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At least 19 records

Comparison of GSFC and JPL VLBI modeling software: Benchmark

The Very Long Base Interferometry. The VLBI modeling software packages CALC 6.0 (GSFC) and MASTERFIT (JPL) are compared in some detail. Theoretical model delays are calculated for a set of 120 fictitious observations which involve a variety of sources, baselines, and antennas. Discrepancies between the total delays given by the two programs are of the order of 2 cm (RMS). The modeling of antenna offsets appears to account for approximately half of this difference. Relativistic bending contributions to the delay differ by 3 cm (RMS), and the there appears to be some mutual cancellation of errors involving antenna offsets, bending, and the effects of the two different Solar System ephemerides employed by CALC and MASTERFIT. This cancellation has not been completely characterized here.

Sovers, O. J.↗

NASA Software Engineering Benchmarking Study

To identify best practices for the improvement of software engineering on projects, NASA's Offices of Chief Engineer (OCE) and Safety and Mission Assurance (OSMA) formed a team led by Heather Rarick and Sally Godfrey to conduct this benchmarking study. The primary goals of the study are to identify best practices that: Improve the management and technical development of software intensive systems; Have a track record of successful deployment by aerospace industries, universities [including research and development (R&D) laboratories], and defense services, as well as NASA's own component Centers; and Identify candidate solutions for NASA's software issues. Beginning in the late fall of 2010, focus topics were chosen and interview questions were developed, based on the NASA top software challenges. Between February 2011 and November 2011, the Benchmark Team interviewed a total of 18 organizations, consisting of five NASA Centers, five industry organizations, four defense services organizations, and four university or university R and D laboratory organizations. A software assurance representative also participated in each of the interviews to focus on assurance and software safety best practices. Interviewees provided a wealth of information on each topic area that included: software policy, software acquisition, software assurance, testing, training, maintaining rigor in small projects, metrics, and use of the Capability Maturity Model Integration (CMMI) framework, as well as a number of special topics that came up in the discussions. NASA's software engineering practices compared favorably with the external organizations in most benchmark areas, but in every topic, there were ways in which NASA could improve its practices. Compared to defense services organizations and some of the industry organizations, one of NASA's notable weaknesses involved communication with contractors regarding its policies and requirements for acquired software. One of NASA's strengths was its software assurance practices, which seemed to rate well in comparison to the other organizational groups and also seemed to include a larger scope of activities. An unexpected benefit of the software benchmarking study was the identification of many opportunities for collaboration in areas including metrics, training, sharing of CMMI experiences and resources such as instructors and CMMI Lead Appraisers, and even sharing of assets such as documented processes. A further unexpected benefit of the study was the feedback on NASA practices that was received from some of the organizations interviewed. From that feedback, other potential areas where NASA could improve were highlighted, such as accuracy of software cost estimation and budgetary practices. The detailed report contains discussion of the practices noted in each of the topic areas, as well as a summary of observations and recommendations from each of the topic areas. The resulting 24 recommendations from the topic areas were then consolidated to eliminate duplication and culled into a set of 14 suggested actionable recommendations. This final set of actionable recommendations, listed below, are items that can be implemented to improve NASA's software engineering practices and to help address many of the items that were listed in the NASA top software engineering issues. 1. Develop and implement standard contract language for software procurements. 2. Advance accurate and trusted software cost estimates for both procured and in-house software and improve the capture of actual cost data to facilitate further improvements. 3. Establish a consistent set of objectives and expectations, specifically types of metrics at the Agency level, so key trends and models can be identified and used to continuously improve software processes and each software development effort. 4. Maintain the CMMI Maturity Level requirement for critical NASA projects and use CMMI to measure organizations developing software for NASA. 5.onsolidate, collect and, if needed, develop common processes principles and other assets across the Agency in order to provide more consistency in software development and acquisition practices and to reduce the overall cost of maintaining or increasing current NASA CMMI maturity levels. 6. Provide additional support for small projects that includes: (a) guidance for appropriate tailoring of requirements for small projects, (b) availability of suitable tools, including support tool set-up and training, and (c) training for small project personnel, assurance personnel and technical authorities on the acceptable options for tailoring requirements and performing assurance on small projects. 7. Develop software training classes for the more experienced software engineers using on-line training, videos, or small separate modules of training that can be accommodated as needed throughout a project. 8. Create guidelines to structure non-classroom training opportunities such as mentoring, peer reviews, lessons learned sessions, and on-the-job training. 9. Develop a set of predictive software defect data and a process for assessing software testing metric data against it. 10. Assess Agency-wide licenses for commonly used software tools. 11. Fill the knowledge gap in common software engineering practices for new hires and co-ops.12. Work through the Science, Technology, Engineering and Mathematics (STEM) program with universities in strengthening education in the use of common software engineering practices and standards. 13. Follow up this benchmark study with a deeper look into what both internal and external organizations perceive as the scope of software assurance, the value they expect to obtain from it, and the shortcomings they experience in the current practice. 14. Continue interactions with external software engineering environment through collaborations, knowledge sharing, and benchmarking.

Rarick, Heather L.↗

NASA Software Engineering Benchmarking Effort

Benchmarking was very interesting and provided a wealth of information (1) We did see potential solutions to some of our "top 10" issues (2) We have an assessment of where NASA stands with relation to other aerospace/defense groups We formed new contacts and potential collaborations (1) Several organizations sent us examples of their templates, processes (2) Many of the organizations were interested in future collaboration: sharing of training, metrics, Capability Maturity Model Integration (CMMI) appraisers, instructors, etc. We received feedback from some of our contractors/ partners (1) Desires to participate in our training; provide feedback on procedures (2) Welcomed opportunity to provide feedback on working with NASA

Godfrey, Sally↗

NOSS Altimeter Detailed Algorithm specifications

The details of the algorithms and data sets required for satellite radar altimeter data processing are documented in a form suitable for (1) development of the benchmark software and (2) coding the operational software. The algorithms reported in detail are those established for altimeter processing. The algorithms which required some additional development before documenting for production were only scoped. The algorithms are divided into two levels of processing. The first level converts the data to engineering units and applies corrections for instrument variations. The second level provides geophysical measurements derived from altimeter parameters for oceanographic users.

Hancock, D. W.↗

A small evaluation suite for Ada compilers

After completing a small Ada pilot project (OCC simulator) for the Multi Satellite Operations Control Center (MSOCC) at Goddard last year, the use of Ada to develop OCCs was recommended. To help MSOCC transition toward Ada, a suite of about 100 evaluation programs was developed which can be used to assess Ada compilers. These programs compare the overall quality of the compilation system, compare the relative efficiencies of the compilers and the environments in which they work, and compare the size and execution speed of generated machine code. Another goal of the benchmark software was to provide MSOCC system developers with rough timing estimates for the purpose of predicting performance of future systems written in Ada.

Wilke, Randy↗

Benchmarking hypercube hardware and software

It was long a truism in computer systems design that balanced systems achieve the best performance. Message passing parallel processors are no different. To quantify the balance of a hypercube design, an experimental methodology was developed and the associated suite of benchmarks was applied to several existing hypercubes. The benchmark suite includes tests of both processor speed in the absence of internode communication and message transmission speed as a function of communication patterns.

Grunwald, Dirk C.↗

A NASA initiative: Software engineering for reliable complex systems

The objective is the development of methods, technology, and skills that will enable NASA to cost-effectively specify, build, and manage reliable software which can evolve and be maintained over an extended period. The need for such software is rooted in the increasing integration of software and computing components into NASA systems. Current NASA Software Engineering expertise was applied toward some of the largest reliable systems including: shuttle launch; ground support; shuttle simulation; minor control; satellite tracking; and scientific data systems. Unfortunately, no theory exists for reliable complex software systems. NASA is seeking to fill this theoretical gap through a number of approaches. One such approach is to conduct research on theoretical foundations for managing complex software systems. It includes: communication models, new and modified paradigms, and life-cycle models. Another approach is research in the theoretical foundations for reliable software development and validation. It focuses upon formal specifications, programming languages, software engineering systems, software reuse, formal verification, and software safety. Further approaches involve benchmarking a NASA software environment, experimentation within the NASA context, evolution of present NASA methodology, and transfer of technology to the space station software support environment.

Holcomb, Lee B.↗

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↗

Permissible Exposure Level for Lunar Dusts: Gaps are Closing

Space faring nations plan to return human explorers to the moon within the next decade. Experience during the Apollo flights suggests that lunar dust will invariably get into the habitat where the finest portion (less than 5 micrometers) could be inhaled by the crew before it is cleared from the atmosphere. NASA is developing a database from which a 6-month, episodic exposure standard for lunar dust can be set. Three kinds of moon dust were prepared from a parent sample of Apollo 14 regolith #14003,96. Our goal was to prepare each type of dust sample with a mean diameter less than 2 m, which is suitable for instillation into the lungs of rats. The three samples were prepared as follows: separation from the parent sample using a fluidized bed, grinding using a jet mill grinder, or grinding with a ball-mill grinder. Grinding simulated restoration of surface activation of dust expected to occur at the surface of the moon on native lunar dust. We used two grinding methods because they seemed to produce different modes of activation. The effects of grinding were preserved by maintaining the dust in ultra-pure nitrogen until immediately before it was placed in suspension for administration to rats. The dust was suspended in physiological saline with 10% Survanta, a lung surfactant. Rats were given intratrachael instillations of the dust suspension at three doses. In addition to the three moon dusts (A, C and E), we instilled the same amount of a negative control (TiO2, B) and a highly-toxic, positive control (quartz, D). These additional mineral dusts were selected because they have well-established and very different permissible exposure levels (PELs). Our goal was to determine where lunar dusts fit between these extremes, and then estimate a PEL for each lunar dust. We evaluated many indices of toxicity to the lung. The figure shows the changes in lactate dehydrogenase (LDH), a marker of cell death, for the five dusts. Benchmark dose software (Version 2.1.2) from the Environmental Protection Agency was used to estimate the 10% effect levels (BMD(sub 10)) using five models. The best-fitting model was used to estimate the optimal BMD(sub 10) (table)

James, John T.↗

Modeling Respiratory Toxicity of Authentic Lunar Dust

The lunar expeditions of the Apollo operations from the 60 s and early 70 s have generated awareness about lunar dust exposures and their implication towards future lunar explorations. Critical analyses on the reports from the Apollo crew members suggest that lunar dust is a mild respiratory and ocular irritant. Currently, NASA s space toxicology group is functioning with the Lunar Airborne Dust Toxicity Assessment Group (LADTAG) and the National Institute for Occupational Safety and Health (NIOSH) to investigate and examine toxic effects to the respiratory system of rats in order to establish permissible exposure levels (PELs) for human exposure to lunar dust. In collaboration with the space toxicology group, LADTAG and NIOSH the goal of the present research is to analyze dose-response curves from rat exposures seven and twenty-eight days after intrapharyngeal instillations, and model the response using BenchMark Dose Software (BMDS) from the Environmental Protection Agency (EPA). Via this analysis, the relative toxicities of three types of Apollo 14 lunar dust samples and two control dust samples, titanium dioxide (TiO2) and quartz will be determined. This will be executed for several toxicity endpoints such as cell counts and biochemical markers in bronchoaveolar lavage fluid (BALF) harvested from the rats.

Santana, Patricia A.↗

Modelling Sonic Boom Propagation through Planetary Boundary Layer Turbulence near the Lateral Extent of the Carpet

Nonlinear acoustic propagation of sonic booms in the atmospheric boundary layer is considered in the context of a one-way solution to a third order wave equation. A split-step approach is utilized to compute different physical effects efficiently. Unlike previous approaches, the diffraction effects are computed exactly in the forward direction with no restriction on the angle of propagation. This results in more accurate modelling of sonic boom near the carpet edge. Heterogenous flow effects are incorporated with a wide-angle parabolic approximation. Nonlinear propagation is computed with a Burgers-Hayes method. Turbulence in the medium is constructed by the method of random Fourier modes. The turbulence spectra are constructed using an altitude dependent 3-dimensional von Karman spectrum. The turbulence field is considered frozen, as the eddy turnover time in the atmospheric boundary layer is generally much larger than the propagation time of the acoustic wave. Comparisons with benchmark predictions from the PCBoom software are conducted. The benchmark cases provide insight into the accuracy of the current prediction code for non-turbulent atmospheres. Future work is discussed regarding the prediction of shaped booms, boundary conditions, and predictions near the lateral extent of the boom carpet where previous approaches fail to capture the diffraction effects.

sonic boom↗

Multirate Flutter Suppression System Design for the Benchmark Active Controls Technology Wing: Methodology Application Software Toolbox - Part 2

To study the effectiveness of various control system design methodologies, the NASA Langley Research Center initiated the Benchmark Active Controls Project. In this project, the various methodologies were applied to design a flutter suppression system for the Benchmark Active Controls Technology (BACT) Wing. This report describes the user's manual and software toolbox developed at the University of Washington to design a multirate flutter suppression control law for the BACT wing.

Mason, Gregory S.↗

Space Flown Rodent Liver RNA Sequencing Data for Machine Learning in Space Biology Research

High-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. Data analysis has been accelerated in recent years by the adoption of artificial intelligence (AI) and machine learning (ML) techniques by biomedical researchers. In space biology research, RNAseq datasets from space-flown experimental samples are critical for characterizing the gene expression aberrations associated with exposure to spaceflight stressors. However, space biological experiments tend to be very low sample size, so identifying proper AI/ML algorithms for sequencing data analysis is an ongoing challenge since these algorithms typically require large sample size. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML”, focused on creating datasets meant for three main applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. These scientific benchmarks consist of an AI-ready dataset and a reference implementation on a specific scientific question. In this work, we focused on generating standardized datasets to allow the scientific community to benchmark AI/ML algorithms in the domain of space biology. We present here a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data as a collaboration between the NASA AI4LS (Artificial Intelligence for Life Sciences) working group. and NASA’s SMD. This dataset consists of space-flown and ground control mouse liver found in the NASA GeneLab omics database. However, to amplify the small sample number (n=112 samples) for ML purposes, we employ Gaussian noise and a generative adversarial network to extend this dataset to 6,000 synthetic samples, matching the original gene expression characteristics.

James Casaletto↗

How simple is software defect detection?

This study benchmarks several FSS techniques and reports several studies where a large set metrics were reduced to a handful with little loss of detection accuracy. This result raises the possibility that software defect detection may be much simpler than previously believed.

feature subset selection software fault model soft↗

Preliminary Computational Analysis of the (HIRENASD) Configuration in Preparation for the Aeroelastic Prediction Workshop

This paper presents preliminary computational aeroelastic analysis results generated in preparation for the first Aeroelastic Prediction Workshop (AePW). These results were produced using FUN3D software developed at NASA Langley and are compared against the experimental data generated during the HIgh REynolds Number Aero- Structural Dynamics (HIRENASD) Project. The HIRENASD wind-tunnel model was tested in the European Transonic Windtunnel in 2006 by Aachen University0s Department of Mechanics with funding from the German Research Foundation. The computational effort discussed here was performed (1) to obtain a preliminary assessment of the ability of the FUN3D code to accurately compute physical quantities experimentally measured on the HIRENASD model and (2) to translate the lessons learned from the FUN3D analysis of HIRENASD into a set of initial guidelines for the first AePW, which includes test cases for the HIRENASD model and its experimental data set. This paper compares the computational and experimental results obtained at Mach 0.8 for a Reynolds number of 7 million based on chord, corresponding to the HIRENASD test conditions No. 132 and No. 159. Aerodynamic loads and static aeroelastic displacements are compared at two levels of the grid resolution. Harmonic perturbation numerical results are compared with the experimental data using the magnitude and phase relationship between pressure coefficients and displacement. A dynamic aeroelastic numerical calculation is presented at one wind-tunnel condition in the form of the time history of the generalized displacements. Additional FUN3D validation results are also presented for the AGARD 445.6 wing data set. This wing was tested in the Transonic Dynamics Tunnel and is commonly used in the preliminary benchmarking of computational aeroelastic software.

Chwalowski, Pawel↗

CAE for thermal management of aerospace electronic boards using the BETAsoft program

Aerospace electronic boards require special attention to thermal management due to constraints such as their need to be light, small, and maintain high power densities. Also, cooling is mainly through conductive and radiative modes with minor or negligible convective cooling. Due to these particular requirements, thermal design has become an integrated part of the electronic design process in order to avoid expensive repeat prototyping and to ensure high reliability. To achieve high speed simulations, the BETAsoft code uses semi-empirical formulations and an advanced finite difference scheme that incorporates local adaptive grids. Detailed conduction, convection and radiation heat transfer is considered. Various benchmark verifications of the software simulation compared to infrared images typically prove to be within 10% of each other. The thermal analysis of a sample avionic card in a natural convection environment is shown. Then, the individual effects of attaching metal screws to the casing, increasing radiative emissivities of the casing, increasing the conductance of the wedge lock, adding an aluminum core to the board, adding metal strips in board layers, inserting conduction pads under components, and adding heat sinks to components are demonstrated.

Bobish, Kimberly↗

Creating Benchmark Data for Artificial Intelligence and Machine Learning Space Biology Research

To identify an appropriate AI/ML approach for a specific problem, the best practice is to measure algorithm performance through the benchmarking process. A scientific benchmark consists of an AI-ready dataset and a reference implementation on a specific scientific question. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML to create scientific benchmark datasets in three applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. Currently, there are no standardized datasets available to benchmark AI/ML algorithms in the domain of space biology. In this work, we constructed two AI/ML-ready biological datasets from experiments in space-flown mice: cellular imaging and RNA-seq. First, radiation-exposed immune cells harbor DNA damage foci that can be fluorescently marked to visualize the amount of damage following exposure to ionizing radiation. However, such large datasets are difficult to analyze visually, due to imaging inconsistencies and human bias, and classical image processing approaches can fail on imaging artifacts. AI/ML are therefore exciting alternative, providing the speed of machines and the accuracy of humans. We have made this dataset available at https://registry.opendata.aws/bps_microscopy/. Second, high-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. However, most sequencing datasets suffer from high dimensionality and low sample count. In this work, we used a generative adversarial network to synthesize a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data with sufficient space-flown and ground control mouse liver samples from NASA GeneLab. This dataset is available at https://registry.opendata.aws/bps_rnaseq/. These datasets are now fully open the Space Biology community to test their favorite AI/ML approaches.

James Casaletto↗

The TSO Logic and G2 Software Product

This internship assignment for spring 2014 was at John F. Kennedy Space Center (KSC), in NASAs Engineering and Technology (NE) group in support of the Control and Data Systems Division (NE-C) within the Systems Hardware Engineering Branch. (NEC-4) The primary focus was in system integration and benchmarking utilizing two separate computer software products. The first half of this 2014 internship is spent in assisting NE-C4s Electronics and Embedded Systems Engineer, Kelvin Ruiz and fellow intern Scott Ditto with the evaluation of a newly piece of software, called G2. Its developed by the Gensym Corporation and introduced to the group as a tool used in monitoring launch environments. All fellow interns and employees of the G2 group have been working together in order to better understand the significance of the G2 application and how KSC can benefit from its capabilities. The second stage of this Spring project is to assist with an ongoing integration of a benchmarking tool, developed by a group of engineers from a Canadian based organization known as TSO Logic. Guided by NE-C4s Computer Engineer, Allen Villorin, NASA 2014 interns put forth great effort in helping to integrate TSOs software into the Spaceport Processing Systems Development Laboratory (SPSDL) for further testing and evaluating. The TSO Logic group claims that their software is designed for, monitoring and reducing energy consumption at in-house server farms and large data centers, allows data centers to control the power state of servers, without impacting availability or performance and without changes to infrastructure and the focus of the assignment is to test this theory. TSOs Aaron Rallo Founder and CEO, and Chris Tivel CTO, both came to KSC to assist with the installation of their software in the SPSDL laboratory. TSOs software is installed onto 24 individual workstations running three different operating systems. The workstations were divided into three groups of 8 with each group having its own operating system. The first group is comprised of Ubuntus Debian -based Linux the second group is windows 7 Professional and the third group ran Red Hat Linux. The highlight of this portion of the assignment is to compose documentation expressing the overall impression of the software and its capabilities.

TSO Logic↗