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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

System Engineering Issues for Avionics Survival in the Space Environment

This paper examines how the system engineering process influences the design of a spacecraft's avionics by considering the space environment. Avionics are susceptible to the thermal, radiation, plasma, and meteoroids/orbital debris environments. The environment definitions for various spacecraft mission orbits (LEO/low inclination, LEO/Polar, MEO, HEO, GTO, GEO and High ApogeeElliptical) are discussed. NASA models and commercial software used for environment analysis are reviewed. Applicability of technical references, such as NASA TM-4527 "Natural Orbital Environment Guidelines for Use in Aerospace Vehicle Development" is discussed. System engineering references, such as the MSFC System Engineering Handbook, are reviewed to determine how the environments are accounted for in the system engineering process. Tools and databases to assist the system engineer and avionics designer in addressing space environment effects on avionics are described and usefulness assessed.

Pavelitz, Steven↗
NASA NTRS1996

User-Centered Indexing for Adaptive Information Access

We are focusing on information access tasks characterized by large volume of hypermedia connected technical documents, a need for rapid and effective access to familiar information, and long-term interaction with evolving information. The problem for technical users is to build and maintain a personalized task-oriented model of the information to quickly access relevant information. We propose a solution which provides user-centered adaptive information retrieval and navigation. This solution supports users in customizing information access over time. It is complementary to information discovery methods which provide access to new information, since it lets users customize future access to previously found information. It relies on a technique, called Adaptive Relevance Network, which creates and maintains a complex indexing structure to represent personal user's information access maps organized by concepts. This technique is integrated within the Adaptive HyperMan system, which helps NASA Space Shuttle flight controllers organize and access large amount of information. It allows users to select and mark any part of a document as interesting, and to index that part with user-defined concepts. Users can then do subsequent retrieval of marked portions of documents. This functionality allows users to define and access personal collections of information, which are dynamically computed. The system also supports collaborative review by letting users share group access maps. The adaptive relevance network provides long-term adaptation based both on usage and on explicit user input. The indexing structure is dynamic and evolves over time. Leading and generalization support flexible retrieval of information under similar concepts. The network is geared towards more recent information access, and automatically manages its size in order to maintain rapid access when scaling up to large hypermedia space. We present results of simulated learning experiments.

Chen, James R.↗
NASA NTRS2003

Three Dimensional Numerical Simulation of Rocket-based Combined-cycle Engine Response During Mode Transition Events

The GTX program at NASA Glenn Research Center is designed to develop a launch vehicle concept based on rocket-based combined-cycle (RBCC) propulsion. Experimental testing, cycle analysis, and computational fluid dynamics modeling have all demonstrated the viability of the GTX concept, yet significant technical issues and challenges still remain. Our research effort develops a unique capability for dynamic CFD simulation of complete high-speed propulsion devices and focuses this technology toward analysis of the GTX response during critical mode transition events. Our principal attention is focused on Mode 1/Mode 2 operation, in which initial rocket propulsion is transitioned into thermal-throat ramjet propulsion. A critical element of the GTX concept is the use of an Independent Ramjet Stream (IRS) cycle to provide propulsion at Mach numbers less than 3. In the IRS cycle, rocket thrust is initially used for primary power, and the hot rocket plume is used as a flame-holding mechanism for hydrogen fuel injected into the secondary air stream. A critical aspect is the establishment of a thermal throat in the secondary stream through the combination of area reduction effects and combustion-induced heat release. This is a necessity to enable the power-down of the rocket and the eventual shift to ramjet mode. Our focus in this first year of the grant has been in three areas, each progressing directly toward the key initial goal of simulating thermal throat formation during the IRS cycle: CFD algorithm development; simulation of Mode 1 experiments conducted at Glenn's Rig 1 facility; and IRS cycle simulations. The remainder of this report discusses each of these efforts in detail and presents a plan of work for the next year.

Edwards, Jack R.↗
NASA NTRS2014

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.

VanZwieten, Tannen↗
NASA NTRS2022

Flow Visualization to Complement Modern Wing Tunnel Testing

In recent times, wind tunnel testing at the NASA Ames Unitary Plan Wind Tunnel (UPWT) seeks to validate computational fluid dynamics (CFD) tools. To that end, we find that now more than ever, flow visualization is a powerful capability that provides context to the experimental results bringing real-time insight to the researcher. It enables us to answer questions like: “Why does this drag polar look different?” or “What is the source of this tone in the microphone data?”. Flow visualization can verify that assumptions made in the CFD model are correct, addressing questions like: “Are our trip dots the correct size and location?” or “Does the position of this shock match our prediction?”. Techniques such as infrared flow visualization and schlieren / shadowgraph are powerful capabilities that when taken together can provide results as to the nature of the fluid structure interaction at a test condition in a format that pairs well with computational results. When properly integrated these measurements can be taken with no impact on the productivity of the test program, supplementing traditional measurements and often discovering something unforeseen, helping the researcher to answer those slippery aerodynamic questions and ultimately build confidence in the accuracy of a model.

wind tunnel↗
DOE OSTI2022

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2024

Geological Thermal Energy Storage (GeoTES) Charged with Solar Thermal Technology Using Depleted Oil/Gas Reservoirs and Carnot-Battery Technique Using Shallow Reservoirs: Preprint

Geological thermal energy storage (GeoTES) utilizes the underground reservoirs to storage and dispatch energy per given demand schedule over a time scale up to seasons of a year. The energy input can be of various sources/forms; in this paper, we investigate 1) the GeoTES technology with solar thermal hybridization and using depleted oil/gas reservoirs; 2) the GeoTES technology with heat pumps charged by excess renewable electricity and using low-temperature shallow reservoirs. For each GeoTES technology, we carry out the suitability analysis of candidate reservoirs, develop initial techno-economic models, and validate the model with selected case study. The paper provides an overview of our technical progress on the topics of concern and aims to promote a wider acceptance of the GeoTES technologies in the future energy market.

Carnot battery↗
DOE OSTI2024

Grid Planning Impacts of Hydropower Growth and Decline

Hydropower and pumped storage hydropower (PSH) have a complex and uncertain future in the U.S. electricity system. On one hand, existing assets have the potential for an expanded role in integrating variable renewable energy while new deployment, particularly of PSH, can help meet growing needs for grid flexibility and improved reliability. On the other hand, challenging environmental and cost considerations could limit the extent of new investments in hydropower and PSH capacity and flexibility. This technical presentation demonstrates the use of a high-fidelity capacity expansion model of the U.S. electric grid (the National Renewable Energy Laboratory's Regional Energy Deployment System) to understand the impacts of alternative futures for the hydropower and PSH fleet, including scenarios of both growth and decline. Growth scenarios include new PSH deployment or improved hydropower flexibility, while scenarios of decline reduce the capacity or energy production potential of hydropower and PSH. Economic, environmental, and performance outcomes of the grid are compared across these scenarios to reveal the potential contributions of hydropower and PSH in the U.S. electric sector over the next several decades, focusing on changes to the grid technology mix, electric sector costs, electricity prices, and air emissions. This broad scenario approach demonstrates how flexible hydropower and PSH can help reduce air emissions and cost by complementing variable renewables, but the opposite can occur with reduced hydropower availability, particularly in the next decade. It is important to consider a wide range of scenarios and metrics to gain a national and regional understanding of hydropower's future in the United States.

capacity expansion↗
DOE OSTI2024

Rapid Detection of Anomalies in Battery Energy Storage System Data

Data analytics is pivotal in assessing the technical characteristics and performance of Battery Energy Storage Systems (BESS), underpinning BESS modeling, optimization, and control. However, raw datasets frequently harbor anomalies from measurement errors and equipment malfunctions, impacting BESS reliability and analysis accuracy To address the challenge, this paper presents a novel methodology for the rapid detection of anomalous charge or discharge cycles within BESS operational data, expediting the cleaning process while ensuring data integrity. We’ve collected diverse and comprehensive real-world BESS operational datasets in collaboration with the Electric Power Research Institute and multiple Washington State utilities. These datasets serve dual roles: enabling comprehensive data exploration and analysis for understanding underlying challenges and method development, while also acting as a vital validation resource, demonstrating practical effectiveness. The proposed method detects anomalies and aids in their resolution, improving system performance characterization precision. It also reveals recurring data anomaly sources, offering insights for data collection and handling enhancement. Practitioners can gain valuable insights from the identified anomalous cycles in the real-world datasets along with the investigative process for root cause analyses and essential data cleaning steps.

Crawford, Aladsair J.↗
DOE OSTI2020

Radiological Recovery Logistics Tool - 20161

Argonne is building and testing a tool, the Radiological Recovery Logistics Tool (RRLT), that can be used during the response and recovery from a radiological or nuclear incident to effectively allocate appropriate commercial and public works equipment to mitigate, remove, and contain radiological contamination. The requirements for this tool - as well as development of the resulting software - is overseen by a steering committee of stakeholders from DHS's National Urban Security Technology Laboratory (NUSTL), the Federal Emergency Management Agency (FEMA), and the Environmental Protection Agency (EPA). One essential requirement is for RRLT to support the efficient and appropriate allocation of resources for a radiological response. Subsequent discussions between ANL and stakeholders have solidified the nature of this support to include identification of the types of resources to be allocated. The study reported in this paper has both factored fundamental concepts and connections out of this identification process and created a Knowledge Base detailing support goals, response scenarios, and efficacy information on dozens of equipment types. In short, RRLT will dynamically apply these findings to situational conditions surrounding contamination incidents. RRLT's Domain, the model of elements, ideas and relationships with which the tool will work, draws concepts from technical reports and stakeholder vocabularies to connect response goals and scenarios to types of equipment that offer utility towards those goals in those scenarios. RRLT's Knowledge Base will contain details on dozens of equipment types and facilitate the operator's discovery and consumption of these details most pertinent to a dynamically selected subset of goals. The core of its Domain Model is based on a report authored by this team. This report [1] contains a comprehensive list of proposed equipment to accomplish various missions or scenarios that might arise after a large-scale radiological contamination incident in an urban environment or critical infrastructure. The report divides potential response and recovery efforts into five support goals: Survey and monitoring of the contaminated area; Mitigation of received dose to first responders: Decontamination (gross and final) of buildings, vehicles, roadways, parks, and other surfaces: Waste management of solid waste generated during recovery operations: and Containment of wastewater and other waste generated during the response and recovery phases. RRLT's development is driven by use cases. A use case is an intention with which a user approaches the software. Use cases are grouped into delivery increments to schedule development, testing, and presentation to stakeholders. This model partitions the system into seven increments: User Arrival and Authentication, Search and Navigation, Equipment Recommendation, Plan Management, Content Management, and Expanded Access. Once a user 15 authenticated, RRLT will present the user with a dashboard that allows them to explore or search RRLT's content. The dashboard will also include a 'Plan' panel for collecting decisions and relevant observations about an incident at hand to facilitate development of an equipment list. RRLT will offer three general modes of access to items in the knowledge base: - Keyword search for direct discovery of items, - Navigation along predetermined paths from recovery goal towards equipment types, and - Interactive guidance towards equipment types by an autonomous software agent: the Equipment Recommendation Wizard. This presentation will detail progress in the development of the RRLT and also discuss opportunities for those interested in providing feedback on its content and functionality. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Hydrogen Storage System Modeling: Public Access, Maintenance, and Enhancements

The hydrogen storage system modeling project aims to develop new and enhance existing material-based hydrogen storage system models and make them accessible to the research community through a public web page. Updating existing storage systems models supports material developers in evaluating the performance of their new materials in mobile and stationary applications relative to the available DOE Technical Targets. Developing new tools helps researchers evaluate the performance of hydrogen storage materials developed under HyMARC activities or other fundamental hydrogen storage materials discovery research. New models will also work for validating alternatives to material-based systems (liquefied & gaseous hydrogen), comparing various mobile and stationary use cases, and expand to include medium-, heavy-duty, and mining vehicles and stationary application(s).

AMR↗
NASA NTRS1986

Progress in the Lewis Research Center Altitude Wind Tunnel (AWT) modeling program

The rehabilitation of the AWT at the NASA Lewis Research Center is under study with the goal of providing a modern subsonic wind tunnel for conducting propulsion system/airframe integration, isolated propulsion system, propulsion acoustics and adverse weather tests. Because of the increased Mach number capability (from Mach 0.6 to 0.9 plus) and the incorporation of acoustic and adverse weather capabilities into an existing tunnel, the AWT rehabilitation represents a significant technical challenge. In order to reduce the risk associated with such an undertaking, an extensive AWT modeling program is being conducted to guide and verify the tunnel design. Significant findings and progress in this modeling program are the subject of this paper.

Ciepluch, C. C.↗
NASA NTRS2002

OAI and NASA's Scientific and Technical Information

The Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) is an evolving protocol and philosophy regarding interoperability for digital libraries (DLs). Previously, "distributed searching" models were popular for DL interoperability. However, experience has shown distributed searching systems across large numbers of DLs to be difficult to maintain in an Internet environment. The OAI-PMH is a move away from distributed searching, focusing on the arguably simpler model of "metadata harvesting". We detail NASA s involvement in defining and testing the OAI-PMH and experience to date with adapting existing NASA distributed searching DLs (such as the NASA Technical Report Server) to use the OAI-PMH and metadata harvesting. We discuss some of the entirely new DL projects that the OAI-PMH has made possible, such as the Technical Report Interchange project. We explain the strategic importance of the OAI-PMH to the mission of NASA s Scientific and Technical Information Program.

Nelson, Michael L.↗
NASA NTRS2015

Exploring NASA Human Spaceflight and Pioneering Scenarios

The life cycle cost analysis of space exploration scenarios is explored via a merger of (1) scenario planning, separating context and (2) modeling and analysis of specific content. Numerous scenarios are presented, leading to cross-cutting recommendations addressing life cycle costs, productivity, and approaches applicable to any scenarios. Approaches address technical and non-technical factors.

space systems life cycle costs↗
NASA NTRS2000

Development of X-33/X-34 Aerothermodynamic Data Bases: Lessons Learned and Future Enhancements

A synoptic of programmatic and technical lessons learned in the development of aerothermodynamic data bases for the X-33 and X-34 programs is presented in general terms and from the perspective of the NASA Langley Research Center Aerothermodynamics Branch. The format used is that of the "aerothermodynamic chain," the links of which are personnel, facilities, models/test articles, instrumentation, test techniques, and computational fluid dynamics (CFD). Because the aerodynamic data bases upon which the X-33 and X-34 vehicles will fly are almost exclusively from wind tunnel testing, as opposed to CFD, the primary focus of the lessons learned is on ground-based testing. The period corresponding to the development of X-33 and X-34 aerothermodynamic data bases was challenging, since a number of other such programs (e.g., X-38, X-43) competed for resources at a time of downsizing of personnel, facilities, etc., outsourcing, and role changes as NASA Centers served as subcontractors to industry. The impact of this changing environment is embedded in the lessons learned. From a technical perspective, the relatively long times to design and fabricate metallic force and moment models, delays in delivery of models, and a lack of quality assurance to determine the fidelity of model outer mold lines (OML) prior to wind tunnel testing had a major negative impact on the programs. On the positive side, the application of phosphor thermography to obtain global, quantitative heating distributions on rapidly fabricated ceramic models revolutionized the aerothermodynamic optimization of vehicle OMLs, control surfaces, etc. Vehicle designers were provided with aeroheating information prior to, or in conjunction with, aerodynamic information early in the program, thereby allowing trades to be made with both sets of input; in the past only aerodynamic data were available as input. Programmatically, failure to include transonic aerodynamic wind tunnel tests early in the assessment phase led to delays in the optimization phase, as OMLs required modification to provide adequate transonic aerodynamic performance without sacrificing subsonic and hypersonic performance. Funding schedules for industry, based on technical milestones, also presented challenges to aerothermodynamics seeking optimum flying characteristics across the subsonic to hypersonic speed regimes and minimum aeroheating. This paper is concluded with a brief discussion of enhancements in ground-based testing/CFD capabilities necessary to partially/fully satisfy future requirements.

Miller, C. G.↗
DOE OSTI2021

A Short-Term Solar Forecasting Platform Using a Physics-Based Smart Persistence Model and Data Imputation Method

Electrical energy plays vital role in our socio-economic activity and therefore ensuring the reliability of the electric grid, from the generation, transmission and distribution level is critical. In order to maintain the power system parameter viz., frequency, voltage, etc., optimally, balancing of generation and consumption is very much essential. However, solar energy is infirm power by nature this is due to cloud cover / other local phenomena. Hence, Photovoltaic (PV) power generation brings a significant challenge to the grid operator due to the variability of the solar energy. The complexity of this challenge in terms of planning and dispatch ability of PV resources, aggravates with the high penetration of solar energy into the electric grid. In this setting, reliable solar radiation forecasting models based on accurate and quality input data become essential. In order to develop a suitable model for predicting solar radiation, quality historical / real time measurement is also needed. Under this study NIWE and NREL jointly developed / tested short-term solar forecasting frameworks using a smart persistence and physics-based smart persistence models for intra-hour forecasting of solar radiation (PSPI) and benchmarked 9 different data imputation techniques in 15 Solar Radiation Resource Assessment (SRRA) stations, located at different parts of India. During any measurement campaign, due to various technical reasons, we may miss few observations. However, the missing observation often reduce the performance of any forecasting model. Therefore, suitable data imputation method would assist us to obtain continuous observation of solar radiation. A station-by-station and method-by-method analysis was carried out to understand the performance of each model. Based on our analysis, among all the data imputation methods, the Kalman data imputation method is better for Indian Weather condition. In addition, Kalman StructTS, Linear, Stine and Arima methods yield slightly inferior accuracy compared to Kalman, but outperform the other methods. The extended solar radiation data are used by solar forecasting models to provide the prediction of solar radiation at 15 SRRA stations. As far as short term forecasting model is concerned, the PSPI model outperforms the Smart Persistence model. However, the forecast error is increases with the forecasting horizon.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1986

Progress in the Lewis Research Center Altitude Wind Tunnel (AWT) Modeling Program

The rehabilitation of the Altitude Wind Tunnel (AWT) at the NASA Lewis Research Center is under study with the goal of providing a modern subsonic wind tunnel for conducting propulsion system/airframe integration, isolated propulsion system, propulsion acoustics and adverse weather tests. Because of the increased Mach number capability (from Mach 0.6 to 0.9 plus) and the incorporation of acoustic and adverse weather capabilities into an existing tunnel, the AWT rehabilitation represents a significant technical challenge. In order to reduce the risk associated with such an undertaking, and extensive AWT modeling program is being conducted to guide and verify the tunnel design. Significant findings and progress in this modeling program are the subject of this paper.

Ciepluch, C. C.↗
NASA NTRS2006

Deep Space Test Bed for Radiation Studies

A key factor affecting the technical feasibility and cost of missions to Mars or the Moon is the need to protect the crew from ionizing radiation in space. Some analyses indicate that large amounts of spacecraft shielding may be necessary for crew safety. The shielding requirements are driven by the need to protect the crew from Galactic cosmic rays (GCR). Recent research activities aimed at enabling manned exploration have included shielding materials studies. A major goal of this research is to develop accurate radiation transport codes to calculate the shielding effectiveness of materials and to develop effective shielding strategies for spacecraft design. Validation of these models and calculations must be addressed in a relevant radiation environment to assure their technical readiness and accuracy. Test data obtained in the deep space radiation environment can provide definitive benchmarks and yield uncertainty estimates of the radiation transport codes. The two approaches presently used for code validation are ground based testing at particle accelerators and flight tests in high-inclination low-earth orbits provided by the shuttle, free-flyer platforms, or polar-orbiting satellites. These approaches have limitations in addressing all the radiation-shielding issues of deep space missions in both technical and practical areas. An approach based on long duration high altitude polar balloon flights provides exposure to the galactic cosmic ray composition and spectra encountered in deep space at a lower cost and with easier and more frequent access than afforded with spaceflight opportunities. This approach also results in shorter development times than spaceflight experiments, which is important for addressing changing program goals and requirements.

Adams, James H.↗