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At least 739 records · Page 41

Automating CapCom Using Mobile Agents and Robotic Assistants

We have developed and tested an advanced EVA communications and computing system to increase astronaut self-reliance and safety, reducing dependence on continuous monitoring and advising from mission control on Earth. This system, called Mobile Agents (MA), is voice controlled and provides information verbally to the astronauts through programs called personal agents. The system partly automates the role of CapCom in Apollo-including monitoring and managing EVA navigation, scheduling, equipment deployment, telemetry, health tracking, and scientific data collection. EVA data are stored automatically in a shared database in the habitat/vehicle and mirrored to a site accessible by a remote science team. The program has been developed iteratively in the context of use, including six years of ethnographic observation of field geology. Our approach is to develop automation that supports the human work practices, allowing people to do what they do well, and to work in ways they are most familiar. Field experiments in Utah have enabled empirically discovering requirements and testing alternative technologies and protocols. This paper reports on the 2004 system configuration, experiments, and results, in which an EVA robotic assistant (ERA) followed geologists approximately 150 m through a winding, narrow canyon. On voice command, the ERA took photographs and panoramas and was directed to move and wait in various locations to serve as a relay on the wireless network. The MA system is applicable to many space work situations that involve creating and navigating from maps (including configuring equipment for local topology), interacting with piloted and unpiloted rovers, adapting to environmental conditions, and remote team collaboration involving people and robots.

Clancey, William J.↗

Constraints and Opportunities in GCM Model Development

Over the past 30 years climate models have evolved from relatively simple representations of a few atmospheric processes to complex multi-disciplinary system models which incorporate physics from bottom of the ocean to the mesopause and are used for seasonal to multi-million year timescales. Computer infrastructure over that period has gone from punchcard mainframes to modern parallel clusters. Constraints of working within an ever evolving research code mean that most software changes must be incremental so as not to disrupt scientific throughput. Unfortunately, programming methodologies have generally not kept pace with these challenges, and existing implementations now present a heavy and growing burden on further model development as well as limiting flexibility and reliability. Opportunely, advances in software engineering from other disciplines (e.g. the commercial software industry) as well as new generations of powerful development tools can be incorporated by the model developers to incrementally and systematically improve underlying implementations and reverse the long term trend of increasing development overhead. However, these methodologies cannot be applied blindly, but rather must be carefully tailored to the unique characteristics of scientific software development. We will discuss the need for close integration of software engineers and climate scientists to find the optimal processes for climate modeling.

Schmidt, Gavin↗

Recent Advances in Solar Sail Propulsion Systems at NASA

Supporting NASA's Science Mission Directorate, the In-Space Propulsion Technology Program is developing solar sail propulsion for use in robotic science and exploration of the solar system. Solar sail propulsion has the potential to provide longer on-station operation, increased scientific payload mass fraction, and access to previously inaccessible orbits for multiple potential science missions. Two different 20-meter solar sail systems were produced and successfully completed functional vacuum testing last year in NASA Glenn s Space Power Facility at Plum Brook Station Ohio. The sails were designed and developed by ATK Space Systems and L'Garde, respectively. The sail systems consist of a central structure with four deployable booms that support the sails. The sail designs are robust enough for deployments in a one atmosphere, one gravity environment and are scalable to much larger solar sails - perhaps as large as 150 meters on a side. In addition, computational modeling and analytical simulations have been performed to assess the scalability of the technology to the large sizes (150 meters) required to implement the first generation of missions using solar sails. Life and space environmental effects testing of sail and component materials are also nearly complete. This paper will summarize recent technology advancements in solar sails and their successful ambient and vacuum environment testing.

Johnson, Les↗

Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions

We discuss the challenges and propose research directions for using AI to revolutionize the development of high-performance computing (HPC) software. AI technologies, in particular large language models, have transformed every aspect of software development. For its part, HPC software is recognized as a highly specialized scientific field of its own. We discuss the challenges associated with leveraging state-of-the-art AI technologies to develop such a unique and niche class of software and outline our research directions in the two US Department of Energy–funded projects for advancing HPC Software via AI: Ellora and Durban.

Teranishi, Keita [ORNL] (ORCID:0000000166472690)↗

TAMM: Tensor algebra for many-body methods

Tensor algebra operations such as contractions in computational chemistry consume a significant fraction of the computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous computing platforms. In this paper, we present Tensor Algebra for Many-body Methods (TAMM), a framework for productive and performance-portable development of scalable computational chemistry methods. TAMM decouples the specification of the computation from the execution of these operations on available high-performance computing systems. With this design choice, the scientific application developers (domain scientists) can focus on the algorithmic requirements using the tensor algebra interface provided by TAMM, whereas high-performance computing developers can direct their attention to various optimizations on the underlying constructs, such as efficient data distribution, optimized scheduling algorithms, and efficient use of intra-node resources (e.g., graphics processing units). The modular structure of TAMM allows it to support different hardware architectures and incorporate new algorithmic advances. We describe the TAMM framework and our approach to the sustainable development of scalable ground- and excited-state electronic structure methods. We present case studies highlighting the ease of use, including the performance and productivity gains compared to other frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Realization and Calibration of Continuously Parameterized Two-Qubit Gates on a Trapped-Ion Quantum Processor

Continuously parameterized two-qubit gates are a key feature of state-of-the-art trapped-ion quantum processors, as they have favorable error scalings and show distinct improvements in circuit performance over more restricted maximally entangling gatesets. In this work, we provide a comprehensive and pedagogical discussion on how to practically implement these continuously parameterized Mølmer–Sørensen gates on the Quantum Scientific Computing Open User Testbed, a low-level trapped-ion processor. To generate the arbitrary entangling angles, θ, we simply scale the amplitude of light used to generate the entanglement. However, doing so requires careful consideration of amplifier saturation as well as the variable light shifts that result. As such, we describe a method to calibrate and cancel the dominant fourth-order effects, followed by a dynamic virtual phase advance during the gate to cancel any residual light shifts, and find a linear scaling between θ and the residual light shift. Once we have considered and calibrated these effects, we demonstrate performance improvement with decreasing θ. Finally, we describe nuances of hardware control to transform the XX-type interaction of the arbitrary-angle Mølmer–Sørensen gate into a phase-agnostic and crosstalk-mitigating ZZ interaction.

Yale, Christopher Gordon [Sandia National Laborato↗

NASA high performance computing and communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 100-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientist's abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects as well as summaries of individual research and development programs within each project.

Holcomb, Lee↗

NASA High Performance Computing and Communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 1(X)-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientists' abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project, exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects, as well as summaries of early accomplishments and the significance, status, and plans for individual research and development programs within each project. Areas of emphasis include benchmarking, testbeds, software and simulation methods.

Holcomb, Lee↗

Mathematical and Computational Challenges in Population Biology and Ecosystems Science

Mathematical and computational approaches provide powerful tools in the study of problems in population biology and ecosystems science. The subject has a rich history intertwined with the development of statistics and dynamical systems theory, but recent analytical advances, coupled with the enhanced potential of high-speed computation, have opened up new vistas and presented new challenges. Key challenges involve ways to deal with the collective dynamics of heterogeneous ensembles of individuals, and to scale from small spatial regions to large ones. The central issues-understanding how detail at one scale makes its signature felt at other scales, and how to relate phenomena across scales-cut across scientific disciplines and go to the heart of algorithmic development of approaches to high-speed computation. Examples are given from ecology, genetics, epidemiology, and immunology.

Levin, Simon A.↗

Forming IDEAS: Interactive Data Exploration & Analysis System

Modern cyber security operations collect an enormous amount of logging and alerting data. While analysts have the ability to query and compute simple statistics and plots from their data, current analytical tools are too simple to admit deep understanding. To detect advanced and novel attacks, analysts turn to manual investigations. While commonplace, current investigations are time-consuming, intuition-based, and proving insufficient. Our hypothesis is that arming the analyst with easy-to-use data science tools will increase their work efficiency, provide them with the ability to resolve hypotheses with scientific inquiry of their data, and support their decisions with evidence over intuition. To this end, we present our work to build IDEAS (Interactive Data Exploration and Analysis System). We present three real-world use-cases that drive the system design from the algorithmic capabilities to the user interface. Finally, a modular and scalable software architecture is discussed along with plans for our pilot deployment with a security operation command.

Bridges, Robert↗

Integrated Hardware and Software for No-Loss Computing

When an algorithm is distributed across multiple threads executing on many distinct processors, a loss of one of those threads or processors can potentially result in the total loss of all the incremental results up to that point. When implementation is massively hardware distributed, then the probability of a hardware failure during the course of a long execution is potentially high. Traditionally, this problem has been addressed by establishing checkpoints where the current state of some or part of the execution is saved. Then in the event of a failure, this state information can be used to recompute that point in the execution and resume the computation from that point. A serious problem arises when one distributes a problem across multiple threads and physical processors is that one increases the likelihood of the algorithm failing due to no fault of the scientist but as a result of hardware faults coupled with operating system problems. With good reason, scientists expect their computing tools to serve them and not the other way around. What is novel here is a unique combination of hardware and software that reformulates an application into monolithic structure that can be monitored in real-time and dynamically reconfigured in the event of a failure. This unique reformulation of hardware and software will provide advanced aeronautical technologies to meet the challenges of next-generation systems in aviation, for civilian and scientific purposes, in our atmosphere and in atmospheres of other worlds. In particular, with respect to NASA s manned flight to Mars, this technology addresses the critical requirements for improving safety and increasing reliability of manned spacecraft.

James, Mark↗

An Overview of Research in Nondestructive Evaluation at the National Aeronautics and Space Administration’s Langley Research Center

The primary focus of the nondestructive evaluation (NDE) effort at Langley Research Center (LaRC) is to pioneer advances in NDE and structural health monitoring (SHM) through fundamental scientific research, technology development, and transferring these to the scientific and aerospace communities. This research supports a variety of NASA missions in space operations, exploration and aeronautics. The work presented will focus on the development of advanced inspection systems to detect critical flaws in both metallic and non-metallic materials and structures for aerospace applications. The emphasis is on increasing the performance of inspection systems to provide defect detection and quantitative characterization of the material state. LaRC NDE utilizes expertise in computational ultrasonic, thermal and eddy current simulations to reduce measured responses to size and locations of flaws, establish technique limitations and optimize performance. This presentation will highlight research into five strategic areas: (1) The development of novel solutions using state-of-the-art NDE technologies such as eddy current, ultrasound, thermography and x-ray computed tomography; (2) Research in the development of unique NDE technologies such as terahertz, wavefield imaging and nonlinear ultrasound; (3) The application of both computational and analytic models to NDE problems; (4) The development of advanced analytic methods to interpret large complex data sets; and (5) Advanced methods of applying and interrogating sensors for structural health monitoring.

K Elliott Cramer↗

An Overview of Research in Nondestructive Evaluation at the National Aeronautics and Space Administration’s Langley Research Center

The primary focus of the nondestructive evaluation (NDE) effort at Langley Research Center (LaRC) is to pioneer advances in NDE and structural health monitoring (SHM) through fundamental scientific research, technology development, and transferring these to the scientific and aerospace communities. This research supports a variety of NASA missions in space operations, exploration and aeronautics. The work presented will focus on the development of advanced inspection systems to detect critical flaws in both metallic and non-metallic materials and structures for aerospace applications. The emphasis is on increasing the performance of inspection systems to provide defect detection and quantitative characterization of the material state. LaRC NDE utilizes expertise in computational ultrasonic, thermal and eddy current simulations to reduce measured responses to size and locations of flaws, establish technique limitations and optimize performance. This presentation will highlight research into five strategic areas: (1) The development of novel solutions using state-of-the-art NDE technologies such as eddy current, ultrasound, thermography and x-ray computed tomography; (2) Research in the development of unique NDE technologies such as terahertz, wavefield imaging and nonlinear ultrasound; (3) The application of both computational and analytic models to NDE problems; (4) The development of advanced analytic methods to interpret large complex data sets; and (5) Advanced methods of applying and interrogating sensors for structural health monitoring.

NDE↗

Software Testing and Verification in Climate Model Development

Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

Clune, Thomas L.↗

FAIR principles for AI models with a practical application for accelerated high energy diffraction microscopy

Abstract A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable) principles for scientific data is transforming the state-of-practice for data management and stewardship, supporting and enabling discovery and innovation. Learning from this initiative, and acknowledging the impact of artificial intelligence (AI) in the practice of science and engineering, we introduce a set of practical, concise, and measurable FAIR principles for AI models. We showcase how to create and share FAIR data and AI models within a unified computational framework combining the following elements: the Advanced Photon Source at Argonne National Laboratory, the Materials Data Facility, the Data and Learning Hub for Science, and funcX, and the Argonne Leadership Computing Facility (ALCF), in particular the ThetaGPU supercomputer and the SambaNova DataScale ® system at the ALCF AI Testbed. We describe how this domain-agnostic computational framework may be harnessed to enable autonomous AI-driven discovery.

47 OTHER INSTRUMENTATION↗

Understanding and Estimating Error Propagation in Neural Networks for Scientific Data Analysis

Neural networks are increasingly integrated into scientific discovery, where input data reduction and model quantization play a key role in accelerating inference. However, understanding and mitigating the impact of these techniques on output error is critical for ensuring reliable results, particularly in tasks demanding high numerical precision. This paper introduces a comprehensive framework for optimizing neural network inference in scientific computing by combining data reduction and weight quantization while maintaining error-controlled outcomes. We develop theoretical analyses to bound error propagation under these reductions and propose a framework that balances computational performance with error constraints. Evaluation on real-world learning-based combustion simulations and satellite image classification demonstrates that our derived error bounds accurately predict observed errors while enabling significant computational speedup under our framework. This work highlights the potential for further leveraging advancements in modern lossy compression algorithms and hardware accelerators that support lower-precision formats.

He, Weiming [New Jersey Institute of Technology]↗

Earth Observing System (EOS) Aqua Launch and Early Mission Attitude Support Experiences

The Earth Observing System (EOS) Aqua satellite was successfully launched on May 4,2002. Aqua is the second in the series of EOS satellites. EOS is part of NASA s Earth Science Enterprise Program, whose goals are to advance the scientific understanding of the Earth system. Aqua is a three-axis stabilized, Earth-pointing spacecraft in a nearly circular, sun-synchronous orbit at an altitude of 705 km. The Goddard Space Flight Center (GSFC) Flight Dynamics attitude team supported all phases of the launch and early mission. This paper presents the main results and lessons learned during this period, including: real-time attitude mode transition support, sensor calibration, onboard computer attitude validation, response to spacecraft emergencies, postlaunch attitude analyses, and anomaly resolution. In particular, Flight Dynamics support proved to be invaluable for successful Earth acquisition, fine-point mode transition, and recognition and correction of several anomalies, including support for the resolution of problems observed with the MODIS instrument.

Tracewell, D.↗

Constructing an advanced software tool for planetary atmospheric modeling

A prototype is described that can serve as a scientific-modeling software tool to facilitate the development of useful scientific models. The prototype is developed for applications to planetary modeling, and specific examples are given that relate to the atmosphere of Titan. The scientific modeling tool employs a high-level domain-specific modeling language, several data-display facilities, and a library of experimental datasets and scientific equations. The planetary modeling prototype links uncomputed physical variables to computed variables with computational transformations based on a backchaining procedure. The system - implemented in LISP with an object-oriented knowledge-representation tool - is run on a workstation that provides interface with several models. The prototype is expected to form the basis for a sophisticated modeling tool that can permit active experimentation.

Keller, Richard M.↗