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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

On Animating 2D Velocity Fields

A velocity field. even one that represents a steady state flow implies a dynamical system. Animated velocity fields is an important tool in understanding such complex phenomena. This paper looks at a number of techniques that animate velocity fields and propose two new alternatives, These are texture advection and streamline cycling. The common theme among these techniques is the use of advection on some texture to generate a realistic animation of the velocity field. Texture synthesis and selection for these methods are presented. Strengths and weaknesses of the techniques are also discussed in conjunction with several examples.

Kao, David↗
NASA NTRS2001

On Animating 2D Velocity Fields

A velocity field, even one that represents a steady state flow, implies a dynamical system. Animated velocity fields is an important tool in understanding such complex phenomena. This paper looks at a number of techniques that animate velocity fields and propose two new alternatives. These are texture advection and streamline cycling. The common theme among these techniques is the use of advection on some texture to generate a realistic animation of the velocity field. Texture synthesis and selection for these methods are presented. Strengths and weaknesses of the techniques are also discussed in conjunctions with several examples.

Kao, David↗
NASA NTRS1998

Methodology for Examining the Operator and the System Concurrently: Pilot Interaction with Automation

Complex system description is problematic when considering operator task activities interacting with system dynamics. Engineering languages have matured sufficiently to allow machine system description at various levels of depth and breadth but without operator synergy. Concurrently, Task Analysis methods have evolved along diverse lines enabling a description of the operator in the system from various paradigms but not describing the system. A void exists when attempting to view the system and the operator in the same plane. We propose a methodology employing descriptive languages from different domains viewed in a single dimension. Finite Automata (FA) languages describe the machine system in the proposed approach. Operator task specifications, a form of task analysis output, examine the operator activities within the system. Operator task specifications were then selected for discrete task activities and overlaid on the system description to examine operator inputs and subsequently view system responses. Unexpected (surprise) and undesirable system behavior was expected to emerge from this analysis. In this paper we shall first describe the methodology and show how the two perspectives, machine model and operator task specifications are integrated. Following we describe the process of doing such analysis using an example from cockpit automation. The methodology was employed in the analysis of a new function that was added to an existing automatic flight control system. We begin by defining a flight scenario involving all aspects of pilot interaction with the new function. Then, we proceed to develop a basic model of the machine behavior, in the context of pilot actions. Finally we superimpose the operator task specification on the machine model and perform the analysis. The proposed methodology may have broad appeal to system designers and human factors specialists. A common language for engineers of diverse domains is a strong point of this approach. Systems engineers may not fully understand operational considerations and human limitations, and human factors specialists may not be exposed to the full extent of system behavior. We hope the proposed methodology is adopted by both disciplines and in the process each assimilates a common language to address potential shortcomings of either approach separately.

Austin, David↗
NASA NTRS2005

A Fundamental Mathematical Model of a Microbial Predenitrification System

Space flight beyond Low Earth Orbit requires sophisticated systems to support all aspects of the mission (life support, real-time communications, etc.). A common concern that cuts across all these systems is the selection of information technology (IT) methodology, software and hardware architectures to provide robust monitoring, diagnosis, and control support. Another dimension of the problem space is that different systems must be integrated seamlessly so that communication speed and data handling appear as a continuum (un-interrupted). One such team investigating this problem is the Advanced Integration Matrix (AIM) team whose role is to define the critical requirements expected of software and hardware to support an integrated approach to the command and control of Advanced Life Support (ALS) for future long-duration human space missions, including permanent human presence on the Moon and Mars. A goal of the AIM team is to set the foundation for testing criteria that will assist in specifying tasks, control schemes and test scenarios to validate and verify systems capabilities. This project is to contribute to the goals of the AIM team by assisting with controls planning for ALS. Control for ALS is an enormous problem it involves air revitalization, water recovery, food production, solids processing and crew. In more general terms, these systems can be characterized as involving both continuous and discrete processes, dynamic interactions among the sub-systems, nonlinear behavior due to the complex operations, and a large number of multivariable interactions due to the dimension of the state space. It is imperative that a baseline approach from which to measure performance is established especially when the expectation for the control system is complete autonomous control.

Hoo, Karlene A.↗
NASA NTRS2011

CoNNeCT Baseband Processor Module

A document describes the CoNNeCT Baseband Processor Module (BPM) based on an updated processor, memory technology, and field-programmable gate arrays (FPGAs). The BPM was developed from a requirement to provide sufficient computing power and memory storage to conduct experiments for a Software Defined Radio (SDR) to be implemented. The flight SDR uses the AT697 SPARC processor with on-chip data and instruction cache. The non-volatile memory has been increased from a 20-Mbit EEPROM (electrically erasable programmable read only memory) to a 4-Gbit Flash, managed by the RTAX2000 Housekeeper, allowing more programs and FPGA bit-files to be stored. The volatile memory has been increased from a 20-Mbit SRAM (static random access memory) to a 1.25-Gbit SDRAM (synchronous dynamic random access memory), providing additional memory space for more complex operating systems and programs to be executed on the SPARC. All memory is EDAC (error detection and correction) protected, while the SPARC processor implements fault protection via TMR (triple modular redundancy) architecture. Further capability over prior BPM designs includes the addition of a second FPGA to implement features beyond the resources of a single FPGA. Both FPGAs are implemented with Xilinx Virtex-II and are interconnected by a 96-bit bus to facilitate data exchange. Dedicated 1.25- Gbit SDRAMs are wired to each Xilinx FPGA to accommodate high rate data buffering for SDR applications as well as independent SpaceWire interfaces. The RTAX2000 manages scrub and configuration of each Xilinx.

Yamamoto, Clifford K↗
NASA NTRSDate not supplied

Investigating Risks Due to Artemis EVA Tempo Via Probabilistic Risk Assessment

Spaceflight operations pose unique challenges to crew health, safety, and resource management. As space agencies and private companies continue to push the boundaries of human exploration, it is essential to understand the risks associated with Extravehicular Activities (EVAs) and develop strategies to mitigate them. The tempo at which EVAs are conducted – the total number and frequency of these activities – can have a profound impact on medical risks, resource consumption, and overall mission success. Probabilistic risk assessment (PRA) provides a powerful framework for evaluating complex systems and identifying potential hazards. Our work employs the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) [1] to simulate mission events, occurrence and treatment of medical conditions, and track the utilization of resources. Coupled with the Evidence Library [2], a medical evidence base for exploration-class missions developed by the Exploration Medical Capability within NASA’s Human Research Program, we can estimate these risks with increased fidelity and optimize medical kit contents to meet specific mission requirements. This presentation provides a detailed examination of how EVA tempo influences medical risk estimates for a lunar surface design reference mission. A comprehensive analysis is conducted to assess the additional mass and volume burden imposed on medical kits required to maintain adequate levels of risk mitigation. Furthermore, we estimate the distribution of the number of successful EVAs completed based on the level of task impairment imposed by medical events and flight rules related to specific medical events, such as decompression sickness.

Modeling↗
NASA NTRS1978

Galileo dual-spin attitude and articulation control system

Galileo, the first outer planet explorer to be configured as a dual spinner, will conduct intensive investigation of Jupiter's atmosphere, satellites, and magnetosphere. The exacting mission, coupled with the inherently complex spin and flexible body dynamics of the vehicle, demands careful design of the Galileo Attitude and Articulation Control System (AACS). A brief overview of the Galileo mission and spacecraft is presented, followed by a detailed discussion on the mechanization of the AACS and the many factors that influence its design. Included are discussions on attitude determination and control, high-gain antenna pointing, science scan platform pointing, nutation damping, wobble compensation, spin and despin control, and propellant migration and boom flexibility effects.

Ward, R. S.↗
NASA NTRS1988

On-orbit parametric identification methodology

On-orbit system identification (ID) of large space systems is essential for various reasons. For example, the complex composite structure of such systems cannot be ground-tested; their structural dynamic characteristics must be known accurately in order to accomplish active control. Furthermore, such capability can be used to characterize/identify various disturbances. The identification process is consisted of four principal elements: (1) modeling, (2) the estimation algorithm, (3) input system, and (4) measurement system. These elements are highly correlated and all togerher determine the success of the identification problem. Accurate modeling of large space systems is the most important element of the identification process. Large flexible structures are non-linear and infinite dimensional systems with highly coupled parameters and low frequency packed modes. In addition, these systems are subject to stochastic and time-varying disturbances, they have structural parameters which can vary due to on-orbit assembly deployment, and operations. These systems are generally; however, represented by constant coefficient, finite order differential equations. The non-linearities, coupling and noise effects are also often neglected. Moreover, identification experiment designs which lead to highly complex optimization problems usually require the simultaneous choice of ID algorithm, sensor, and actuator type and placement. On-orbit bandwidth and power restrictions on excitation, limited data window, and restrictions on sensor/actuator type, placement and number, has led to practical questions of implementations.

Hadaegh, Fred Y.↗
NASA NTRS1985

Operational fitness of box truss antennas in response to dynamic slewing

A parametric study was performed to define slewing capability of large satellites along with associated system changes or subsystem weight and complexity impacts. The satellite configuration and structural arrangement from the Earth Observation Spacecraft (EOS) study was used as the baseline spacecraft. Varying slew rates, settling times, damping, maneuver frequencies, and attitude hold times provided the data required to establish applicability to a wide range of potential missions. The key elements of the study are: (1) determine the dynamic transient response of the antenna system; (2) calculate the system errors produced by the dynamic response; (3) determine if the antenna has exceeded operational requirements at completion of the slew, and if so; (4) determine when the antenna has settled to the operational requirements. The slew event is not considered complete until the antenna is within operational limits.

Bachtell, E. E.↗
NASA NTRS1989

Aeromechanics and man-machine integration technology opportunities for rotorcraft of the 1990s and beyond

Programs related to rotorcraft aeromechanics and man-machine integration are discussed which will support advanced army rotorcraft design. In aeromechanics, recent advances in computational fluid dynamics will be used to characterize the complex unsteady flowfields of rotorcraft, and a second-generation comprehensive helicopter analysis system will be used along with models of aerodynamics, engines, and control systems to study the structural dynamics of rotor/body configurations. The man-machine integration program includes the development of advanced cockpit design technology and the evaluation of cockpit and mission equipment concepts in a real-time full-combat environment.

Kerr, Andrew W.↗
NASA NTRS2005

Analyses Of Transient Events In Complex Valve and Feed Systems

Valve systems in rocket propulsion systems and testing facilities are constantly subject to dynamic events resulting from the timing of valve motion leading to unsteady fluctuations in pressure and mass flow. Such events can also be accompanied by cavitation, resonance, system vibration leading to catastrophic failure. High-fidelity dynamic computational simulations of valve operation can yield important information of valve response to varying flow conditions. Prediction of transient behavior related to valve motion can serve as guidelines for valve scheduling, which is of crucial importance in engine operation and testing. In this paper, we present simulations of the diverse unsteady phenomena related to valve and feed systems that include valve stall, valve timing studies as well as cavitation instabilities in components utilized in the test loop.

Ahuja, Vineet↗
NASA NTRS2021

Bias Correction of Hydrologic Projections Strongly Impacts Inferred Climate Vulnerabilities in Institutionally Complex Water Systems

Water-resources planners use regional water management models (WMMs) to identify vulnerabilities to climate change. Frequently, dynamically downscaled climate inputs are used in conjunction with land-surface models (LSMs) to provide hydrologic streamflow projections, which serve as critical inputs for WMMs. Here, we show how even modest projection errors can strongly affect assessments of water availability and financial stability for irrigation districts in California. Specifically, our results highlight that LSM errors in projections of flood and drought extremes are highly interactive across timescales, path-dependent, and can be amplified when modeling infrastructure systems (e.g., misrepresenting banked groundwater). Common strategies for reducing errors in deterministic LSM hydrologic projections (e.g., bias correction) can themselves strongly distort projected climate vulnerabilities and misrepresent their inferred financial consequences. Overall, our results indicate a need to move beyond standard deterministic climate projection and error management frameworks that are dependent on single simulated climate change scenario outcomes.

Keyvan Malek↗
NASA NTRS1988

Modelling and Control of an Annular Momentum Control Device

The results of a modelling and control study for an advanced momentum storage device supported on magnetic bearings are documented. The control challenge posed by this device lies in its dynamics being such a strong function of flywheel rotational speed. At high rotational speed, this can lead to open loop instabilities, resulting in requirements for minimum and maximum control bandwidths and gains for the stabilizing controllers. Using recently developed analysis tools for systems described by complex coefficient differential equations, the closed properties of the controllers were analyzed and stability properties established. Various feedback controllers are investigated and discussed. Both translational and angular dynamics compensators are developed, and measures of system stability and robustness to plant and operational speed variations are presented.

Downer, James R.↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
NASA NTRS1995

Advanced Methodology for Simulation of Complex Flows Using Structured Grid Systems

Detailed simulations of viscous flows in complicated geometries pose a significant challenge to current capabilities of Computational Fluid Dynamics (CFD). To enable routine application of CFD to this class of problems, advanced methodologies are required that employ (a) automated grid generation, (b) adaptivity, (c) accurate discretizations and efficient solvers, and (d) advanced software techniques. Each of these ingredients contributes to increased accuracy, efficiency (in terms of human effort and computer time), and/or reliability of CFD software. In the long run, methodologies employing structured grid systems will remain a viable choice for routine simulation of flows in complex geometries only if genuinely automatic grid generation techniques for structured grids can be developed and if adaptivity is employed more routinely. More research in both these areas is urgently needed.

Steinthorsson, Erlendur↗
NASA NTRS2010

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗
NASA NTRS1995

Advanced in Visualization of 3D Time-Dependent CFD Solutions

Numerical simulations of complex 3D time-dependent (unsteady) flows are becoming increasingly feasible because of the progress in computing systems. Unfortunately, many existing flow visualization systems were developed for time-independent (steady) solutions and do not adequately depict solutions from unsteady flow simulations. Furthermore, most systems only handle one time step of the solutions individually and do not consider the time-dependent nature of the solutions. For example, instantaneous streamlines are computed by tracking the particles using one time step of the solution. However, for streaklines and timelines, particles need to be tracked through all time steps. Streaklines can reveal quite different information about the flow than those revealed by instantaneous streamlines. Comparisons of instantaneous streamlines with dynamic streaklines are shown. For a complex 3D flow simulation, it is common to generate a grid system with several millions of grid points and to have tens of thousands of time steps. The disk requirement for storing the flow data can easily be tens of gigabytes. Visualizing solutions of this magnitude is a challenging problem with today's computer hardware technology. Even interactive visualization of one time step of the flow data can be a problem for some existing flow visualization systems because of the size of the grid. Current approaches for visualizing complex 3D time-dependent CFD solutions are described. The flow visualization system developed at NASA Ames Research Center to compute time-dependent particle traces from unsteady CFD solutions is described. The system computes particle traces (streaklines) by integrating through the time steps. This system has been used by several NASA scientists to visualize their CFD time-dependent solutions. The flow visualization capabilities of this system are described, and visualization results are shown.

Lane, David A.↗
NASA NTRS1991

Instrumentation, performance visualization, and debugging tools for multiprocessors

The need for computing power has forced a migration from serial computation on a single processor to parallel processing on multiprocessor architectures. However, without effective means to monitor (and visualize) program execution, debugging, and tuning parallel programs becomes intractably difficult as program complexity increases with the number of processors. Research on performance evaluation tools for multiprocessors is being carried out at ARC. Besides investigating new techniques for instrumenting, monitoring, and presenting the state of parallel program execution in a coherent and user-friendly manner, prototypes of software tools are being incorporated into the run-time environments of various hardware testbeds to evaluate their impact on user productivity. Our current tool set, the Ames Instrumentation Systems (AIMS), incorporates features from various software systems developed in academia and industry. The execution of FORTRAN programs on the Intel iPSC/860 can be automatically instrumented and monitored. Performance data collected in this manner can be displayed graphically on workstations supporting X-Windows. We have successfully compared various parallel algorithms for computational fluid dynamics (CFD) applications in collaboration with scientists from the Numerical Aerodynamic Simulation Systems Division. By performing these comparisons, we show that performance monitors and debuggers such as AIMS are practical and can illuminate the complex dynamics that occur within parallel programs.

Yan, Jerry C.↗