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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

ASRC Aerospace Corporation Selects Dynamically Reconfigurable Anadigm(Registered Trademark) FPAA For Advanced Data Acquisition System

Anadigm(registered trademark) today announced that ASRC Aerospace Corporation has designed Anadigm's dynamically reconfigurable Field Programmable Analog Array (FPAA) technology into an advanced data acquisition system developed under contract for NASA. ASRC Aerospace designed in the Anadigm(registered trademark) FPAA to provide complex analog signal conditioning in its intelligent, self-calibrating, and self-healing advanced data acquisition system (ADAS). The ADAS has potential applications in industrial, manufacturing, and aerospace markets. This system offers highly reliable operation while reducing the need for user interaction. Anadigm(registered trademark)'s dynamically reconfigurable FPAAs can be reconfigured in-system by the designer or on the fly by a microprocessor. A single device can thus be programmed to implement multiple analog functions and/or to adapt on-the-fly to maintain precision operation despite system degradation and aging. In the case of the ASRC advanced data acquisition system, the FPAA helps ensure that the system will continue to operating at 100% functionality despite changes in the environment, component degradation, and/or component failures.

Mata, Carlos T.↗
NASA NTRS1994

Advanced data assimilation in strongly nonlinear dynamical systems

Advanced data assimilation methods are applied to simple but highly nonlinear problems. The dynamical systems studied here are the stochastically forced double well and the Lorenz model. In both systems, linear approximation of the dynamics about the critical points near which regime transitions occur is not always sufficient to track their occurrence or nonoccurrence. Straightforward application of the extended Kalman filter yields mixed results. The ability of the extended Kalman filter to track transitions of the double-well system from one stable critical point to the other depends on the frequency and accuracy of the observations relative to the mean-square amplitude of the stochastic forcing. The ability of the filter to track the chaotic trajectories of the Lorenz model is limited to short times, as is the ability of strong-constraint variational methods. Examples are given to illustrate the difficulties involved, and qualitative explanations for these difficulties are provided. Three generalizations of the extended Kalman filter are described. The first is based on inspection of the innovation sequence, that is, the successive differences between observations and forecasts; it works very well for the double-well problem. The second, an extension to fourth-order moments, yields excellent results for the Lorenz model but will be unwieldy when applied to models with high-dimensional state spaces. A third, more practical method--based on an empirical statistical model derived from a Monte Carlo simulation--is formulated, and shown to work very well. Weak-constraint methods can be made to perform satisfactorily in the context of these simple models, but such methods do not seem to generalize easily to practical models of the atmosphere and ocean. In particular, it is shown that the equations derived in the weak variational formulation are difficult to solve conveniently for large systems.

Miller, Robert N.↗
DOE OSTI2025

Advanced Data Management for the Wastewater Industry

This information sheet discusses the technology pillar Advanced Data Management as a pathway toward improving wastewater infrastructure sustainability and resiliency. To supplement existing literature on current technologies and policies for improving resiliency at wastewater treatment plants (WWTPs), this document aims to accomplish the following: • Summarize key technologies such as Supervisory Control and Data Acquisition (SCADA), digital twins, and smart sensors • Summarize relevant cybersecurity measures and data management tools available for WW utilities • Summarize advances in sensing and monitoring technologies • Serve as a comprehensive (though not exhaustive) repository for data management for wastewater utilities The Advanced Management Technical Information Sheet should be viewed as a general guide to established best practices for the water and wastewater sector when considering implementing energy capture and energy- or process-efficient technologies. Further details are presented in the SWIFt Technology Information Sheet Series for accompanying Technology Pillars.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1986

A definition study of an Advanced Data Collection and Location System (ADCLS)

The technical and economic advantages of developing an Advanced Data Collection and Location System (ADCLS) to operate within the Earth Observation System (EOS) planned for Polar Platform, as a replacement and/or augmentation of the existing ARGOS data collection system were assessed. The cost/effectiveness of ADCLS with respect to ARGOS hinges on the traffic and quality of service demand of the future user constituency.

Source record↗
NASA NTRS1978

The design and demonstration of an advanced data collection/position locating system, addendum

The theoretical background for a coherent demodulator for minimum shift keying signals generated by the advanced data collection/position locating system breadboard is presented along with a discussion of the design concept. Various tests and test results, obtained with the breadboard system described, include evaluation of bit-error rate performance, acquisition time, clock recovery, recycle time, frequency measurement accuracy, and mutual interference.

Source record↗
NASA NTRS1998

Advanced Data Format (ADF) Software Library and Users Guide

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial. Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: 1) The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its 1/0 software, which handles the actual reading and writing of data from and to external storage media; 2) The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; 3) The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and 4) The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The ADF is a generic database manager with minimal intrinsic capability. It was written for the purpose of storing large numerical datasets in an efficient, platform independent manner. To be effective, it must be used in conjunction with external agreements on how the data will be organized within the ADF database such defined by the SIDS. There are currently 34 user callable functions that comprise the ADF Core library and are described in the Users Guide. The library is written in C, but each function has a FORTRAN counterpart.

Smith, Matthew↗
NASA NTRS1977

Design and demonstration of an advanced data collection/position location system

The final report on a breadboard evaluation and demonstration program is reported concerning the applicability of MSK modulation and chirp-z transformer technology in Advanced Data Collection/Position Location (ADC/PL) systems. The program effort consisted of three phases - design, testing, and evaluation. Section 2 describes the breadboard hardware built during the design phase of the program, Section 3 describes the tests conducted on the breadboard and the results of the tests, and Section 4 presents a brief analysis and summary of the findings of the breadboard tests and develops a sample ADC/PL system which incorporates both MSK modulation and a chirp-z transformer.

Source record↗
NASA NTRS2022

Perspective on Satellite-Based Land Data Assimilation to Estimate Water Cycle Components in an Era of Advanced Data Availability and Model Sophistication

The beginning of the 21st century is marked by a rapid growth of land surface satellite data and model sophistication. This offers new opportunities to estimate multiple components of the water cycle via satellite-based land data assimilation (DA) across multiple scales. By resolving more processes in land surface models and by coupling the land, the atmosphere, and other Earth system compartments, the observed information can be propagated to constrain additional unobserved variables. Furthermore, access to more satellite observations enables the direct constraint of more and more components of the water cycle that are of interest to end users. However, the finer level of detail in models and data is also often accompanied by an increase in dimensions, with more state variables, parameters, or boundary conditions to estimate, and more observations to assimilate. This requires advanced DA methods and efficient solutions. One solution is to target specific observations for assimilation based on a sensitivity study or coupling strength analysis, because not all observations are equally effective in improving subsequent forecasts of hydrological variables, weather, agricultural production, or hazards through DA. This paper offers a perspective on current and future land DA development, and suggestions to optimally exploit advances in observing and modeling systems.

Data Assimilation↗
NASA NTRS1990

Advanced data management system architectures testbed

The objective of the Architecture and Tools Testbed is to provide a working, experimental focus to the evolving automation applications for the Space Station Freedom data management system. Emphasis is on defining and refining real-world applications including the following: the validation of user needs; understanding system requirements and capabilities; and extending capabilities. The approach is to provide an open, distributed system of high performance workstations representing both the standard data processors and networks and advanced RISC-based processors and multiprocessor systems. The system provides a base from which to develop and evaluate new performance and risk management concepts and for sharing the results. Participants are given a common view of requirements and capability via: remote login to the testbed; standard, natural user interfaces to simulations and emulations; special attention to user manuals for all software tools; and E-mail communication. The testbed elements which instantiate the approach are briefly described including the workstations, the software simulation and monitoring tools, and performance and fault tolerance experiments.

Grant, Terry↗
NASA NTRS2012

Advancing Data Assimilation in Operational Hydrologic Forecasting: Progresses, Challenges, and Emerging Opportunities

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

forecasting↗
NASA NTRS1970

Program documentation with advanced data management systems

The problems of program documentation are considered for those cases in which the programmer is using a computer along with an advanced DMS. Three problem areas discussed include: data description, process description, and execution-time documentation.

Swift, W. B.↗
DOE OSTI2024

Advanced Data Science Model for Detecting Intelligent Malware

This study focused on developing a robust artificial intelligence (AI) model capable of detecting and characterizing advanced malware in Internet of Things (IoT) devices using network data. By analyzing network traffic with various machine learning (ML) models, our AI model can identify and characterize malicious activities to significantly improve malware detection accuracy and reliability as compared to traditional methods. The developed AI/ML model was trained using network data from IoT devices, leveraging classifiers such as Random Forest, Gradient Boosting, AdaBoost, and others to optimize detection performance. This project demonstrates a scalable framework for real-time malware detection and characterization in IoT networks, capable of identifying infected devices and facilitating the necessary steps to remove or isolate them, thereby preventing further infections. Although digital twin (DT) integration is not yet implemented in the current model, it represents a promising future enhancement. By creating a virtual replica of physical IoT devices, DT technology would allow for real-time monitoring and analysis without directly accessing operational technology, thus reducing the risk of compromising or reducing the performance of actual devices. This integration would further enhance the security of IoT ecosystems, combining AI technology to better flag and detect indications of malware-infected devices within a nuclear system environment.

42 ENGINEERING↗
NASA NTRS1987

Advanced data management design for autonomous telerobotic systems in space using spaceborne symbolic processors

The use of computers in autonomous telerobots is reaching the point where advanced distributed processing concepts and techniques are needed to support the functioning of Space Station era telerobotic systems. Three major issues that have impact on the design of data management functions in a telerobot are covered. It also presents a design concept that incorporates an intelligent systems manager (ISM) running on a spaceborne symbolic processor (SSP), to address these issues. The first issue is the support of a system-wide control architecture or control philosophy. Salient features of two candidates are presented that impose constraints on data management design. The second issue is the role of data management in terms of system integration. This referes to providing shared or coordinated data processing and storage resources to a variety of telerobotic components such as vision, mechanical sensing, real-time coordinated multiple limb and end effector control, and planning and reasoning. The third issue is hardware that supports symbolic processing in conjunction with standard data I/O and numeric processing. A SSP that currently is seen to be technologically feasible and is being developed is described and used as a baseline in the design concept.

Goforth, Andre↗
NASA NTRS1993

Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

Savage, Richard C.↗
NASA NTRS1991

Advanced data acquisition and display techniques for laser velocimetry

The Basic Aerodynamics Research Tunnel (BART) has been equipped with state-of-the-art instrumentation for acquiring the data needed for code validation. This paper describes the three-component LDV and the workstation-based data-acquisition system (DAS) which has been developed for the BART. The DAS allows the use of automation and the quick integration of advanced instrumentation, while minimizing the software development time required between investigations. The paper also includes a description of a graphics software library developed to support the windowing environment of the DAS. The real-time displays generated using the graphics library help the researcher ensure the test is proceeding properly. The graphics library also supports the requirements of posttest data analysis. The use of the DAS and graphics libraries is illustrated by presenting examples of the real-time and postprocessing display graphics for LDV investigations.

Kjelgaard, Scott O.↗
NASA NTRS1994

Extending HPF for advanced data parallel applications

The stated goal of High Performance Fortran (HPF) was to 'address the problems of writing data parallel programs where the distribution of data affects performance'. After examining the current version of the language we are led to the conclusion that HPF has not fully achieved this goal. While the basic distribution functions offered by the language - regular block, cyclic, and block cyclic distributions - can support regular numerical algorithms, advanced applications such as particle-in-cell codes or unstructured mesh solvers cannot be expressed adequately. We believe that this is a major weakness of HPF, significantly reducing its chances of becoming accepted in the numeric community. The paper discusses the data distribution and alignment issues in detail, points out some flaws in the basic language, and outlines possible future paths of development. Furthermore, we briefly deal with the issue of task parallelism and its integration with the data parallel paradigm of HPF.

Chapman, Barbara↗