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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Scalable Traffic Management for Emergency Response Operations (STEReO)Airspace Operations Laboratory (AOL) Unmanned Aircraft Systems (UAS)Traffic Management (UTM) (AOLUSS)Tabletop Overview

The Scalable Traffic Management for Emergency Response Operations (STEReO) project requires prototyping software to extend existing Airspace Operations Laboratory (AOL) software capabilities to support research in integrating drone flight activities within an emergency response airspace environment. A presentation encompassing project AOLUSS details, communications and network design will be presented at a Workshop.

STEReO software↗
NASA NTRS2019

Adaptations of guidance, navigation, and control verification and validation philosophies for small spacecraft

Decades of experience developing increasingly capable and more complex space-craft have resulted in a set of accepted practices and philosophies to verify and validate (V&V) guidance, navigation, and control (GN&C) subsystems. Until recently, small, low-cost spacecraft have had very simple or non-existent GN&C subsystems requiring minimal or no subsystem testing. As the next generation of small spacecraft take on more challenging GN&C requirements, the GN&C community is struggling with how to scale the subsystem V&V effort to produce spacecraft approaching the reliability of flagship-class missions while staying within the reduced resources of a small satellite project.For this paper, we will examine five aspects of GN&C V&V (requirements definition, software testing and analysis, hardware component testing, integrated vehicle testing, and in-flight V&V) and compare the V&V campaign of a flagship-class mission (Mars 2020) to that of two recent, successful CubeSat missions: ASTERIA and MarCO. Experiences from the development of these CubeSats yield valuable lessons learned and guidelines for future small spacecraft designers.

Chen, George T.↗
NASA NTRS2022

Towards Self-Adaptive Game Logic

Self-adaptive systems (SAS) can reconfigure at run time in response to changing situations to express acceptable behaviors in the face of uncertainty. With respect to game design, such situations may include user input, emergent behaviors, performance concerns, and combinations thereof. Typically an SAS is modeled as a feedback loop that functions within an existing system, with operations including monitoring, analyzing, planning, and executing (i.e., MAPE-K) to enable online reconfiguration. This paper presents a conceptual approach for extending software engineering artifacts to be self-adaptive within the context of game design. We have modified a game developed for creative coding education to include a MAPE-K self-adaptive feedback loop, comprising run-time adaptation capabilities and the software artifacts required to support adaptation.

Erik M. Fredericks↗
NASA NTRSDate not supplied

Visualizing Geospatial Data through ESRI Story Maps for Earth Science Education: Lessons Learned from My NASA Data

For 20 years My NASA Data (MND) has curated NASA Earth science data and provided the data to educators in engaging learner-centered resources. MND has recently featured story maps as an innovative way to engage students in NASA Earth data. A story map is a cloud-based lesson that engages the learner in interactive geospatial maps using NASA data, and other multimedia content, text, and tasks that can be seamlessly incorporated in classroom instruction. This immersive technology eliminates the need for the user to move among tricky interfaces to access and visualize Earth science data, and no special software is required to be downloaded. Each story map integrates data from different NASA satellite missions, retrieved from Distributed Active Archive Centers (DAACs). Story maps also employ data analysis tools, such as time series options and swipe tools that allow learners to view and analyze relationships between scientific variables. MND has produced 25 story map lesson plans on the topics of air quality, the urban heat island effect, Earth’s energy budget, phytoplankton distribution, hurricane formation, solar eclipses, ocean circulation patterns, sea ice extent, and volcanic eruptions. Nine of them are extended story maps and written in the 5E format, which is internationally recognized as best practice based on how children learn science. Each story map resource is developed by the MND team featuring a GIS programming specialist, a lead scientist, and educational specialist/s to ensure the context, content, and methods are scientifically and educationally sound. The MND story maps are written for middle and high school science teachers and students as they connect with the Earth Systems Science phenomena featured in the Next Generation Science Standards. Each story map includes supporting resources for smooth integration in the classroom. During Fiscal Year 2023, The My NASA Data website received over 100,000 story map engagements during. These metrics highlight the interest in story maps as an Earth Science educational resource.

Desiray Wilson↗
DOE OSTI2020

Biosequence-based approach to analyzing binaries

In a dynamic computing environment, it is a nontrivial task to verify code running in the environment because most approaches to software similarity require extensive and time-consuming analysis of a binary, or the approaches fail to recognize executables that are similar but nonidentical. A biosequence-based method for quantifying similarity of executable binaries is used to identify allowed codes in a real-world multi-user environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Variable-Speed Pump Efficiency Calculation For Fluid Flow Systems with and without Static Head

To accurately calculate pump energy savings gained from implementing variable frequency drive (VFD) controls, the variation of pump efficiency must be considered when operating conditions transition from the design operating point to new operating points. Many software tools require users to specify the new pump efficiency, or it is assumed to be unchanged. Unfortunately, many users have challenges of estimating the pump efficiency at new operating points. This paper presents a simplified method of estimating centrifugal pump efficiency at new operating speeds when the pump is controlled by a VFD. This methodology applies to systems with and without static head when the system curve is not affected by the change, and also systems where the change in operation changes the system curve.A hypothetical fluid flow system and centrifugal pump were used to demonstrate the calculation process for these scenarios. For this hypothetical system, the pump’s efficiency at new operating points was up to 5.4% lower than the design operating point.

42 ENGINEERING↗
DOE OSTI2020

High Performance Computing Systems Tools, Visualization, and Management

High Performance Computing (HPC) systems are complex setups of servers, storage devices, network switches, and cables that are specifically designed to accommodate hundreds of users running highly computationally intensive applications at a time. These applications require numerous softwares, licenses, and various levels of storage as well. All of these resources must be monitored and managed by HPC administrators, which presents a daunting task. In this project, I created numerous software tools as part of an HPC Visualization and Management system, which is now used by HPC administrators on a daily basis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Comparison of Attila Transport Code with MCNP in the Analysis of Small Modular Reactor Shielding

Of great importance in the design of a nuclear power plant is the evaluation of shielding from the ionizing radiation produced in the core of the nuclear reactor. This requires simulation software to predict the dose rates in the areas of interest. These problems are referred to as deep penetration problems, as they involve the reduction of a radiation field by two or three orders of magnitude or more. This makes accurate analyses difficult for Monte Carlo based solutions that rely on enough particles being sampled in an area of interest. Comparing the simulation of the same modeled system with more than one computer application, especially one that uses a different algorithmic approach, is a way to gain confidence in the results. In this research, two models were created, one in Monte Carlo N Particle (MCNP) which uses a stochastic algorithmic approach, and the other in Attila, which uses a deterministic algorithmic approach to test the validity of the model and to estimate the dose rates in the area of interest. Successful comparison of the two models is a way we can validate the model used for that estimation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

\texttt{qec\_code\_sim}: An open-source Python framework for estimating the effectiveness of quantum-error correcting codes on superconducting qubits

Quantum computers are highly susceptible to errors due to unintended interactions with their environment. It is crucial to correct these errors without gaining information about the quantum state, which would result in its destruction through back-action. Quantum Error Correction (QEC) provides information about occurred errors without compromising the quantum state of the system. However, the implementation of QEC has proven to be challenging due to the current performance levels of qubits -- break-even requires fabrication and operation quality that is beyond the state-of-the-art. Understanding how qubit performance factors into the success of a QEC code is a valuable exercise for tracking progress towards fault-tolerant quantum computing. Here we present \texttt{qec\_code\_sim}, an open-source, lightweight Python framework for studying the performance of small quantum error correcting codes under the influence of a realistic error model appropriate for superconducting transmon qubits, with the goal of enabling useful hardware studies and experiments. \texttt{qec\_code\_sim} requires minimal software dependencies and prioritizes ease of use, ease of change, and pedagogy over execution speed. As such, it is a tool well-suited to small teams studying systems on the order of one dozen qubits.

Lopez, Santiago↗
NASA NTRS2001

A Practical Approach to Modified Condition/Decision Coverage

Testing of software intended for safety-critical applications in commercial transport aircraft must achieve modified condition/decision coverage (MC/DC) of the software structure. This requirement causes anxiety for many within the aviation software community. Results of a survey of the aviation software industry indicate that many developers believe that meeting the MC/DC requirement is difficult, and the cost is exorbitant. Some of the difficulties stem, no doubt, from the scant information available on the subject. This paper provides a practical 5-step approach for assessing MC/DC for aviation software products, and an analysis of some types of errors expected to be caught when MC/DC is achieved1.

Hayhurst, Kelly J.↗
NASA NTRSDate not supplied

Autonomous Robotic Manipulator Software

Autonomous robotic manipulation requires a deep and wide stack of supporting software. This paper presents Autonomous Robotic Manipulator Software (ARMS), a software suite designed at NASA Langley Research Center to support research and development of different algorithms for In-space Servicing, Assembly and Manufacturing (ISAM). ARMS solves common challenges along the autonomous manipulation software stack. Various challenges, such as integration with commercial hardware, simulation, and path planning, are solved through the use of Robot Operating System 2 and its community-developed packages. Other challenges, such as configuration management and task definition, and execution are solved in software built on those tools. The result is a modular approach to robotic system definition, agent actions, and assembly task definitions. ARMS has been used in two ISAM projects at NASA Langley Research Center, the Precision Assembled Space Structures project and the Built On-orbit Robotically assembled Gigatruss project.

Collin J Cresta↗
NASA NTRS2002

Interactive Software Fault Analysis Tool for Operational Anomaly Resolution

Resolving software operational anomalies frequently requires a significant amount of resources for software troubleshooting activities. The time required to identify a root cause of the anomaly in the software may lead to significant timeline impacts and in some cases, may extend to compromise of mission and safety objectives. An integrated tool that supports software fault analysis based on the observed operational effects of an anomaly could significantly reduce the time required to resolve operational anomalies; increase confidence for the proposed solution; identify software paths to be re-verified during regression testing; and, as a secondary product of the analysis, identify safety critical software paths.

Chen, Ken↗
NASA NTRS1984

Non-Imaging Software/Data Analysis Requirements

The analysis software needs of the non-imaging planetary data user are discussed. Assumptions as to the nature of the planetary science data centers where the data are physically stored are advanced, the scope of the non-imaging data is outlined, and facilities that users are likely to need to define and access data are identified. Data manipulation and analysis needs and display graphics are discussed.

Source record↗
DOE OSTI2026

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗
NASA NTRS2006

Automated Derivation of Complex System Constraints from User Requirements

International Space Station (ISS) payload developers submit their payload science requirements for the development of on-board execution timelines. The ISS systems required to execute the payload science operations must be represented as constraints for the execution timeline. Payload developers use a software application, User Requirements Collection (URC), to submit their requirements by selecting a simplified representation of ISS system constraints. To fully represent the complex ISS systems, the constraints require a level of detail that is beyond the insight of the payload developer. To provide the complex representation of the ISS system constraints, HOSC operations personnel, specifically the Payload Activity Requirements Coordinators (PARC), manually translate the payload developers simplified constraints into detailed ISS system constraints used for scheduling the payload activities in the Consolidated Planning System (CPS). This paper describes the implementation for a software application, User Requirements Integration (URI), developed to automate the manual ISS constraint translation process.

Muery, Kim↗