SEARCH · Search NASA

Results for “software competition”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

All sources NASA NTRS DOE OSTI

NASA NTRS1997

Using Common Graphics Paradigms Implemented in a Java Applet to Represent Complex Scheduling Requirements

The experiments planned for the International Space Station promise to be complex, lengthy and diverse. The scarcity of the space station resources will cause significant competition for resources between experiments. The scheduling job facing the Space Station mission planning software requires a concise and comprehensive description of the experiments' requirements (to ensure a valid schedule) and a good description of the experiments' flexibility (to effectively utilize available resources). In addition, the continuous operation of the station, the wide geographic dispersion of station users, and the budgetary pressure to reduce operations manpower make a low-cost solution mandatory. A graphical representation of the scheduling requirements for station payloads implemented via an Internet-based application promises to be an elegant solution that addresses all of these issues. The graphical representation of experiment requirements permits a station user to describe his experiment by defining "activities" and "sequences of activities". Activities define the resource requirements (with alternatives) and other quantitative constraints of tasks to be performed. Activities definitions use an "outline" graphics paradigm. Sequences define the time relationships between activities. Sequences may also define time relationships with activities of other payloads or space station systems. Sequences of activities are described by a "network" graphics paradigm. The bulk of this paper will describe the graphical approach to representing requirements and provide examples that show the ease and clarity with which complex requirements can be represented. A Java applet, to run in a web browser, is being developed to support the graphical representation of payload scheduling requirements. Implementing the entry and editing of requirements via the web solves the problems introduced by the geographic dispersion of users. Reducing manpower is accomplished by developing a concise representation which eliminates the misunderstanding possible with verbose representations and which captures the complete requirements and flexibility of the experiments.

Jaap, John↗

NASA NTRS2002

A Data-Driven Solution for Performance Improvement

Marketed as the "Software of the Future," Optimal Engineering Systems P.I. EXPERT(TM) technology offers statistical process control and optimization techniques that are critical to businesses looking to restructure or accelerate operations in order to gain a competitive edge. Kennedy Space Center granted Optimal Engineering Systems the funding and aid necessary to develop a prototype of the process monitoring and improvement software. Completion of this prototype demonstrated that it was possible to integrate traditional statistical quality assurance tools with robust optimization techniques in a user- friendly format that is visually compelling. Using an expert system knowledge base, the software allows the user to determine objectives, capture constraints and out-of-control processes, predict results, and compute optimal process settings.

Source record↗

NASA NTRS2002

A "Tread" Ahead of the Competition

Through a consortium formed by NASA's Glenn Research Center and the Great Lakes Industrial Technology Center, Goodyear acquired a software use agreement for NASA's Micromechanics Analysis Code (MAC), in an effort to design stronger and safer tires. Based on the Generalized Method of Cells micromechanics methodology, the MAC technology has allowed Goodyear scientists and engineers to perform structural analysis of composite laminates for tires all in one step, rather than the several steps previously required. Currently, the MAC code can be used to assess and optimize composite laminates; set cord-spacing guidelines (the diameter and distance between cords may impact the overall durability of a tire); explain structural impact of geometrical configurations; and compare the behavior of the different wire constructions that make up a tire. Furthermore, the MAC software contains a built-in material database and several representative volume elements for a wider choice of composites to better represent the plies and belts in a tire. The end result of the process ultimately reduces the time spent on building, testing, and adjusting tires.

Source record↗

NASA NTRS1985

The search for extraterrestrial life: Recent developments; Proceedings of the Symposium, Boston University, MA, June 18-21, 1984

The conference presents papers on the history of the search for extraterrestrial life, the scientific rationale and methods used in the search for other planetary systems, the detection of distant planets with the Space Telescope, planetary searches using optical astrometric interferometers, and infrared spectral identification of complex organic molecules in interstellar grains. Also considered are universal protein ancestors from hydrogen cyanide and water, astronomical sources of polarized light and their role in determining molecular chirality on earth, the universal diagrams and life in the universe, the precambrian evolution of terrestrial life and a thermodynamic approach to the occurrance and appearance of galactic life forms. Papers are also presented on the Ohio Seti program, lunar reflections of terrestrial radio leakage, the multichannel spectrum analyzer, software implementation of detection algorithms for the MCSA, the Serendip II design, galactic colonization and competition in a young galactic disk, implications of ancient and future migrations, extraterrestrial intelligence, the ineviability and the possible structures of supercivilizations, planetary, interplanetary and interstellar organic matter, and universal aspects of biological evolution.

Papagiannis, M. D.↗

NASA NTRS2016

Remote Adaptive Motor Resistance Training Exercise Apparatus and Method of Use Thereof

The invention comprises a method and/or an apparatus using a computer configured exercise system equipped with an electric motor to provide physical resistance to user motion in conjunction with means for sharing exercise system related data and/or user performance data with a secondary user, such as a medical professional, a physical therapist, a trainer, a computer generated competitor, and/or a human competitor. For example, the exercise system is used with a remote trainer to enhance exercise performance, with a remote medical professional for rehabilitation, and/or with a competitor in a competition, such as in a power/weightlifting competition or in a video game. The exercise system is optionally configured with an intelligent software assistant and knowledge navigator functioning as a personal assistant application.

Reich, Alton↗

NASA NTRS2017

Remote Adaptive Motor Resistance Training Exercise Apparatus and Method of Use Thereof

Reich, Alton↗

NASA NTRS2018

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is a suite of tools for the analysis of porous materials and generation of material microstructures. From microstructural data, often obtained through X-ray microtomography, PuMA can determine a number of effective material properties and perform material response simulations. Version 2.2 includes capabilities for computing volume fractions, porosity, specific surface area, effective thermal and electrical conductivities, and continuum and rarefied diffusive tortuosity. PuMA can also simulate competitive diffusion/reaction processes at the micro-scale, such as surface oxidation. In this poster, recent advancements to the PuMA software are detailed, including the full refactoring of PuMA into v3.0, a new module to compute heat conduction in anisotropic materials, a particle method for simulating molecular beam experiments, a new finite-volume Laplace solver, complex fibrous material generation, woven material generation, and a coupling of PuMA with the DAKOTA software for advanced statistics.

PuMA↗

DOE OSTI2026

JUSTIFI: Software for Improving Performance Objectives via Energy Efficiency

With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1991

A nonparametric software-reliability growth model

The authors (1985) previously introduced a nonparametric model for software-reliability growth which is based on complete monotonicity of the failure rate. The authors extend the completely monotone software model by developing a method for providing long-range predictions of reliability growth, based on the model. They derive upper and lower bounds on extrapolation of the failure rate and the mean function. These are then used to obtain estimates for the future software failure rate and the mean future number of failures. Preliminary evaluation indicates that the method is competitive with parametric approaches, while being more robust.

Sofer, Ariela↗

NASA NTRS2007

Smart Payload Development for High Data Rate Instrument Systems

This slide presentation reviews the development of smart payloads instruments systems with high data rates. On-board computation has become a bottleneck for advanced science instrument and engineering capabilities. In order to improve the computation capability on board, smart payloads have been proposed. A smart payload is a Localized instrument, that can offload the flight processor of extensive computing cycles, simplify the interfaces, and minimize the dependency of the instrument on the flight system. This has been proposed for the Mars mission, Mars Atmospheric Trace Molecule Spectroscopy (MATMOS). The design of this system is discussed; the features of the Virtex-4, are discussed, and the technical approach is reviewed. The proposed Hybrid Field Programmable Gate Array (FPGA) technology has been shown to deliver breakthrough performance by tightly coupling hardware and software. Smart Payload designs for instruments such as MATMOS can meet science data return requirements with more competitive use of available on-board resources and can provide algorithm acceleration in hardware leading to implementation of better (more advanced) algorithms in on-board systems for improved science data return

Virtex-4↗

NASA NTRSDate not supplied

OpenNEX: An open collaboration platform for the earth science community

Satellite data from the past several decades provide the most consistent record of land-surface processes that form the basis for scientific assessments of the impacts of climate variations and changes on the environment and human social-economical activities. During this time, scientific research on the characterization and assessment of environmental changes had tended to focus on large-scale land-surface changes with significant social-economic impacts. Increasingly, attention is shifting toward changes that occur more locally and that most directly relate to the everyday life of the majority of the population. In addition, there has been needs to develop management and policy decision support systems that are based on local environmental information. Almost at the same time, the advancement in sensor technology has allowed us to collect an unprecedented volume of environmental data. These data must be curated and analyzed to extract useful information for research and decision support purposes. Established in 2013 and funded by NASA, the Open NASA Earth eXchange (OpenNEX; https://opennex.org/ , Jia et al., 2019 ) project partnered with Amazon Web Services (AWS) to make available a large amount of Earth observing data, modeling results, and analysis tools on the AWS. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of NASA data assets and software tools. To encourage the public's engagement in this project, NASA ran virtual workshops and prize competitions. The virtual workshops provided online lectures and tutorials about how prominent scientists used the data in their research and the tutorials gave examples how to use the tools to interrogate the data in the Amazon cloud. Finally, the prize competitions allowed much wider participation in the OpenNEX project and enable testing the non-traditional projects and out-of-box ideas. OpenNEX has continued to evolve and mature. Here, we highlight new features and functionalities available to the community.

Jian Zhang↗

DOE OSTI2026

Implementing a unified solver for nonlinearly constrained optimization

SQP and interior-point methods (also referred to as Lagrange-Newton methods) typically share key algorithmic components, such as strategies for computing descent directions and mechanisms that promote global convergence. Building on this insight, we introduce a unifying framework with eight building blocks that abstracts the workflows of Lagrange-Newton methods. We then present Uno, a modular C++ solver that implements our unifying framework and allows the automatic combination of a wide range of strategies with no programming effort from the user. Uno is meant to (1) organize mathematical optimization strategies into a coherent hierarchy; (2) offer a wide range of efficient and robust methods that can be compared for a given instance; (3) enable researchers to experiment with novel optimization strategies; and (4) reduce the cost of development and maintenance of multiple optimization solvers. Uno’s software design allows user to compose new customized solvers for emerging optimization areas such as robust optimization or optimization problems with complementarity constraints, while building on reliable nonlinear optimization techniques. We demonstrate that Uno is highly competitive against state-of-the-art solvers filterSQP, IPOPT, SNOPT, MINOS, LANCELOT, LOQO, and CONOPT on a subset of 429 small problems from the CUTE collection. Uno is available as open-source software under the MIT license at https://github.com/cvanaret/Uno and via its C, Julia, Python, Fortran, and AMPL interfaces.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Technical Report on the Belle II Summer Workshop and Explorer Workshop 2023

The 2023 Belle II Summer workshop took place July 24-28, 2023 at Duke University in Durham. The meeting webpage can be found at https://indico.belle2.org/event/8841/. The meeting had 58 registered participants with the overwhelming majority attending in person. The event at giving beginning graduate students and postdocs an overview over the Belle II physics program and detector as well as an in-depth exploration of the Belle II software. For the latter, several hands-on sessions were organized to introduce participants to the Belle II software as well as more specialized topics in statistics and Machine Learning. The workshop also featured an ML/AI competition. In addition to the DOE support, the workshop was also supported by the Duke Physics department. We were able to host almost all students that so wished in the Duke Dorms and provide a meal plan. The support enabled us to waive the registration fee for all participants and cover also part of the dorm costs. Furthermore, we covered travel costs for external speakers on ML/AI topics. Figures 1 and 2 show the group picture and a scene from the hands-on sessions, respectively.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2002

Comparisons of Kinematics and Dynamics Simulation Software Tools

Kinematic and dynamic analyses for moving bodies are essential to system engineers and designers in the process of design and validations. 3D visualization and motion simulation plus finite element analysis (FEA) give engineers a better way to present ideas and results. Marshall Space Flight Center (MSFC) system engineering researchers are currently using IGRIP from DELMIA Inc. as a kinematic simulation tool for discrete bodies motion simulations. Although IGRIP is an excellent tool for kinematic simulation with some dynamic analysis capabilities in robotic control, explorations of other alternatives with more powerful dynamic analysis and FEA capabilities are necessary. Kinematics analysis will only examine the displacement, velocity, and acceleration of the mechanism without considering effects from masses of components. With dynamic analysis and FEA, effects such as the forces or torques at the joint due to mass and inertia of components can be identified. With keen market competition, ALGOR Mechanical Event Simulation (MES), MSC visualNastran 4D, Unigraphics Motion+, and Pro/MECHANICA were chosen for explorations. In this study, comparisons between software tools were presented in terms of following categories: graphical user interface (GUI), import capability, tutorial availability, ease of use, kinematic simulation capability, dynamic simulation capability, FEA capability, graphical output, technical support, and cost. Propulsion Test Article (PTA) with Fastrac engine model exported from IGRIP and an office chair mechanism were used as examples for simulations.

Yeu-Sheng Paul Shiue↗

DOE OSTI2024

Supporting ARPA-E Power Grid Optimization (Final Report)

Pacific Northwest National Laboratory (PNNL), Arizona State University (ASU), Georgia Institute of Technology (Georgia Tech), Los Alamos National Laboratory (LANL), National Renewable Energy Laboratory (NREL), Texas A&M University (TAMU), The University of Texas at Austin (UT), and the University of Wisconsin-Madison (UW-M) supported the ARPA-E Grid Optimization (GO) Competition by providing a common problem formulation, data format, datasets, evaluation mechanism, scoring, rules, and results that resulted in the awarding of $\$9.24$ million dollars to teams from academia, industry, and national labs for solving three sets of increasingly difficult non-linear, security- constrained AC Optimal Powerflow (AC-OPF) optimization problems in order to increase the efficiency of the US Electric Grid. It is estimated that a 1% increase in efficiency can save $\$1$ billion. Current industry practices typically use a linear DC model (DC-OPF) in order solve the OPF problem within the time constraints of the operation schedule. The GO Competition challenges the best power engineers, mathematicians, and computer scientists to make possible operational decisions based on accurate physical models. To accomplish this, the GO Competition created a series of Challenges and funded teams to produce the best solver. Challenge 1 was to solve the security constrained Alternating Current Optimal Power Flow (ACOPF) problem. Challenge 2 extended that to by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and loads, and fast-start unit commitment (UC). Furthermore, Challenge 2 was a maximization problem while Challenge 1 was a minimization problem. While Challenge 3 was being developed, the entrants were invited to find better solutions to the Challenge 2 synthetic datasets with no restrictions on time, hardware, or algorithms. The Challenge 2 solutions turned out to be very good. Challenge 3 expanded the Challenge 2 problem further by using multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. These problems included active bid-in demand and topology optimization. Together the Challenges used nearly 30 million CPU hours. Since each team was working on the same problem, using the same data, and running on the same hardware, fair comparisons could be drawn as to the best solver. The datasets were varied enough, however, that the best solver for one dataset was not necessarily the best at another, so cumulative scores were used. The process was managed by the PNNL maintained website https://GOCompetition.energy.gov, where Entrants could find information about the problem, the data, the rules, submit their solver for evaluation, and see the scores of all the competing teams on a Leaderboard. Interest was world-wide but only American teams were eligible for prizes. The Competition has produced 34 journal articles 115 papers and been cited over 500 times in the literature, including 12 dissertations (4 from foreign countries; Columbia (2), Germany, and Italy) and 3 from the DOE ExaScale project. Software developed by Pearl Street Technologies for Challenges 1 and 2 is now deployed by Southwest Power Pool (SPP) and Midcontinent Independent Service Operator (MISO). Other teams have received inquiries from venture capitalists. Google DeepMind has thanked the Competition for making the datasets developed for the Competition public. They are using it to train machine learning models. The larger datasets have billions of unknowns to be solved for, but only a small percent matter in the final solution. Knowing what unknowns are important can dramatically speedup the solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Rasterization with Data-Parallel Primitives

Parallel rasterization can suffer from race conditions during fragment generation, which is traditionally addressed by using specialized hardware accessible via vendor graphics APIs. Unfortunately, graphics APIs are increasingly problematic on high-performance computers, either because they are not provided or because of concerns about dependencies with in situ visualization. In response, we present a hardware-agnostic rasterization algorithm that handles race conditions using only data-parallel primitives (DPPs), enabling efficient rendering on HPC systems without graphics API dependencies and aligning with recent efforts to deliver visualization software with DPPs. Our evaluation consists of three phases: (1) evaluating portability across different CPU and GPU architectures, (2) evaluating competitiveness with a community standard, and (3) evaluating performance across varying workloads and available parallelism. The supporting experiments run on both AMD and NVIDIA GPUs, considering data sets as large as 460 million triangles and 160 million pixels. While performance generally falls short of graphics API baselines, it achieves interactive frame rates on most workloads. As a result, we conclude our approach is a viable solution for rasterization on high-performance computers since our approach is portably performant across different architectures without the need for specialized vendor support.

Buckley, Makani [University of Oregon] (ORCID:0009↗

NASA NTRS1993

Grand challenges in mass storage: A systems integrators perspective

Within today's much ballyhooed supercomputing environment, with its CFLOPS of CPU power, and Gigabit networks, there exists a major roadblock to computing success; that of Mass Storage. The solution to this mass storage problem is considered to be one of the 'Grand Challenges' facing the computer industry today, as well as long into the future. It has become obvious to us, as well as many others in the industry, that there is no clear single solution in sight. The Systems Integrator today is faced with a myriad of quandaries in approaching this challenge. He must first be innovative in approach, second choose hardware solutions that are volumetric efficient; high in signal bandwidth; available from multiple sources; competitively priced, and have forward growth extendibility. In addition he must also comply with a variety of mandated, and often conflicting software standards (GOSIP, POSIX, IEEE, MSRM 4.0, and others), and finally he must deliver a systems solution with the 'most bang for the buck' in terms of cost vs. performance factors. These quandaries challenge the Systems Integrator to 'push the envelope' in terms of his or her ingenuity and innovation on an almost daily basis. This dynamic is explored further, and an attempt to acquaint the audience with rational approaches to this 'Grand Challenge' is made.

Lee, Richard R.↗

NASA NTRS2012

Engineering a Multimission Approach to Navigation Ground Data System Operations

The Mission Design and Navigation (MDNAV) Section at the Jet Propulsion Laboratory (JPL) supports many deep space and earth orbiting missions from formulation to end of mission operations. The requirements of these missions are met with a multimission approach to MDNAV ground data system (GDS) infrastructure capable of being shared and allocated in a seamless and consistent manner across missions. The MDNAV computing infrastructure consists of compute clusters, network attached storage, mission support area facilities, and desktop hardware. The multimission architecture allows these assets, and even personnel, to be leveraged effectively across the project lifecycle and across multiple missions simultaneously. It provides a more robust and capable infrastructure to each mission than might be possible if each constructed its own. It also enables a consistent interface and environment within which teams can conduct all mission analysis and navigation functions including: trajectory design; ephemeris generation; orbit determination; maneuver design; and entry, descent, and landing analysis. The savings of these efficiencies more than offset the costs of increased complexity and other challenges that had to be addressed: configuration management, scheduling conflicts, and competition for resources. This paper examines the benefits of the multimission MDNAV ground data system infrastructure, focusing on the hardware and software architecture. The result is an efficient, robust, scalable MDNAV ground data system capable of supporting more than a dozen active missions at once.

Mission Design and Navigation (MDNAV)↗