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At least 487 records · Page 27

Digital temperature and velocity control of mach 0.3 atmospheric pressure durability testing burner rigs in long time, unattended cyclic testing

Hardware and software were developed to implement the hybrid digital control of two Jet A-1 fueled Mach 0.3 burners from startup to completion of a preset number of hot corrosion flame durability cycle tests of materials at 1652 F. This was accomplished by use of a basic language programmable microcomputer and data aquisition and control unit connected together by the IEEE-488 Bus. The absolute specimen temperature was controlled to + or - 3 F by use of digital adjustment of the fuel flow using a P-I-D (Proportional-Integral-Derivative) control algorithm. The specimen temperature was within + or - 2 F of the set point more than 90 percent of the time. Pressure control was achieved by digital adjustment of the combustion air flow using a proportional control algorithm. The burner pressure was controlled at 1.0 + or - 0.02 psig. Logic schemes were incorporated into the system to protect the test specimen from abnormal test conditions in the event of a hardware of software malfunction.

Deadmore, D. L.↗

A Survey of New Trends in Symbolic Execution for Software Testing and Analysis

Symbolic execution is a well-known program analysis technique which represents values of program inputs with symbolic values instead of concrete (initialized) data and executes the program by manipulating program expressions involving the symbolic values. Symbolic execution has been proposed over three decades ago but recently it has found renewed interest in the research community, due in part to the progress in decision procedures, availability of powerful computers and new algorithmic developments. We provide a survey of some of the new research trends in symbolic execution, with particular emphasis on applications to test generation and program analysis. We first describe an approach that handles complex programming constructs such as input data structures, arrays, as well as multi-threading. We follow with a discussion of abstraction techniques that can be used to limit the (possibly infinite) number of symbolic configurations that need to be analyzed for the symbolic execution of looping programs. Furthermore, we describe recent hybrid techniques that combine concrete and symbolic execution to overcome some of the inherent limitations of symbolic execution, such as handling native code or availability of decision procedures for the application domain. Finally, we give a short survey of interesting new applications, such as predictive testing, invariant inference, program repair, analysis of parallel numerical programs and differential symbolic execution.

Pasareanu, Corina S.↗

Online fault adaptive control for efficient resource management in Advanced Life Support Systems

This article presents the design and implementation of a controller scheme for efficient resource management in Advanced Life Support Systems. In the proposed approach, a switching hybrid system model is used to represent the dynamics of the system components and their interactions. The operational specifications for the controller are represented by utility functions, and the corresponding resource management problem is formulated as a safety control problem. The controller is designed as a limited-horizon online supervisory controller that performs a limited forward search on the state-space of the system at each time step, and uses the utility functions to decide on the best action. The feasibility and accuracy of the online algorithm can be assessed at design time. We demonstrate the effectiveness of the scheme by running a set of experiments on the Reverse Osmosis (RO) subsystem of the Water Recovery System (WRS).

NASA Discipline Life Support Systems↗

Numerical simulation of axisymmetric turbulent flow in combustors and diffusors

A method for predicting turbulent flow in combustors and diffusers is developed. The Navier-Stokes equations, incorporating a turbulence kappa-epsilon model equation, were solved in a nonorthogonal curvilinear coordinate system. The solution applied the finite volume method to discretize the differential equations and utilized the SIMPLE algorithm iteratively to solve the differenced equations. A zonal grid method, wherein the flow field was divided into several subsections, was developed. This approach permitted different computational schemes to be used in the various zones. In addition, grid generation was made a more simple task. However, treatment of the zonal boundaries required special handling. Boundary overlap and interpolating techniques were used and an adjustment of the flow variables was required to assure conservation of mass, momentum and energy fluxes. The numerical accuracy was assessed using different finite differencing methods, i.e., hybrid, quadratic upwind and skew upwind, to represent the convection terms. Flows in different geometries of combustors and diffusers were simulated and results compared with experimental data and good agreement was obtained.

Yung, Chain Nan↗

NASA Tech Briefs, October 2008

Topics covered include: Control Architecture for Robotic Agent Command and Sensing; Algorithm for Wavefront Sensing Using an Extended Scene; CO2 Sensors Based on Nanocrystalline SnO2 Doped with CuO; Improved Airborne System for Sensing Wildfires; VHF Wide-Band, Dual-Polarization Microstrip-Patch Antenna; Onboard Data Processor for Change-Detection Radar Imaging; Using LDPC Code Constraints to Aid Recovery of Symbol Timing; System for Measuring Flexing of a Large Spaceborne Structure; Integrated Formation Optical Communication and Estimation System; Making Superconducting Welds between Superconducting Wires; Method for Thermal Spraying of Coatings Using Resonant-Pulsed Combustion; Coating Reduces Ice Adhesion; Hybrid Multifoil Aerogel Thermal Insulation; SHINE Virtual Machine Model for In-flight Updates of Critical Mission Software; Mars Image Collection Mosaic Builder; Providing Internet Access to High-Resolution Mars Images; Providing Internet Access to High-Resolution Lunar Images; Expressions Module for the Satellite Orbit Analysis Program Virtual Satellite; Small-Body Extensions for the Satellite Orbit Analysis Program (SOAP); Scripting Module for the Satellite Orbit Analysis Program (SOAP); XML-Based SHINE Knowledge Base Interchange Language; Core Technical Capability Laboratory Management System; MRO SOW Daily Script; Tool for Inspecting Alignment of Twinaxial Connectors; An ATP System for Deep-Space Optical Communication; Polar Traverse Rover Instrument; Expert System Control of Plant Growth in an Enclosed Space; Detecting Phycocyanin-Pigmented Microbes in Reflected Light; DMAC and NMP as Electrolyte Additives for Li-Ion Cells; Mass Spectrometer Containing Multiple Fixed Collectors; Waveguide Harmonic Generator for the SIM; Whispering Gallery Mode Resonator with Orthogonally Reconfigurable Filter Function; Stable Calibration of Raman Lidar Water-Vapor Measurements; Bimaterial Thermal Compensators for WGM Resonators; Root Source Analysis/ValuStream[Trade Mark] - A Methodology for Identifying and Managing Risks; Ensemble: an Architecture for Mission-Operations Software; Object Recognition Using Feature-and Color-Based Methods; On-Orbit Multi-Field Wavefront Control with a Kalman Filter; and The Interplanetary Overlay Networking Protocol Accelerator.

Source record↗

NASA Tech Briefs, October 2010

Topics covered include: Hybrid Architecture Active Wavefront Sensing and Control; Carbon-Nanotube-Based Chemical Gas Sensor; Aerogel-Positronium Technology for the Detection of Small Quantities of Organic and/or Toxic Materials; Graphene-Based Reversible Nano-Switch/Sensor Schottky Diode; Inductive Non-Contact Position Sensor; High-Temperature Surface-Acoustic-Wave Transducer; Grid-Sphere Electrodes for Contact with Ionospheric Plasma; Enabling IP Header Compression in COTS Routers via Frame Relay on a Simplex Link; Ka-Band SiGe Receiver Front-End MMIC for Transponder Applications; Robust Optimization Design Algorithm for High-Frequency TWTs; Optimal and Local Connectivity Between Neuron and Synapse Array in the Quantum Dot/Silicon Brain; Method and Circuit for In-Situ Health Monitoring of Solar Cells in Space; BGen: A UML Behavior Network Generator Tool; Platform for Post-Processing Waveform-Based NDE; Electrochemical Hydrogen Peroxide Generator; Fabrication of Single, Vertically Aligned Carbon Nanotubes in 3D Nanoscale Architectures; Process to Create High-Fidelity Lunar Dust Simulants; Lithium-Ion Electrolytes Containing Phosphorous-Based, Flame-Retardant Additives; InGaP Heterojunction Barrier Solar Cells; Straight-Pore Microfilter with Efficient Regeneration; Determining Shear Stress Distribution in a Laminate; Self-Adjusting Liquid Injectors for Combustors; Handling Qualities Prediction of an F-16XL-Based Reduced Sonic Boom Aircraft; Tele-Robotic ATHLETE Controller for Kinematics - TRACK; Three-Wheel Brush-Wheel Sampler; Heterodyne Interferometer Angle Metrology; Aligning Astronomical Telescopes via Identification of Stars; Generation of Optical Combs in a WGM Resonator from a Bichromatic Pump; Large-Format AlGaN PIN Photodiode Arrays for UV Images; Fiber-Coupled Planar Light-Wave Circuit for Seed Laser Control in High Spectral Resolution Lidar Systems; On Calculating the Zero-Gravity Surface Figure of a Mirror; Optical Modification of Casimir Forces for Improved Function of Micro- and Nano-Scale Devices; Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems; Core and Off-Core Processes in Systems Engineering; Digital Reconstruction Supporting Investigation of Mishaps; and Template Matching Approach to Signal Prediction.

Source record↗

SPoRT Participation in the GOES-R and JPSS Proving Grounds

For the last several years, the NASA Short-term Prediction Research and Transition (SPoRT) project at has been working with the various algorithm working groups and science teams to demonstrate the utility of future operational sensors for GOES-R and the suite of instruments for the JPSS observing platforms. For GOES-R, imagery and products have been developed from polar-orbiting sensors such as MODIS and geostationary observations from SEVIRI, simulated imagery, enhanced products derived from existing GOES satellites, and data from ground-based observing systems to generate pseudo or proxy products for the ABI and GLM instruments. The suite of products include GOES-POES basic and RGB hybrid imagery, total lightning flash products, quantitative precipitation estimates, and convective initiation products. SPoRT is using imagery and products from VIIRS, CrIS, ATMS, and OMPS to show the utility of data and products from their operational counterparts on JPSS. The products include VIIRS imagery in swath form, the GOES-POES hybrid, a suite of RGB products including the air mass RGB using water vapor and ozone channels from CrIS, and several DNB products. Over a dozen SPoRT collaborative WFOs and several National Centers are involved in an intensive evaluation of the operational utility of these products.

Jedlovec, Gary↗

A study of 'onboard' data processing for typical astrophysics payloads

The data, signal flow, and ground processing requirements for a typical set of X-ray and gamma-ray experiments were examined. A set of algorithms for ground processing were derived and these were taken as requirements imposed on 'onboard' spacecraft computers. Five types of CPU microprocessors were evaluated and compared with one another to determine the degree to which the data processing could be performed onboard the spacecraft. These included the NASA Standard Spacecraft Computer (NSSC-1), the Z-80, a Z-80 augmented with an auxiliary fast multiply chip, and an advanced augmented Z-80 with virtually unlimited memory. These CPU were investigated when used in a centralized mode, an experiment dedicated mode, and a hybrid of the first two modes. It was found that the use of onboard processing can significantly reduce downlink data rates for typical payloads, and may lead to greater efficiency of operation. Quantitative data for gamma-ray and X-ray payloads will be presented, and the results of the analysis discussed.

Stout, C. M.↗

High Rate Digital Demodulator ASIC

The architecture of High Rate (600 Mega-bits per second) Digital Demodulator (HRDD) ASIC capable of demodulating BPSK and QPSK modulated data is presented in this paper. The advantages of all-digital processing include increased flexibility and reliability with reduced reproduction costs. Conventional serial digital processing would require high processing rates necessitating a hardware implementation in other than CMOS technology such as Gallium Arsenide (GaAs) which has high cost and power requirements. It is more desirable to use CMOS technology with its lower power requirements and higher gate density. However, digital demodulation of high data rates in CMOS requires parallel algorithms to process the sampled data at a rate lower than the data rate. The parallel processing algorithms described here were developed jointly by NASA's Goddard Space Flight Center (GSFC) and the Jet Propulsion Laboratory (JPL). The resulting all-digital receiver has the capability to demodulate BPSK, QPSK, OQPSK, and DQPSK at data rates in excess of 300 Mega-bits per second (Mbps) per channel. This paper will provide an overview of the parallel architecture and features of the HRDR ASIC. In addition, this paper will provide an over-view of the implementation of the hardware architectures used to create flexibility over conventional high rate analog or hybrid receivers. This flexibility includes a wide range of data rates, modulation schemes, and operating environments. In conclusion it will be shown how this high rate digital demodulator can be used with an off-the-shelf A/D and a flexible analog front end, both of which are numerically computer controlled, to produce a very flexible, low cost high rate digital receiver.

Ghuman, Parminder↗

Artificial Intelligence Based Control Power Optimization on Tailless Aircraft

Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

Gern, Frank↗

Estimation of the absolute position of mobile systems by an optoelectronic processor

A method that determine the absolute position of a mobile system with a hybrid optoelectronic processor has been developed. Position estimates are based on an analysis of circular landmarks that are detected by a TV camera attached to the mobile system. The difference between the known shape of the landmark and its image provides the information needed to determine the absolute position of the mobile system. For robust operation, the parameters of the landmark image are extracted at high speeds using an optical processor that performs an optical Hough transform. The coordinates of the mobile system are computed from these parameters in a digital co-processor using fast algorithms. Different sources of position estimation errors have also been analyzed, and consequent algorithms to improve the navigation performance of the mobile system have been developed and evaluated by both computer simulation and experiments.

Feng, Liqiang↗

HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation

Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.

Sterling, Thomas↗

Control Algorithms Charge Batteries Faster

On March 29, 2011, NASA s Mercury Surface, Space Environment, Geochemistry and Ranging (MESSENGER) spacecraft beamed a milestone image to Earth: the first photo of Mercury taken from orbit around the solar system s innermost planet. (MESSENGER is also the first spacecraft to orbit Mercury.) Like most of NASA s deep space probes, MESSENGER is enabled by a complex power system that allows its science instruments and communications to function continuously as it travels millions of miles from Earth. "Typically, there isn't one particular power source that can support the entire mission," says Linda Taylor, electrical engineer in Glenn Research Center s Power Systems Analysis Branch. "If you have solar arrays and you are in orbit, at some point you re going to be in eclipse." Because of this, Taylor explains, spacecraft like MESSENGER feature hybrid power systems. MESSENGER is powered by a two-panel solar array coupled with a nickel hydrogen battery. The solar arrays provide energy to the probe and charge the battery; when the spacecraft s orbit carries it behind Mercury and out of the Sun s light, the spacecraft switches to battery power to continue operations. Typically, hybrid systems with multiple power inputs and a battery acting alternately as storage and a power source require multiple converters to handle the power flow between the devices, Taylor says. (Power converters change the qualities of electrical energy, such as from alternating current to direct current, or between different levels of voltage or frequency.) This contributes to a pair of major concerns for spacecraft design. "Weight and size are big drivers for any space application," Taylor says, noting that every pound added to a space vehicle incurs significant costs. For an innovative solution to managing power flows in a lightweight, cost-effective manner, NASA turned to a private industry partner.

Source record↗

The FIELDS Instrument Suite on MMS: Scientific Objectives, Measurements, and Data Products

The FIELDS instrumentation suite on the Magnetospheric Multiscale (MMS) mission provides comprehensive measurements of the full vector magnetic and electric fields in the reconnection regions investigated by MMS, including the dayside magnetopause and the night-side magnetotail acceleration regions out to 25 Re. Six sensors on each of the four MMS spacecraft provide overlapping measurements of these fields with sensitive cross-calibrations both before and after launch. The FIELDS magnetic sensors consist of redundant flux-gate magnetometers (AFG and DFG) over the frequency range from DC to 64 Hz, a search coil magnetometer (SCM) providing AC measurements over the full whistler mode spectrum expected to be seen on MMS, and an Electron Drift Instrument (EDI) that calibrates offsets for the magnetometers. The FIELDS three-axis electric field measurements are provided by two sets of biased double-probe sensors (SDP and ADP) operating in a highly symmetric spacecraft environment to reduce significantly electrostatic errors. These sensors are complemented with the EDI electric measurements that are free from all local spacecraft perturbations. Cross-calibrated vector electric field measurements are thus produced from DC to 100 kHz, well beyond the upper hybrid resonance whose frequency provides an accurate determination of the local electron density. Due to its very large geometric factor, EDI also provides very high time resolution (∼1 ms) ambient electron flux measurements at a few selected energies near 1 keV. This paper provides an overview of the FIELDS suite, its science objectives and measurement requirements, and its performance as verified in calibration and cross-calibration procedures that result in anticipated errors less than 0.1 nT in B and 0.5 mV/m in E. Summaries of data products that result from FIELDS are also described, as well as algorithms for cross-calibration. Details of the design and performance characteristics of AFG/DFG, SCM, ADP, SDP, and EDI are provided in five companion papers.

Electromagnetic field measurements↗

Universal Coating by 3D Hybrid Programmable Matter

Motivated by the prospect of nano-robots that assist human physiological functions at the nanoscale, we investigate the coating problem in the three-dimensional model for hybrid programmable matter. In this model, a single agent with strictly limited viewing range and the computational capability of a deterministic finite automaton can act on passive tiles by picking up a tile, moving, and placing it at some spot. The goal of the coating problem is to fill each node of some surface graph of size n with a tile. We first solve the problem on a restricted class of graphs with a single tile type, and then use constantly many tile types to encode this graph in certain surface graphs capturing the surface of 3D objects. Our algorithm requires O(n^2) steps, which is worst-case optimal compared to an agent with global knowledge and no memory restrictions.

programmable matter↗

Comparing and Integrating Constraint Programming and Temporal Planning for Quantum Circuit Compilation

Recently, the makespan-minimization problem of compiling a general class of quantum algorithms into near-term quantum processors has been introduced to the AI community. The research demonstrated that temporal planning is a strong solution approach for the studied class of quantum circuit compilation (QCC) problems. In this paper, we explore the use of methods from operations research, specifically constraint programming (CP), as an alternative and complementary approach to temporal planning. We also extend previous work by introducing two new problem variations that incorporate important characteristics identified by the quantum computing community. We apply temporal planning and CP to the baseline and extended QCC problems as both stand-alone and hybrid approaches. The hybrid method uses solutions found by temporal planning to warm-start CP, leveraging the ability of temporal planning to find satisficing solutions to problems with a high degree of task optionality, an area that CP typically struggles with. These solutions are then used to seed the CP formulation which significantly benefits from inferred bounds on planning horizon and task counts provided by the warm-start. Our extensive empirical evaluation indicates that while stand-alone CP is not competitive with temporal planning, except for the smallest problems, CP in a hybrid setting is beneficial for all temporal planners in all problem classes.

quantum circuit compilation↗

Exploring Quantum State Preparation Using Tensor Networks and Sparse Wavefunction Simulations

The variational quantum eigenvalue solver is a powerful hybrid quantum-classical approach that has been suggested as a candidate method to run on near-term quantum hardware for computing ground state electronic energies of molecular systems. However, even for small molecules, the number of variational parameters and qubits required to minimize the electronic energy is beyond the reach of current quantum computers except for small basis sets. We explore a new paradigm for state preparation where we test how much of the optimization can be approximately prepared with classical computers to reduce the number of optimization steps performed using a quantum device. By adapting a recent algorithm for the factorized form of the UCC ansatz, we can study molecular electronic structure problems with up to 64 qubits. In addition, we also test a related approach of using tensor networks to optimize quantum circuits in order to benchmark various lattice models. We present results using these approaches and discuss strategies for incorporating these ideas into variational algorithms involving near-term quantum computers. Our results help demonstrate the strength of the UCC ansatz and address pressing questions about optimal initial parameterizations and circuit construction.

quantum computing↗

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 km or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed-shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗