribution error and the elevator position command is developed (26) as a function of the energy distribution error. For any vertical flight path and speed mode the outerloop errors are normalized (30, 34) to produce flight path angle and longitudinal acceleration commands. The system provides decoupled flight path and speed control for all control modes previously provided by the longitudinal autopilot, autothrottle and flight management systems.

Lambregts, Antonius A.↗

Enhanced Spectral Anisotropies Near the Proton-Cyclotron Scale: Possible Two-Component Structure in Hall-FLR MHD Turbulence Simulations

Recent analysis of the magnetic correlation function of solar wind fluctuations at 1 AU suggests the existence of two-component structure near the proton-cyclotron scale. Here we use two-and-one-half dimensional and three-dimensional compressible MHD models to look for two-component structure adjacent the proton-cyclotron scale. Our MHD system incorporates both Hall and Finite Larmor Radius (FLR) terms. We find that strong spectral anisotropies appear adjacent the proton-cyclotron scales depending on selections of initial condition and plasma beta. These anisotropies are enhancements on top of related anisotropies that appear in standard MHD turbulence in the presence of a mean magnetic field and are suggestive of one turbulence component along the inertial scales and another component adjacent the dissipative scales. We compute the relative strengths of linear and nonlinear accelerations on the velocity and magnetic fields to gauge the relative influence of terms that drive the system with wave-like (linear) versus turbulent (nonlinear) dynamics.

Ghosh, Sanjoy↗

Time-Varying Changes in the Simulated Structure of the Brewer-Dobson Circulation

A series of simulations using the NASA Goddard Earth Observing System Chemistry Climate Model are analyzed in order to assess changes in the Brewer-Dobson Circulation (BDC) over the past 55 years. When trends are computed over the past 55 years, the BDC accelerates throughout the stratosphere, consistent with previous modeling results. However, over the second half of the simulations (i.e., since the late 1980s), the model simulates structural changes in the BDC as the temporal evolution of the BDC varies between regions in the stratosphere. In the mid-stratosphere in the midlatitude Northern Hemisphere, the BDC does not accelerate in the ensemble mean of our simulations despite increases in greenhouse gas concentrations and warming sea surface temperatures, and it even decelerates in one ensemble member. This deceleration is reminiscent of changes inferred from satellite instruments and in situ measurements. In contrast, the BDC in the lower stratosphere continues to accelerate. The main forcing agents for the recent slowdown in the mid-stratosphere appear to be declining ozone-depleting substance (ODS) concentrations and the timing of volcanic eruptions. Changes in both mean age of air and the tropical upwelling of the residual circulation indicate a lack of recent acceleration. We therefore clarify that the statement that is often made that climate models simulate a decreasing age throughout the stratosphere only applies over long time periods and is not necessarily the case for the past 25 years, when most tracer measurements were taken.

stratospheric ozone↗

Importance of Ice Nucleation and Precipitation on Climate With the Parameterization of Unified Microphysics Across Scales Version 1 (PUMASv1)

Cloud microphysics is critical for weather and climate prediction. In this work, we document updates and corrections to the cloud microphysical scheme used in the Community Earth System Model (CESM) and other models. These updates include a new nomenclature for the scheme, now called Parameterization of Unified Microphysics Across Scales (PUMAS), and the ability to run the scheme on graphics processing units (GPUs). The main science changes include refactoring an ice number limiter and associated changes to ice nucleation, adding vapor deposition onto snow, and introducing an implicit numerical treatment for sedimentation. We also detail the improvements in computational performance that can be achieved with GPU acceleration. We then show the impact of these scheme changes on the (a) mean state climate, (b) cloud feedback response to warming, and (c) aerosol forcing. We find that corrections are needed to the immersion freezing parameterization and that ice nucleation has important impacts on climate. We also find that the revised scheme produces less cloud liquid and ice but that this can be adjusted by changing the loss process for cloud liquid (autoconversion). Furthermore, there are few discernible effects of the PUMAS changes on cloud feedbacks but some reductions in the magnitude of aerosol–cloud interactions (ACIs). Small cloud feedback changes appear to be related to the implicit sedimentation scheme, with a number of factors affecting ACIs.

Clouds↗

McMillan map and nonlinear Twiss parameters

In this article we consider two dynamical systems: the McMillan sextupole and octupole integrable mappings originally introduced by Edwin McMillan; the second one is also known as canonical McMillan map. Both of them are simplest symmetric McMillan maps with only one intrinsic parameter, the trace of the Jacobian at the fixed point. While these dynamical systems have numerous of applications and are used in many areas of math and physics, some of their dynamical properties have not been described yet. We fulfill the gap and provide complete description of all stable trajectories including parametrization of invariant curves, Pioncaré rotation numbers and canonical action-angle variables. In the second part we relate these maps with general chaotic map in McMillan-Turaev form. We show that McMillan sextupole and octupole mappings are first order approximations of dynamics around the fixed point, in a similar way as linear map and quadratic invariant (Courant-Snyder invariant in accelerator physics) is the zeroth order approximation (known as linearization). Finally we suggest the new formalism of nonlinear Twiss parameters which incorporate dependence of rotation number as a function of amplitude, in contrast to e.g. betatron phase advance used in accelerator physics which is independent of amplitude. Specifically in application to accelerator physics this new formalism is capable of predicting dynamical aperture around 1-st, 2-nd, 3-rd and 4-th order resonances for flat beams, which is critical for beam injection/extraction.

43 PARTICLE ACCELERATORS↗

CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our approach formulates catalyst discovery as an uncertain environment where an agent actively searches for highly effective catalysts via the iterative combination of large language model (LLM)-derived hypotheses and atomistic graph neural network (GNN)-derived feedback. Identified catalysts in intermediate search steps undergo structural evaluation based on spatial orientation, reaction pathways, and stability. Scoring functions based on adsorption energies and barriers steer the exploration in the LLM's knowledge space toward energetically favorable, high-efficiency catalysts. We introduce planning methods that automatically guide the exploration without human input, providing competitive performance against expert-enumerated chemical descriptor-based implementations. By integrating language-guided reasoning with computational chemistry feedback, our work pioneers AI-accelerated, trustworthy catalyst discovery.

artificial intelligence↗

Transonic Navier-Stokes solutions about a generic hypersonic configuration

Three-dimensional transonic viscous flow computations are presented for a generic high-speed accelerator model that includes wing, body, fillets, and a no-flow-through engine nacelle. Solutions are obtained from an algorithm for the compressible Navier-Stokes equations that incorporates an upwind-biased, flux-vector-splitting approach along with longitudinally patched grids. Results are presented for fully turbulent flow assumptions and include correlations with wind-tunnel data. A good quantitative agreement for the forebody surface pressure distribution is achieved between computations and the available wind-tunnel measurements at M∞ = 0.9. Furthermore, it is demonstrated that the flow is stagnating around the boattail region due to separation from the aft-engine cowl lip.

Hypersonic flows↗

AI Denoising to Accelerate Detector Simulation

Detector simulation is critical to experimental HEP; however this simulation (commonly done through toolkits such as Geant4) is computationally intensive. Performance can be improved somewhat through technical optimization, but more is needed. Using machine learning (ML) to accelerate simulation is a promising field, however efforts to use generative adversarial networks (GANs) or optimized autoencoders have faced issues. Using convolutional neural networks (CNNs) for denoising has been successful in non-HEP applications such as image processing. This poster investigates the efficacy of using CNNs to denoise Geant4 simulations. This could increase the accuracy of simulations performed under settings designed to increase computational efficiency.

Franklin, Lena↗

Ensemble Simulations on Leadership Computing Systems

Scientific productivity can be enhanced through workflow management tools, relieving large High Performance Computing (HPC) system users from the tedious tasks of scheduling and designing the complex computational execution of scientific applications. This paper presents a study on the usage of ensemble workflow tools to accelerate science using the Summit and Frontier supercomputing systems. The research aims to connect science domain simulations using Oak Ridge Leadership Computing Facility (OLCF) supercomputing platforms with ensemble workflow methods in order to accelerate HPC-enabled discovery and boost scientific impact. We present the coupling, porting and optimization of Radical-Cybertools on three applications: Chroma, NAMD and LAMMPS. The tools augment traditional HPC monolithic runs with a pilot scheduler. Lessons-learned are discussed for physics, biology and materials science applications. We discuss intrinsic limitations of coupling and porting ensemble workflow tools to applications that run on large HPC systems. The origins of technical challenges and their solutions developed during the implementation process are discussed. Data management strategies, OLCF’s policies for ensembles, and natively supported workflow tools are also summarized.

Georgiadou, Antigoni [ORNL] (ORCID:000000020977631↗

IRIS-MASH: Efficient Multi-device Asynchronous Multi-Stream Heterogeneous Computing

In the rapidly evolving field of high-performance computing (HPC), effectively leveraging heterogeneous devices through asynchronous task programming is paramount. This paper presents a robust asynchronous task programming model tailored for a multi-device, multi-stream execution environment that incorporates a diverse array of heterogeneous computing units, including GPUs from various vendors and other accelerators. Current state-of-the-art task programming models provide methodologies to support asynchronous task executions, but they typically handle homogeneous devices using native programming languages, while support for heterogeneous devices is limited to frameworks like OpenCL. This gap presents significant challenges in abstracting heterogeneous devices to harness their true asynchronous capabilities effectively using their native programming languages. By implementing asynchronous task execution, our model significantly boosts the performance of tiled algorithm task graphs through overlapping data transfers with computation and enabling the simultaneous execution of multiple kernels. We integrate this approach into a heterogeneous Intelligent Runtime System (IRIS) and assess its performance using a suite of tiled algorithm benchmarks from the heterogeneous math kernels library (MatRIS) based on IRIS. Experimental results demonstrate a performance improvement ranging from 1.6 × to 2 × over IRIS without asynchronous support, and a notable 22% performance enhancement compared to established runtime systems such as StarPU and PaRSEC. This approach significantly improves computation efficiency of HPC workflows and provides a solid base for future exploration and development in the area of asynchronous task programming in heterogeneous systems.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗

JACC.shared: Leveraging HPC Metaprogramming and Performance Portability for Computations That Use Shared Memory GPUs

In this work, we present JACC.shared, a new feature of Julia for ACCelerators (JACC), which is the performanceportable and metaprogramming model of the just-in-time and LLVM-based Julia language. This new feature allows JACC applications to leverage the high-performance computing (HPC) capabilities of high-bandwidth, on-chip GPU memory. Historically, exploiting high-bandwidth, shared-memory GPUs has not been a priority for high-level programming solutions. JACC.shared covers that gap for the first time, thereby providing a highlevel, portable, and easy-to-use solution for programmers to exploit this memory and supporting all current major accelerator architectures. Well-known HPC and AI workloads, such as multi/hyperspectral imaging and AI convolutions, have been used to evaluate JACC.shared on two exascale GPU architectures hosted by some of the most powerful US Department of Energy supercomputers: Perlmutter (NVIDIA A100) and Frontier (AMD MI250X). The performance evaluation reports speedup of up to 3.5× by adding only one line of code to the base codes, thus providing important accelerators in a simple, portable, and transparent way and elevating the programming productivity and performance-portability capabilities for Julia/JACC HPC, AI, and scientific applications.

Valero Lara, Pedro [ORNL] (ORCID:0000000214794310)↗