CAWAP Experimental Data - NASA/TP-2001-210629/ Supplement
Flight surface flow data of various types for the F-16XL-1 aircraft, employed in the Cranked Arrow Wing Aerodynamics Project (CAWAP), are available.
Lamar, John E.↗
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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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Strategies for concurrent processing of complex algorithms in data driven architectures
The performance modeling and enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures is examined. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called ATAMM (Algorithm To Architecture Mapping Model). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.
Stoughton, John W.↗
Strategies for concurrent processing of complex algorithms in data driven architectures
Performance modeling and performance enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures are discussed. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called algorithm to architecture mapping model (ATAMM). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.
Som, Sukhamoy↗
Algorithm Optimally Orders Forward-Chaining Inference Rules
People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally developed and have it automatically ordered for efficiency. Although data flow analysis was first developed for use in compilers for producing optimal code sequences, its usefulness is now recognized in many software systems including knowledge-based systems. However, this approach for exhaustively computing data-flow information cannot directly be applied to inference systems because of the ubiquitous execution of the rules. An algorithm is presented that efficiently performs a complete producer/consumer analysis for each antecedent and consequence clause in a knowledge base to optimally order the rules to minimize inference cycles. An algorithm was developed that optimally orders a knowledge base composed of forwarding chaining inference rules such that independent inference cycle executions are minimized, thus, resulting in significantly faster execution. This algorithm was integrated into the JPL tool Spacecraft Health Inference Engine (SHINE) for verification and it resulted in a significant reduction in inference cycles for what was previously considered an ordered knowledge base. For a knowledge base that is completely unordered, then the improvement is much greater.
James, Mark↗
The influence of wing, fuselage and tail design on rotational flow aerodynamics data obtained beyond maximum lift with general aviation configurations
The NASA Langley Research Center has initiated a broad general aviation stall/spin research program. A rotary balance system was developed to support this effort. Located in the Langley spin tunnel, this system makes it possible to identify an airplane's aerodynamic characteristics in a rotational flow environment, and thereby permits prediction of spins. This paper presents a brief description of the experimental set-up, testing technique, five model programs conducted to date, and an overview of the rotary balance results and their correlation with spin tunnel free-spinning model results. It is shown, for example, that there is a large, nonlinear dependency of the aerodynamic moments on rotational rate and that these moments are pronouncedly configuration-dependent. Fuselage shape, horizontal tail and, in some instances, wing location are shown to appreciably influence the yawing moment characteristics above an angle of attack of 45 deg.
Bihrle, W., Jr.↗
Constraints on rift thermal processes from heat flow and uplift
The implications of heat flow data available from five major Cenozoic continental rift systems for the processes of continental rifting are discussed, and simple thermal models of lithospheric thinning which predict uplift are used to further constrain the thermal processes in the lithosphere during rifting. Compilations of the heat flow data are summarized and the salient results of these compilations are briefly discussed. The uplift predictions of the slow and rapid thinning models, in which thinning is assumed to occur at a respectively slower and faster rate than heat can be conducted into the lithosphere, are presented. Comparison of uplift rates with model results indicates that the lithosphere is in a state between the two models. While uplift is predicted to continue after thinning has ceased due to thermal relaxation of the lithosphere, the rapid thinning model is always predicted to apply to surface heat flow, and an anomaly in this flow is not predicted to develop until after thinning has stopped.
Morgan, P.↗
Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions
Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.
J Lemery↗
Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions
Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.
Medical Operations↗
Analytical developments for definition and prediction of USB noise
A systematic acoustic data base and associated flow data are used in identifying the noise generating mechanisms of upper surface blown flap configurations of short takeoff and landing aircraft. Theory is developed for the radiated sound field of the highly sheared flow of the trailing edge wake. An empirical method is also developed using extensive experimental data and physical reasonings to predict the noise levels.
Reddy, N. N.↗
Resource utilization model for the algorithm to architecture mapping model
The analytical model for resource utilization and the variable node time and conditional node model for the enhanced ATAMM model for a real-time data flow architecture are presented in this research. The Algorithm To Architecture Mapping Model, ATAMM, is a Petri net based graph theoretic model developed at Old Dominion University, and is capable of modeling the execution of large-grained algorithms on a real-time data flow architecture. Using the resource utilization model, the resource envelope may be obtained directly from a given graph and, consequently, the maximum number of required resources may be evaluated. The node timing diagram for one iteration period may be obtained using the analytical resource envelope. The variable node time model, which describes the change in resource requirement for the execution of an algorithm under node time variation, is useful to expand the applicability of the ATAMM model to heterogeneous architectures. The model also describes a method of detecting the presence of resource limited mode and its subsequent prevention. Graphs with conditional nodes are shown to be reduced to equivalent graphs with time varying nodes and, subsequently, may be analyzed using the variable node time model to determine resource requirements. Case studies are performed on three graphs for the illustration of applicability of the analytical theories.
Stoughton, John W.↗
Aeroacoustic Analysis of a Simplified Landing Gear
A hybrid approach is used to investigate the noise generated by a simplified landing gear without small scale parts such as hydraulic lines and fasteners. The Ffowcs Williams and Hawkings equation is used to predict the noise at far-field observer locations from flow data provided by an unsteady computational fluid dynamics calculation. A simulation with 13 million grid points has been completed, and comparisons are made between calculations with different turbulence models. Results indicate that the turbulence model has a profound effect on the levels and character of the unsteadiness. Flow data on solid surfaces and a set of permeable surfaces surrounding the gear have been collected. Noise predictions using the porous surfaces appear to be contaminated by errors caused by large wake fluctuations passing through the surfaces. However, comparisons between predictions using the solid surfaces with the near-field CFD solution are in good agreement giving confidence in the far-field results.
Lockard, David P.↗
Jet-Surface Interaction Noise from High-Aspect Ratio Nozzles: Test Summary
Noise and flow data have been acquired for a 16:1 aspect ratio rectangular nozzle exhausting near a simple surface at the NASA Glenn Research Center as part of an ongoing effort to understand, model, and predict the noise produced by current and future concept aircraft employing a tightly integrated engine airframe designs. The particular concept under consideration in this experiment is a blended-wing-body airframe powered by a series of electric fans exhausting through slot nozzle over an aft deck. The exhaust Mach number and surface length were parametrically varied during the test. Far-field noise data were acquired for all nozzle surface geometries and exhaust flow conditions. Phased-array noise source localization data and in-flow pressure data were also acquired for a subset of the isolated (no surface) and surface configurations; these measurements provide data that have proven useful for modeling the jet-surface interaction noise source and the surface effect on the jet-mixing noise in round jets. A summary of the nozzle surface geometry, flow conditions tested, and data collected are presented.
Propulsion Noise↗
Study of lee-side flows over conically cambered delta wings at supersonic speeds, part 1
An experimental investigation was performed in which surface pressure data, flow visualization data, and force and moment data were obtained on four conical delta wing models which differed in leading-edge camber only. Wing leading-edge camber was achieved through a deflection of the outboard 30% of the local wind semispan of a reference 75 degrees swept flat delta wing. The four wing models have leading-edge deflection angles delta sub F of 0, 5, 10, and 15 degrees measured streamwise. Data for the wings with delta sub F = 10 and 15 degrees showed that hinge-line separation dominated the lee-side wing loading and prohibited the develpment of leading-edge separation on the deflected portion of wing leading edge. However, data for the wing with delta sub F = 5 degrees, a vortex was positioned on the deflected leading edge with reattachment at the hinge line. Flow visualization results were presented which detail the influence of Mach number, angle of attack, and camber on the lee-side flow characteristics of conically cambered delta wings. Analysis of photgraphic data identified the existence of 12 distinctive lee-side flow types. In general, the aerodynamic force and moment data correlated well with the pressure and flow visualization data.
Wood, Richard M.↗
Architecture and design of a 500-MHz gallium-arsenide processing element for a parallel supercomputer
The design of the processing element of GASP, a GaAs supercomputer with a 500-MHz instruction issue rate and 1-GHz subsystem clocks, is presented. The novel, functionally modular, block data flow architecture of GASP is described. The architecture and design of a GASP processing element is then presented. The processing element (PE) is implemented in a hybrid semiconductor module with 152 custom GaAs ICs of eight different types. The effects of the implementation technology on both the system-level architecture and the PE design are discussed. SPICE simulations indicate that parts of the PE are capable of being clocked at 1 GHz, while the rest of the PE uses a 500-MHz clock. The architecture utilizes data flow techniques at a program block level, which allows efficient execution of parallel programs while maintaining reasonably good performance on sequential programs. A simulation study of the architecture indicates that an instruction execution rate of over 30,000 MIPS can be attained with 65 PEs.
Fouts, Douglas J.↗
A practical approach to object based requirements analysis
Presented here is an approach developed at the Unisys Houston Operation Division, which supports the early identification of objects. This domain oriented analysis and development concept is based on entity relationship modeling and object data flow diagrams. These modeling techniques, based on the GOOD methodology developed at the Goddard Space Flight Center, support the translation of requirements into objects which represent the real-world problem domain. The goal is to establish a solid foundation of understanding before design begins, thereby giving greater assurance that the system will do what is desired by the customer. The transition from requirements to object oriented design is also promoted by having requirements described in terms of objects. Presented is a five step process by which objects are identified from the requirements to create a problem definition model. This process involves establishing a base line requirements list from which an object data flow diagram can be created. Entity-relationship modeling is used to facilitate the identification of objects from the requirements. An example is given of how semantic modeling may be used to improve the entity-relationship model and a brief discussion on how this approach might be used in a large scale development effort.
Drew, Daniel W.↗
Interpretation of Boundary-layer Pressure-rake Data in Flow with a Detached Shock
No abstract available
Luidens, R. W.↗
Parallel-Access Alinement Network Using Barrel Switches
Practical version of parallel-access alinement network utilizes two barrel switches for interfacing N parallel memory modules with N parallel processing elements. Switches are interconnected where 17 memory ports (MP's) are connected to 17 processor ports (PP's). Network uses two electronic barrel switches to direct data flow in parallel data-processing system. Each switch can shift a multibit parallel input a predetermined number of places to left or right, end off, or end around in one clock-pulse.
Barnes, George H.↗
IDEF4 technical report, version 1.0
A language for the representation of object oriented software designs is described. IDEF4, a methodology for object-oriented design, is being developed as a design tool for software designers who use such object-oriented languages. Such languages include the Common LISP Object System, Flavors, C++, Smalltalk, Objective C, and others. Since effective usage of the object-oriented paradigm requires a different thought process than that used with conventional procedural or database languages, standard methodologies such as structure charts, data flow diagrams, and traditional data design models (hierarchical, relational, and network) are not sufficient. IDEF4 seeks to provide the necessary facilities to support the object-oriented design decision making process. Specifically, the two primary design goals of IDEF4 are: (1) to provide support for creating object oriented designs whose implementations will exhibit desirable life cycle qualities and reduce total implementation development time; and (2) to make it easy to evaluate object oriented code to determine whether or not the delivered product both conforms to the design and exhibits the desired life cycle qualities. The application of IDEF4 in the life cycle of a software development project is intended to be focused on those activities after a decision has been made to employ object oriented programming technology, but prior to detailed code specification.
Mayer, Richard J.↗