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At least 145 records · Page 8

Framework for Small-Scale Experiments in Software Engineering: Guidance and Control Software Project: Software Engineering Case Study

Software is becoming increasingly significant in today's critical avionics systems. To achieve safe, reliable software, government regulatory agencies such as the Federal Aviation Administration (FAA) and the Department of Defense mandate the use of certain software development methods. However, little scientific evidence exists to show a correlation between software development methods and product quality. Given this lack of evidence, a series of experiments has been conducted to understand why and how software fails. The Guidance and Control Software (GCS) project is the latest in this series. The GCS project is a case study of the Requirements and Technical Concepts for Aviation RTCA/DO-178B guidelines, Software Considerations in Airborne Systems and Equipment Certification. All civil transport airframe and equipment vendors are expected to comply with these guidelines in building systems to be certified by the FAA for use in commercial aircraft. For the case study, two implementations of a guidance and control application were developed to comply with the DO-178B guidelines for Level A (critical) software. The development included the requirements, design, coding, verification, configuration management, and quality assurance processes. This paper discusses the details of the GCS project and presents the results of the case study.

Hayhurst, Kelly J.↗

User Manual for Physical Scalars and Plotting Tools in Scala

An open-source scalar package and associated software tools have been developed in the Scala programming language, including plotting tools based on the free GRACE plotting package. The scalar package represents physical scalars and can help to prevent errors involving physical units in engineering and scientific computation. The scalar package includes a complete implementation of the standard SI metric system of units and many common non-metric units. The design also allows users to easily de ne a specialized or reduced set of physical units for any particular application or domain. The scalar package can be used in two different modes: one mode provides unit compatibility checking but is slower, and the other mode bypasses the compatibility checks but is much faster and still prevents the most common type of unit error. Switching between the two modes requires no changes in the user's code, making it convenient and usable with no significant performance penalty for even the most computationally intensive applications.

Paielli, Russell A.↗

Planetary Mapping for Landing Sites Selection: The Mars Case Study

The selection of a landing site on a planetary body is a multistep process that involves both the fulfillment of several engineering constraints and the accomplishment of scientific requirements. In this chapter, we will show how the simultaneous production and exploitation of different GIS maps depicting these criteria are pivotal in the landing site selection. Indeed, all of such constraints are presently evaluated through the use of GIS-based software. To show this, we will focus on the Martian site identification outline, providing multiple real examples taken from two ongoing study cases, i.e., the Simud Vallis landing site proposed by Pajola et al. (Icarus 268:355–381, 2016a) for the ESA ExoMars rover and the Eridania landing site proposed by Pajola et al. (Icarus 275:163–182, 2016b) for the NASA Mars 2020 landing site selection.

Planetary mapping↗

The Kalman Filter and High Performance Computing at NASA's Data Assimilation Office (DAO)

Atmospheric data assimilation is a method of combining actual observations with model simulations to produce a more accurate description of the earth system than the observations alone provide. The output of data assimilation, sometimes called "the analysis", are accurate regular, gridded datasets of observed and unobserved variables. This is used not only for weather forecasting but is becoming increasingly important for climate research. For example, these datasets may be used to assess retrospectively energy budgets or the effects of trace gases such as ozone. This allows researchers to understand processes driving weather and climate, which have important scientific and policy implications. The primary goal of the NASA's Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. This presentation will: (1) describe ongoing work on the advanced Kalman/Lagrangian filter parallel algorithm for the assimilation of trace gases in the stratosphere; and (2) discuss the Kalman filter in relation to other presentations from the DAO on Four Dimensional Data Assimilation at this meeting. Although the designation "Kalman filter" is often used to describe the overarching work, the series of talks will show that the scientific software and the kind of parallelization techniques that are being developed at the DAO are very different depending on the type of problem being considered, the extent to which the problem is mission critical, and the degree of Software Engineering that has to be applied.

Lyster, Peter M.↗

MER SPICE Interface

MER SPICE Interface is a software module for use in conjunction with the Mars Exploration Rover (MER) mission and the SPICE software system of the Navigation and Ancillary Information Facility (NAIF) at NASA's Jet Propulsion Laboratory. (SPICE is used to acquire, record, and disseminate engineering, navigational, and other ancillary data describing circumstances under which data were acquired by spaceborne scientific instruments.) Given a Spacecraft Clock value, MER SPICE Interface extracts MER-specific data from SPICE kernels (essentially, raw data files) and calculates values for Planet Day Number, Local Solar Longitude, Local Solar Elevation, Local Solar Azimuth, and Local Solar Time (UTC). MER SPICE Interface was adapted from a subroutine, denoted m98SpiceIF written by Payam Zamani, that was intended to calculate SPICE values for the Mars Polar Lander. The main difference between MER SPICE Interface and m98SpiceIf is that MER SPICE Interface does not explicitly call CHRONOS, a time-conversion program that is part of a library of utility subprograms within SPICE. Instead, MER SPICE Interface mimics some portions of the CHRONOS code, the advantage being that it executes much faster and can efficiently be called from a pipeline of events in a parallel processing environment.

Sayfi, Elias↗

DLES Unreal Simulation Tool (DUST)

NASA’s future Artemis missions to the Moon seek to explore areas around the Lunar South Pole. Though humans have previously set foot on the lunar surface, the proposed region provides unique and challenging environments that require insight and investigation prior to arrival. Several teams throughout the agency are performing this site and mission planning, design, and analysis to support areas like the Human Landing System (HLS), surface mobility, habitation elements, and scientific exploration. The NASA Exploration Systems Simulation (NExSyS) team at Johnson Space Center is developing a graphical environment of the Lunar South Pole region. Lunar terrain information collected from the Lunar Reconnaissance Orbiter (LRO) is compiled and made available through Johnson Space Center’s Digital Lunar Exploration Sites (DLES) data sets. The DLES data is used to build this graphic environment. The process of ingesting and accurately modeling this information in a meaningful way for analysis creates its own challenges such as generating a performant model from the source data and the application of curvature. Additionally, the area around the Lunar South Pole experiences different lighting conditions than those observed from the Apollo missions. The need to use the lunar environmental data products provided by DLES combined with the capability to calculate date specific ephemerides in real-time has given rise to the development of the DLES Unreal Simulation Tool (DUST). DUST incorporates augmented terrain from the DLES product into a desktop application that allows exploration of the Lunar South Pole region and its complex lighting conditions. DUST leverages advanced capabilities in the recently released Unreal Engine 5 renderer by Epic Games such as double precision for positioning of planetary bodies and surface elements, multiple infinite light sources to represent the Sun and eventually Earthshine, high resolution shadow maps for dynamic shadow accuracy, real-time software ray-tracing for multi-surface bounce lighting to render sunlight reflected off surface elements and terrain features, and performance optimized level of detail shifting as the eyepoint changes in a scene. This paper details the DUST application, the technologies of the engine platform that enable scientific and engineering analysis, the unique techniques and processes developed to consume the DLES data sets, and how the tool is being used to support the Artemis program.

Lunar Visualization↗

An open-access simulated earthquake ground-motion database for an M7 Hayward Fault earthquake in the San Francisco Bay Region

Comprehensive understanding of earthquake ground motions, particularly in the near-fault region of large-magnitude events, is limited by gaps in strong-motion data. This challenge is prominent in areas with high seismic hazard but infrequent large earthquakes where data is sparse and difficult to interpret. These data limitations lead to uncertainties in the development of site-specific ground motions, which are crucial for engineering risk assessments. To address these challenges, physics-based regional-scale ground-motion simulations have been developed. With the emergence of exaflop-scale computing ecosystems, it is now possible to simulate regional earthquake processes at unprecedented fidelity and generate the large number of fault rupture realizations necessary to characterize both intra- and inter-event ground-motion variability. This article introduces a new database of simulated earthquake ground motions, created for applications in earthquake engineering, earthquake planning, and emergency response. The inaugural version of the database features simulated ground motions for a magnitude 7 Hayward Fault earthquake in the San Francisco Bay Region (SFBR), using the EarthQuake SIMulation (EQSIM) simulation framework and the Graves–Pitarka kinematic rupture model. The aim is to provide high-fidelity, spatially dense, three-component motions generated on the Department of Energy’s (DOE) newest generation of graphics processing unit (GPU)-accelerated supercomputers. These motions are being made openly available to the engineering, scientific, and disaster planning communities. In addition, this work develops protocols for the efficient dissemination of these large data sets and emphasizes community engagement to build confidence in their application. This article discusses the methodology behind the data, underlying software verification and validation, scalable data management, and a user interface for data access. The goal is to facilitate widespread use and elicit expert feedback to maximize the utility and exploitation of simulated motions. While the initial focus is on the San Francisco Region, simulations for additional regions will be added as the DOE program progresses.

Simulated ground-motion database↗

Software for Managing Parametric Studies

The Information Power Grid Virtual Laboratory (ILab) is a Practical Extraction and Reporting Language (PERL) graphical-user-interface computer program that generates shell scripts to facilitate parametric studies performed on the Grid. (The Grid denotes a worldwide network of supercomputers used for scientific and engineering computations involving data sets too large to fit on desktop computers.) Heretofore, parametric studies on the Grid have been impeded by the need to create control language scripts and edit input data files painstaking tasks that are necessary for managing multiple jobs on multiple computers. ILab reflects an object-oriented approach to automation of these tasks: All data and operations are organized into packages in order to accelerate development and debugging. A container or document object in ILab, called an experiment, contains all the information (data and file paths) necessary to define a complex series of repeated, sequenced, and/or branching processes. For convenience and to enable reuse, this object is serialized to and from disk storage. At run time, the current ILab experiment is used to generate required input files and shell scripts, create directories, copy data files, and then both initiate and monitor the execution of all computational processes.

Yarrow, Maurice↗

Engineering the Microstructure and Morphology of Explosive Films via Control of Interfacial Energy

Physical vapor deposition of organic explosives enables growth of polycrystalline films with a unique microstructure and morphology compared to the bulk material. This study demonstrates the ability to control crystal orientation and porosity in pentaerythritol tetranitrate films by varying the interfacial energy between the substrate and the vapor-deposited explosive. Additionally, variation in density, porosity, surface roughness, and optical properties is achieved in the explosive film, with significant implications for initiation sensitivity and detonation performance of the explosive material. Various surface science techniques, including angle-resolved X-ray photoelectron spectroscopy and multiliquid contact angle analysis, are utilized to characterize interfacial characteristics between the substrate and explosive film. Optical microscopy and scanning electron microscopy of pentaerythritol tetranitrate surfaces and fracture cross sections illustrate the difference in morphology evolution and the microstructure achieved through surface energy modification. X-ray diffraction studies with the Tilt-A-Whirl three-dimensional pole figure rendering and texture analysis software suite reveal that high surface energy substrates result in a preferred (110) out-of-plane orientation of pentaerythritol tetranitrate crystallites and denser films. Low surface energy substrates create more randomly textured pentaerythritol tetranitrate and lead to nanoscale porosity and lower density films. This work furthers the scientific basis for interfacial engineering of polycrystalline organic explosive films through control of surface energy, enabling future study of dynamic and reactive detonative phenomena at the microscale. Results of this study also have potential applications to active pharmaceutical ingredients, stimuli-responsive polymer films, organic thin film transistors, and other areas.

36 MATERIALS SCIENCE↗

Summarizing the interoperabilities between xSDK members

Rapid, efficient production of high-quality, sustainable extreme-scale scientific applications is best accomplished using a rich ecosystem of state-of-the art reusable libraries, tools, lightweight frameworks, and defined software methodologies, developed by a community of scientists who are striving to identify, adapt, and adopt best practices in software engineering. The vision of the xSDK is to provide infrastructure for and interoperability of a collection of related and complementary software elements — developed by diverse, independent teams throughout the high-performance computing (HPC) community — that provide the building blocks, tools, models, processes, and related artifacts for rapid and efficient development of high-quality applications. A primary component, and challenge, of the xSDK is to improve interoperability among software libraries and domain components. This document summarizes the current and planned interoperabilities of the twenty-three xSDK member packages as of March 2021. Additionally, the status of the xSDK example codes that demonstrate and test the interoperabilities within the xSDK is provided.

97 MATHEMATICS AND COMPUTING↗

Engineering Performance

Under Goddard Space Flight Center and Jet Propulsion Laboratory SBIR (Small Business Innovative Research) contracts, AST Engineering Services, Inc. developed a system engineering computer software tool to model how certain applications will affect a proposed system's performance. Quantitative System Engineering (QASE) evaluates system timing, capacity and availability. The system is used to predict performance of proposed real-time, aerospace systems, embedded systems, and/or scientific systems, as well as in support of NASA's EDOS (Earth Observing System (EOS) Data and Operations System) initiative.

Source record↗

The Legacy of the Low Temperature Microgravity Physics Facility

The Jet Propulsion Laboratory (JPL) has been building the Low Temperature Microgravity Physics Facility (LTMPF) as a multi-user research facility for the International Space Station. Because of the recent Presidential Exploration Initiative placed on NASA, NASA has informally told JPL to phase out the development of the LTMPF, assuming a suspension of funding at the end of fiscal year 2004. Over the last five years of development of the Facility, a tremendous legacy of both scientific and technical progress has been made, and a significant amount of flight hardware has been built. During these last few months of remaining funding, the LTMPF plans on finishing some remaining development efforts, archiving the hardware (flight and engineering models), software, and capturing the knowledge generated for possible future missions. These possible future missions could include gravitational or relativistic physics experiments (around the Earth or the Moon), charged particle physics experiments away from the Earth, possible other fundamental physics experiments in a Code U-developed free flyer orbiting the Earth, or even gravitational mapping experiments around the Moon or possibly Mars. LTMPF-developed technologies that are likely to have substantial impact on such future missions include SQUID magnetometers and thermometers, ultra-high-performance cryogenics, and high-Q superconducting resonators.

Larson, Melora↗

Developing Multiphysics, Integrated, High-Fidelity, Massively Parallel Computational Capabilities for Fusion Applications Using MOOSE

As the need for fusion as a clean, sustainable, and abundant energy source grows internationally, so does the need for multiphysics, computational tools to model, study, and predict the complex interactions between plasma, materials, and engineering processes. These tools have a crucial role to play in solving scientific and engineering challenges and accelerating fusion energy deployment. To address these needs, modeling capabilities should enable massively parallel, multiphysics, fully integrated high-fidelity simulations of fusion systems. Additional attributes, such as being open source and modular while maintaining high software quality assurance standards will maximize impact by ensuring accessibility for all and wide acceptance, rapid expansion and development, as well as reliability, efficiency, and robustness. In this paper, we describe how the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has a track record of success in the fission space thanks to the attributes listed above, can be leveraged in the fusion energy field. We highlight key successes of the MOOSE application in the fission space and describe how MOOSE has been and is being applied to fusion applications in the United States---e.g., Tritium Migration Analysis Program, version 8 (TMAP8), MOOSE Fusion Module, Fusion ENergy Integrated multiphys-X (FENIX)---and the United Kingdom---e.g., AURORA, Achlys, Apollo. These efforts aim to establish a suite of tools that can be further extended to accelerate fusion energy deployment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Foundations of machine learning for low-temperature plasmas: methods and case studies

Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable tool in tackling a vast array of scientific, engineering, and societal problems. The main drivers behind the recent proliferation of ML in practically all aspects of science and technology can be attributed to: (a) improved data acquisition and inexpensive data storage; (b) exponential growth in computing power; and (c) availability of open-source software and resources that have made the use of state-of-the-art ML algorithms widely accessible. The impact of ML on the field of low-temperature plasmas (LTPs) could be particularly significant in the emerging applications that involve plasma treatment of complex interfaces in areas ranging from the manufacture of microelectronics and processing of quantum materials, to the LTP-driven electrification of the chemical industry, and to medicine and biotechnology. This is primarily due to the complex and poorly-understood nature of the plasma-surface interactions in these applications that pose unique challenges to the modeling, diagnostics, and predictive control of LTPs. As the use of ML is becoming more prevalent, it is increasingly paramount for the LTP community to be able to critically analyze and assess the concepts and techniques behind data-driven approaches. To this end, the goal of this paper is to provide a tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone, for learning multivariable nonlinear data-driven prediction models that are capable of describing the complex behavior of plasma interacting with interfaces, and for guiding the design of experiments to explore the parameter space of plasma-assisted processes in a systematic and resource-efficient manner. We illustrate the utility of various supervised, unsupervised and active learning methods using LTP datasets consisting of commonly-available, information-rich measurements (e.g. optical emission spectra, current–voltage characteristics, scanning electron microscope images, infrared surface temperature measurements, Fourier transform infrared spectra). All the ML demonstrations presented in this paper are carried out using open-source software; the datasets and codes are made publicly available. The FAIR guiding principles for scientific data management and stewardship can accelerate the adoption and development of ML in the LTP community.

Physics↗

Software for Planning Scientific Activities on Mars

Mixed-Initiative Activity Plan Generator (MAPGEN) is a ground-based computer program for planning and scheduling the scientific activities of instrumented exploratory robotic vehicles, within the limitations of available resources onboard the vehicle. MAPGEN is a combination of two prior software systems: (1) an activity-planning program, APGEN, developed at NASA s Jet Propulsion Laboratory and (2) the Europa planner/scheduler from NASA Ames Research Center. MAPGEN performs all of the following functions: Automatic generation of plans and schedules for scientific and engineering activities; Testing of hypotheses (or what-if analyses of various scenarios); Editing of plans; Computation and analysis of resources; and Enforcement and maintenance of constraints, including resolution of temporal and resource conflicts among planned activities. MAPGEN can be used in either of two modes: one in which the planner/scheduler is turned off and only the basic APGEN functionality is utilized, or one in which both component programs are used to obtain the full planning, scheduling, and constraint-maintenance functionality.

Ai-Chang, Mitchell↗

Quantum Software Engineering (Dagstuhl Seminar 24512)

The Dagstuhl Seminar 24512 on "Quantum Software Engineering" was held from December 15 to 20, 2024. It brought together 26 participants from industry and academia from 13 different countries, including senior and junior researchers as well as practitioners in the field of Quantum Software Engineering. The aim of the seminar was to advance software engineering methods and tools for the engineering of hybrid quantum systems by promoting personal interaction and open discussion among researchers who are already working in this emerging area of knowledge. The first day of the seminar was devoted to the topic "When software engineering meets quantum mechanics", while the second day focused on "Quantum software engineering and its challenges." During both days, 16 invited presentations were given. The rest of the seminar was organized into three working groups to address the topics "Quantum Software Design, Modelling and Architecturing", "Adaptive Hybrid Quantum Systems", and "Quantum Software Quality Assurance". The seminar was a very fruitful experience for all participants both in terms of scientific outcomes and in terms of the personal relationships that were generated to jointly address future experiences.

97 MATHEMATICS AND COMPUTING↗

A unified approach to computer analysis and modeling of spacecraft environmental interactions

A new, coordinated, unified approach to the development of spacecraft plasma interaction models is proposed. The objective is to eliminate the unnecessary duplicative work in order to allow researchers to concentrate on the scientific aspects. By streamlining the developmental process, the interchange between theories and experimentalists is enhanced, and the transfer of technology to the spacecraft engineering community is faster. This approach is called the UNIfied Spacecraft Interaction Model (UNISIM). UNISIM is a coordinated system of software, hardware, and specifications. It is a tool for modeling and analyzing spacecraft interactions. It will be used to design experiments, to interpret results of experiments, and to aid in future spacecraft design. It breaks a Spacecraft Ineraction analysis into several modules. Each module will perform an analysis for some physical process, using phenomenology and algorithms which are well documented and have been subject to review. This system and its characteristics are discussed.

Katz, I.↗

The FIFE information system

A description is given of the FIFE (First ISLSCP Field Experiment) information system, which was developed to serve FIFE investigators as a tool for designing the experiment and for organizing and manipulating the complex data set. Fulfilling these functions on an experiment-driven timeline led to abandoning the classical sequential development paradigm of software engineering in favor of a more responsive and broadly based approach. The design, development, and operation of the information system supporting the experiment had to be flexible and under direct day-to-day control of scientist/users. Because of the organization around scientific requirements, the system was able to incorporate diverse data types in a systematic way as they became available, to add scientific rigor by identifying data gaps at an early stage, and to provide real-time quality assurance. These factors are important for designing and building future databases and long-term information systems to support interdisciplinary scientific research.

Strebel, Donald E.↗