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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.

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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Damage Tolerance Comparison of IM7/8552 and T1100/3960 Carbon Fiber/Epoxy Sandwich Structure in Support of the Space Launch System Payload Adapter Fitting

As technology evolves and improves within the science of composite materials, new fiber/ resin systems are being developed for improved properties given certain loading and environmental scenarios. Improving the room temperature damage tolerance capabilities has long been one of the goals in the carbon fiber/polymer composite industry. Recently a new fiber/epoxy system has been introduced that is claimed to have superior damage tolerance capabilities. To examine if this new carbon fiber/epoxy composite material would be of benefit to a program to manufacture a Payload Adapter Fitting (PAF) for NASA’s Space Launch System (SLS) rocket, the question was asked as to just how much damage tolerance could be realized if this new system were used. Compression after impact (CAI) strength of sandwich structure is one of the leading metrics being used to evaluate materials for the PAF program. As a result, a comparison of this new fiber/resin system with a very common (and planned baseline) fiber/resin system with respect to CAI was considered in this study. While it was already known that the older, baseline carbon fiber structure would not have as good damage tolerance characteristics as the newer carbon fiber system, the quantitative difference in damage tolerance was sought in this study since no other CAI data could be found in open literature on sandwich structures made with this new fiber/resin system.

A.T. Nettles↗
NASA NTRSDate not supplied

Creating A Consistent Historical NASA POWER Solar Radiation Dataset to Support Renewable Energy, Building Energy Efficiency and Agro-Climatology Decisions

Prediction of Worldwide Energy Resources (POWER) project provides irradiance dataset to support renewable energy, building energy efficiency and agricultural needs. These datasets are derived from Global Energy and Water Cycle Experiment Surface Radiation Budget (GEWEX SRB) and Clouds and the Earth’s Radiant Energy System (CERES SYN1Deg). A systematic bias has been reported between these two datasets for the years with overlapping observations. For obtaining a consistent climate data record spanning the entire time record of observations, it is crucial to understand and remove the bias in the irradiance dataset. Inconsistency in solar radiation data can lead to inaccurate conclusions about solar energy potential and obscure real trends in solar radiation patterns that would impact energy availability assessments. In this study, we adapt quantile mapping approach to remove the systematic bias and to improve reliability of shortwave and longwave irradiance data. We present a validation of the bias corrected data against ground truth. For each 1° latitude and 1° longitude grid box across the globe, we match the CDFs of the reference dataset (CERES SYN1Deg) to that of the SRB dataset, thereby, adjusting the irradiance values to match the empirical distribution of two different measurements. The performance of quantile mapping is evaluated by using the metrics such as Mean Absolute Deviation (MAD). The results indicate that the quantile mapping significantly improves the accuracy and reliability of solar irradiance dataset especially for the weather conditions associated with high cloud cover and extreme irradiance values. The initial range of MAD for the studied sites for daily data was 4 to 19 Wm-2. After correction these reduced to 3 to 7 Wm-2. The findings from this study have important implications for solar energy system design, agricultural planning, and climate modeling community. Reducing the inconsistency and biases in solar irradiance dataset can enable better planning and operation of solar energy systems, leading to increased efficiency and cost-effectiveness. Additionally, this work also contributes to the statistical post-processing techniques in the renewable energy domain and highlights the potential of historical and near-real-time NASA POWER dataset as a valuable resource for solar energy research and applications.

POWER↗
NASA NTRSDate not supplied

Field Tests With Trident Drill in Bishop Tuff Help Prepare for Future Missions to Moon and Mars

We performed drilling in volcanic deposits near Bishop California using an engineering model of the Honeybee Robotics TRIDENT (The Regolith and Ice Drill for Exploration of New Terrains) drill [1] a rotary percussive 1-meter class drill that is carried on the PRIME1and VIPER (Volatiles Investigating Polar Exploration Rover)[2] missions that launch in 2024. A similar drilling system was planned for the proposed Icebreaker Discovery class mission to Mars [3] and the Mars Life Explorer mission recommended by the 2020 Decadal Survey of planetary science [4]. The objectives of the project were (1) to use data collected by the drill for operational purposes as a probe of subsurface material properties in formations that are analogous to those that may be encountered on planetary surfaces; (2) correlate subsurface structures with those deduced from Ground Penetrating Radar (GPR); and (3) inspect the boreholes after they were drilled to test PERISCOPE (Probe for Exploring Regolith and Ice by Subsurface Classification of Organics, polycyclic aromatic hydrocarbons (PAHs), and Elements), a newly developed downhole UV fluorescence spectrometer [5].

Carol R. Stoker↗
NASA NTRS1976

Formulation of detailed consumables management models for the development (preoperational) period of advanced space transportation system. Volume 1: Detailed requirements for the mission planning processor

Detailed requirements for the mission planning processor are documented. The mission planning processor is a user oriented tool for consumables management and is part of the total consumables subsystem management concept. A quasi top-down approach was applied to the design of the mission planning processor. Interface requirements, input/output, and data base concepts were considered before computational processing. Existing analytical models were investigated for applicability before new models were developed. The mission planning processor was designed for an interactive system using demand terminals for input/outputdisplay and interfacing with an updateable mission data bank. The control and support routines provide the user interface, peripheral data handling, program control, and support functions required by the mission planning processor for execution on an interactive system. A description, interface requirements, definition of internal variables, listing of input data, processing flow diagram, and listing of output data are presented for each routine.

Connelly, L. C.↗
NASA NTRS2006

Model-Unified Planning and Execution for Distributed Autonomous System Control

The Intelligent Distributed Execution Architecture (IDEA) is a real-time architecture that exploits artificial intelligence planning as the core reasoning engine for interacting autonomous agents. Rather than enforcing separate deliberation and execution layers, IDEA unifies them under a single planning technology. Deliberative and reactive planners reason about and act according to a single representation of the past, present and future domain state. The domain state behaves the rules dictated by a declarative model of the subsystem to be controlled, internal processes of the IDEA controller, and interactions with other agents. We present IDEA concepts - modeling, the IDEA core architecture, the unification of deliberation and reaction under planning - and illustrate its use in a simple example. Finally, we present several real-world applications of IDEA, and compare IDEA to other high-level control approaches.

Aschwanden, Pascal↗
NASA NTRS2010

Planning and Execution for an Autonomous Aerobot

The Aerial Onboard Autonomous Science Investigation System (AerOASIS) system provides autonomous planning and execution capabilities for aerial vehicles (see figure). The system is capable of generating high-quality operations plans that integrate observation requests from ground planning teams, as well as opportunistic science events detected onboard the vehicle while respecting mission and resource constraints. AerOASIS allows an airborne planetary exploration vehicle to summarize and prioritize the most scientifically relevant data; identify and select high-value science sites for additional investigation; and dynamically plan, schedule, and monitor the various science activities being performed, even during extended communications blackout periods with Earth.

Gaines, Daniel M.↗
NASA NTRS1981

The potential evolution of the space transportation system

An evolutionary plan satisfying the requirements of permanent manned space stations in low orbit by 1990 along with geostationary orbit sortie capabilities by 2000 is proposed. The program, to be gradually implemented with near-term technology, comprises: (1) unmanned platforms in low and geostationary orbits; (2) growth and development of these platforms into manned systems; (3) satellite checkout, handling, repair and maneuvering by means of special techniques, such as teleoperated docking, berthing and component exchange; and (4) transportation, by means of unmanned, cargo-carrying derivatives of the Space Shuttle and reuseable, space-based orbit transfer vehicles. Attention is given the envisioned configurations of both manned and unmanned orbital platforms, through a series of progress diagrams.

Bekey, I.↗
NASA NTRS1992

A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems

In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

Sartori, Michael A.↗
NASA NTRS1983

PDSS configuration control plan and procedures

The payload development support system (PDSS) configuration control plan and procedures are presented. These plans and procedures establish the process for maintaining configuration control of the PDSS system, especially the Spacelab experiment interface device's (SEID) RAU, HRM, and PDI interface simulations and the PDSS ECOS DEP Services simulation. The plans and procedures as specified are designed to provide a simplified but complete configuration control process. The intent is to require a minimum amount of paperwork but provide total traceability of PDSS during experiment test activities.

Source record↗
NASA NTRS2005

D-Side: A Facility and Workforce Planning Group Multi-criteria Decision Support System for Johnson Space Center

"To understand and protect our home planet, to explore the universe and search for life, and to inspire the next generation of explorers" is NASA's mission. The Systems Management Office at Johnson Space Center (JSC) is searching for methods to effectively manage the Center's resources to meet NASA's mission. D-Side is a group multi-criteria decision support system (GMDSS) developed to support facility decisions at JSC. D-Side uses a series of sequential and structured processes to plot facilities in a three-dimensional (3-D) graph on the basis of each facility alignment with NASA's mission and goals, the extent to which other facilities are dependent on the facility, and the dollar value of capital investments that have been postponed at the facility relative to the facility replacement value. A similarity factor rank orders facilities based on their Euclidean distance from Ideal and Nadir points. These similarity factors are then used to allocate capital improvement resources across facilities. We also present a parallel model that can be used to support decisions concerning allocation of human resources investments across workforce units. Finally, we present results from a pilot study where 12 experienced facility managers from NASA used D-Side and the organization's current approach to rank order and allocate funds for capital improvement across 20 facilities. Users evaluated D-Side favorably in terms of ease of use, the quality of the decision-making process, decision quality, and overall value-added. Their evaluations of D-Side were significantly more favorable than their evaluations of the current approach. Keywords: NASA, Multi-Criteria Decision Making, Decision Support System, AHP, Euclidean Distance, 3-D Modeling, Facility Planning, Workforce Planning.

Tavana, Madjid↗
NASA NTRS2013

Scheduling Spitzer: The SIRPASS Story

NASA's Spitzer Space Telescope was launched on August 25, 2003 from Florida's Cape Canaveral Air Force Base. Drifting in a unique Earth-trailing orbit around the Sun, Spitzer sees an optically invisible universe dominated by dust and stars. Since 1997, the Spitzer Integrated Resource Planning and Scheduling System (SIRPASS) has helped produce spacecraft activity plans for the Spitzer Space Telescope. SIRPASS is used by members of the Observatory Planning and Scheduling Team to plan, schedule and sequence the Telescope from data made available to them from the science and engineering community. Because of the volume of data that needs to be scheduled, SIRPASS offers a variety of automated assistants to aid in this task. This paper will describe the functional elements of the SIRPASS software system -- emphasizing the role that automation plays in the system -- and will highlight lessons learned for the software developer from a decade of Spitzer Space Telescope operations experience.

flight systems↗
NASA NTRS1991

Wind Shear radar program future plans

The status of the Windshear Radar Program at the Collins Air Transport Division of Rockwell International is given in viewgraph form. Topics covered include goals, modifications to the WXR-700 system, flight test plans, technical approaches, design considerations, system considerations, certification, and future plans.

Robertson, Roy E.↗
NASA NTRS1990

Resource Allocation Planning Helper (RALPH): Lessons learned

The current task of Resource Allocation Process includes the planning and apportionment of JPL's Ground Data System composed of the Deep Space Network and Mission Control and Computing Center facilities. The addition of the data driven, rule based planning system, RALPH, has expanded the planning horizon from 8 weeks to 10 years and has resulted in large labor savings. Use of the system has also resulted in important improvements in science return through enhanced resource utilization. In addition, RALPH has been instrumental in supporting rapid turn around for an increased volume of special what if studies. The status of RALPH is briefly reviewed and important lessons learned from the creation of an highly functional design team are focused on through an evolutionary design and implementation period in which an AI shell was selected, prototyped, and ultimately abandoned, and through the fundamental changes to the very process that spawned the tool kit. Principal topics include proper integration of software tools within the planning environment, transition from prototype to delivered to delivered software, changes in the planning methodology as a result of evolving software capabilities and creation of the ability to develop and process generic requirements to allow planning flexibility.

Durham, Ralph↗
NASA NTRS1990

An expert system based software sizing tool, phase 2

A software tool was developed for predicting the size of a future computer program at an early stage in its development. The system is intended to enable a user who is not expert in Software Engineering to estimate software size in lines of source code with an accuracy similar to that of an expert, based on the program's functional specifications. The project was planned as a knowledge based system with a field prototype as the goal of Phase 2 and a commercial system planned for Phase 3. The researchers used techniques from Artificial Intelligence and knowledge from human experts and existing software from NASA's COSMIC database. They devised a classification scheme for the software specifications, and a small set of generic software components that represent complexity and apply to large classes of programs. The specifications are converted to generic components by a set of rules and the generic components are input to a nonlinear sizing function which makes the final prediction. The system developed for this project predicted code sizes from the database with a bias factor of 1.06 and a fluctuation factor of 1.77, an accuracy similar to that of human experts but without their significant optimistic bias.

Friedlander, David↗