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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

A comparison of the efficiency of numerical methods for integrating chemical kinetic rate equations

A comparison of the efficiency of several algorithms recently developed for the efficient numerical integration of stiff ordinary differential equations is presented. The methods examined include two general-purpose codes EPISODE and LSODE and three codes (CHEMEQ, CREK1D, and GCKP84) developed specifically to integrate chemical kinetic rate equations. The codes are applied to two test problems drawn from combustion kinetics. The comparisons show that LSODE is the fastest code currently available for the integration of combustion kinetic rate equations. An important finding is that an iterative solution of the algebraic energy conservation equation to compute the temperature can be more efficient than evaluating the temperature by integrating its time-derivative.

Radhakrishnan, K.↗
NASA NTRS1993

Implementing abstract multigrid or multilevel methods

Multigrid methods can be formulated as an algorithm for an abstract problem that is independent of the partial differential equation, domain, and discretization method. In such an abstract setting, problems not arising from partial differential equations can be treated. A general theory exists for linear problems. The general theory was motivated by a series of abstract solvers (Madpack). The latest version was motivated by the theory. Madpack now allows for a wide variety of iterative and direct solvers, preconditioners, and interpolation and projection schemes, including user callback ones. It allows for sparse, dense, and stencil matrices. Mildly nonlinear problems can be handled. Also, there is a fast, multigrid Poisson solver (two and three dimensions). The type of solvers and design decisions (including language, data structures, external library support, and callbacks) are discussed. Based on the author's experiences with two versions of Madpack, a better approach is proposed. This is based on a mixed language formulation (C and FORTRAN + preprocessor). Reasons for not using FORTRAN, C, or C++ (individually) are given. Implementing the proposed strategy is not difficult.

Douglas, Craig C.↗
NASA NTRS2001

An Analysis of an Automatic Coolant Bypass in the International Space Station Node 2 Internal Active Thermal Control System

A challenging part of International Space Station (ISS) thermal control design is the ability to incorporate design changes into an integrated system without negatively impacting performance. The challenge presents itself in that the typical ISS Internal Active Thermal Control System (IATCS) consists of an integrated hardware/software system that provides active coolant resources to a variety of users. Software algorithms control the IATCS to specific temperatures, flow rates, and pressure differentials in order to meet the user-defined requirements. What may seem to be small design changes imposed on the system may in fact result in system instability or the temporary inability to meet user requirements. The purpose of this paper is to provide a brief description of the solution process and analyses used to implement one such design change that required the incorporation of an automatic coolant bypass in the ISS Node 2 element.

Clanton, Stephen E.↗
NASA NTRS2005

Remote Sensing of Particulate Organic Carbon Pools in the High-Latitude Oceans

The general goal of this project was to characterize spatial distributions at basin scales and variability on monthly to interannual timescales of particulate organic carbon (POC) in the high-latitude oceans. The primary objectives were: (1) To collect in situ data in the north polar waters of the Atlantic and in the Southern Ocean, necessary for the derivation of POC ocean color algorithms for these regions. (2) To derive regional POC algorithms and refine existing regional chlorophyll (Chl) algorithms, to develop understanding of processes that control bio-optical relationships underlying ocean color algorithms for POC and Chl, and to explain bio-optical differentiation between the examined polar regions and within the regions. (3) To determine basin-scale spatial patterns and temporal variability on monthly to interannual scales in satellite-derived estimates of POC and Chl pools in the investigated regions for the period of time covered by SeaWiFS and MODIS missions.

Stramski, Dariusz↗
NASA NTRS1989

Modified Chebyshev pseudospectral method with O(N exp -1) time step restriction

The extreme eigenvalues of the Chebyshev pseudospectral differentiation operator are O(N exp 2) where N is the number of grid points. As a result of this, the allowable time step in an explicit time marching algorithm is O(N exp -2) which, in many cases, is much below the time step dictated by the physics of the partial differential equation. A new set of interpolating points is introduced such that the eigenvalues of the differentiation operator are O(N) and the allowable time step is O(N exp -1). The properties of the new algorithm are similar to those of the Fourier method. The new algorithm also provides a highly accurate solution for non-periodic boundary value problems.

Kosloff, Dan↗
NASA NTRS1993

A modified Chebyshev pseudospectral method with an O(N exp -1) time step restriction

The extreme eigenvalues of the Chebyshev pseudospectral differentiation operator are O(N exp 2) where N is the number of grid points. As a result of this, the allowable time step in an explicit time marching algorithm is O(N exp -2) which, in many cases, is much below the time step dictated by the physics of the partial differential equation. A new set of interpolating points is introduced such that the eigenvalues of the differentiation operator are O(N) and the allowable time step is O(N exp -1). The properties of the new algorithm are similar to those of the Fourier method. The new algorithm also provides a highly accurate solution for non-periodic boundary value problems.

Kosloff, Dan↗
NASA NTRSDate not supplied

TPSAS-NF1676L-20108-DND

This presentation describes several enhancements planned for the version 4 aerosol subtyping and lidar ratio selection algorithms of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The CALIOP subtyping algorithm determines the most likely aerosol type from CALIOP measurements (attenuated backscatter, estimated particulate depolarization ratios de, layer altitude), and surface type. The aerosol type, so determined, is associated with a lidar ratio (LR) from a discrete set of values. In the version 3 algorithms, there are 6 pairs of 532 and 1064 nm lidar ratios. Some of these lidar ratios will be updated in the version 4 algorithms. In particular, the dust and polluted dust will be adjusted to reflect the latest measurements and model studies of these types. The algorithms are being updated to eliminate the occasional confusion between smoke and clean marine aerosols seen in version 3 by modifications to the elevated layer flag definitions that are used to determine the presence of smoke aerosols over the ocean. In the subtyping algorithms pure dust is determined by high estimated particulate depolarization ratios [de > 0.20]. Mixtures of dust and other aerosol types are determined by intermediate values of the estimated depolarization ratio [0.075< de <0.2]. The version 3 algorithms are limited to mixtures of dust and smoke, the so-called polluted dust aerosol type. To differentiate between mixtures of dust and smoke, and dust and marine aerosols, a new aerosol type will be added in the version 4 data products. In the revised classification algorithms, polluted dust will still defined as dust + smoke/pollution but in the marine boundary layer instances of moderate depolarization will be typed as dusty marine aerosols with a lower lidar ratio [LR = 35 sr] than polluted dust [currently LR = 55 sr]. The dusty marine type introduced in version 4 is modeled as a mixture of dust + marine aerosol. In the v3 algorithms the frequency of dust and polluted dust aerosols at daytime is higher than at nighttime. We present possible reasons for this and present the v4 distributions resulting from both improved background slope corrections of the daytime depolarization ratios and changes to the daytime thresholds for the polluted dust and dusty marine types of version 4. To gauge the impact of the enhancements, we contrast the following between versions 3 and 4: aerosol type, parameter distributions of each type, layer heights of maximum frequency, and distributions of smoke in biomass burning regions. To illustrate specific impacts the presentation shows case studies of version 3 and version 4 vertical feature masks of the aerosol subtypes, where appropriate, for the above enhancements.

A Omar↗
NASA NTRS1991

On-orbit demonstration of automated closure and capture using ESA-developed proximity operations technologies and an existing, serviceable NASA Explorer Platform spacecraft

The European Space Agency (ESA) has been working to develop an autonomous rendezvous and docking capability since 1984 to enable Hermes to automatically dock with Columbus. As a result, ESA with Matra, MBB, and other space companies have developed technologies that are also directly supportive of the current NASA initiative for Automated Rendezvous and Capture. Fairchild and Matra would like to discuss the results of the applicable ESA/Matra rendezvous and capture developments, and suggest how these capabilities could be used, together with an existing NASA Explorer Platform satellite, to minimize new development and accomplish a cost effective automatic closure and capture demonstration program. Several RV sensors have been developed at breadboard level for the Hermes/Columbus program by Matra, MBB, and SAAB. Detailed algorithms for automatic rendezvous, closure, and capture have been developed by ESA and CNES for application with Hermes to Columbus rendezvous and docking, and they currently are being verified with closed-loop software simulation. The algorithms have multiple closed-loop control modes and phases starting at long range using GPS navigation. Differential navigation is used for coast/continuous thrust homing, holdpoint acquisition, V-bar hopping, and station point acquisition. The proximity operation sensor is used for final closure and capture. A subset of these algorithms, comprising the proximity operations algorithms, could easily be extracted and tailored to a limited objective closure and capture flight demonstration.

Hohwiesner, Bill↗
NASA NTRS2001

Low power, lightweight vapor sensing using arrays of conducting polymer composite chemically-sensitive resistors

Arrays of broadly responsive vapor detectors can be used to detect, identify, and quantify vapors and vapor mixtures. One implementation of this strategy involves the use of arrays of chemically-sensitive resistors made from conducting polymer composites. Sorption of an analyte into the polymer composite detector leads to swelling of the film material. The swelling is in turn transduced into a change in electrical resistance because the detector films consist of polymers filled with conducting particles such as carbon black. The differential sorption, and thus differential swelling, of an analyte into each polymer composite in the array produces a unique pattern for each different analyte of interest, Pattern recognition algorithms are then used to analyze the multivariate data arising from the responses of such a detector array. Chiral detector films can provide differential detection of the presence of certain chiral organic vapor analytes. Aspects of the spaceflight qualification and deployment of such a detector array, along with its performance for certain analytes of interest in manned life support applications, are reviewed and summarized in this article.

NASA Discipline Life Sciences Technologies↗
NASA NTRS2013

Fuzzy Reasoning to More Accurately Determine Void Areas on Optical Micrographs of Composite Structures

Accomplishing the best-performing composite matrix (resin) requires that not only the processing method but also the cure cycle generate low-void-content structures. If voids are present, the performance of the composite matrix will be significantly reduced. This is usually noticed by significant reductions in matrix-dominated properties, such as compression and shear strength. Voids in composite materials are areas that are absent of the composite components: matrix and fibers. The characteristics of the voids and their accurate estimation are critical to determine for high performance composite structures. One widely used method of performing void analysis on a composite structure sample is acquiring optical micrographs or Scanning Electron Microscope (SEM) images of lateral sides of the sample and retrieving the void areas within the micrographs/images using an image analysis technique. Segmentation for the retrieval and subsequent computation of void areas within the micrographs/images is challenging as the gray-scaled values of the void areas are close to the gray-scaled values of the matrix leading to the need of manually performing the segmentation based on the histogram of the micrographs/images to retrieve the void areas. The use of an algorithm developed by NASA and based on Fuzzy Reasoning (FR) proved to overcome the difficulty of suitably differentiate void and matrix image areas with similar gray-scaled values leading not only to a more accurate estimation of void areas on composite matrix micrographs but also to a faster void analysis process as the algorithm is fully autonomous.

Dominquez, Jesus A.↗
NASA NTRS1992

Spurious Solutions Of Nonlinear Differential Equations

Report utilizes nonlinear-dynamics approach to investigate possible sources of errors and slow convergence and non-convergence of steady-state numerical solutions when using time-dependent approach for problems containing nonlinear source terms. Emphasizes implications for development of algorithms in CFD and computational sciences in general. Main fundamental conclusion of study is that qualitative features of nonlinear differential equations cannot be adequately represented by finite-difference method and vice versa.

Yee, H. C.↗
NASA NTRS1981

Multigrid solvers on parallel computers

Massively parallel computers, as considered in this investigation, are not yet available. However, a large-scale parallel computer cannot usefully be designed before the hypothetical algorithms which will employ it are studied. Most of the studies of parallel partial differential equations (PDE) solvers are based on solution techniques much slower (on sequential machines) than multigrid methods. Multigrid methods are highly parallelizable. Each of their processes can simultaneously be performed at all grid points. The present investigation is concerned with a preliminary exploration of the potential of multigrid, or, more generally, Multi-Level Adaptive Techniques (MLAT) on computers with many processors. Basic processes are considered, taking into account coarse-grid approximation, relaxation, coarse-grid corrections, full multigrid algorithms, nonlinear problems and eigenvalue problems, fine-to-coarse correction, and chains of problems. Details of parallel multigrid processing are also examined.

Brandt, A.↗
NASA NTRS1990

Approximations of thermoelastic and viscoelastic control systems

Well-posed models and computational algorithms are developed and analyzed for control of a class of partial differential equations that describe the motions of thermo-viscoelastic structures. An abstract (state space) framework and a general well-posedness result are presented that can be applied to a large class of thermo-elastic and thermo-viscoelastic models. This state space framework is used in the development of a computational scheme to be used in the solution of a linear quadratic regulator (LQR) control problem. A detailed convergence proof is provided for the viscoelastic model and several numerical results are presented to illustrate the theory and to analyze problems for which the theory is incomplete.

Burns, J. A.↗
NASA NTRS1989

Gradient methods for identification of distributed parameter systems

Parameter-dependence properties are developed in the context of a linear abstract Cauchy problem governed by a parameter-dependent operator. Of particular interest are problems in which the parameter induces an unbounded perturbation of the evolution operator. Conditions are stated under which the derivative of the state with respect to the parameter possesses certain smoothness properties. These properties lead to local convergence results for a gradient-based estimation algorithm based on quasi-linearization. Numerical results concerning a delay-differential equation indicate the effect of a forcing function on parameter sensitivity.

Brewer, Dennis W.↗
NASA NTRS1990

A parallel iterative solution method for systems of nonlinear hyperbolic equations

An iterative algorithm suitable for the solution of a system of nonlinear hyperbolic partial differentiation equations in multiple dimensions is discussed. Current numerical methods for systems of nonlinear PDEs have limited parallelism due to strong coupling between the equations. This method decouples the PDEs by linearizing the convention coefficient for a space-time domain. This provides large grain parallelism. The linearization also allows the treatment of some terms in the equations as source terms, providing more freedom to choose from a wider variety of numerical methods. Smaller grain parallelism may be exploited within the solves for each equation. Thus, the method has potential for parallelism at several levels.

Scroggs, Jeffrey S.↗
NASA NTRS1993

Investigation for improving Global Positioning System (GPS) orbits using a discrete sequential estimator and stochastic models of selected physical processes

GEODYNII is a conventional batch least-squares differential corrector computer program with deterministic models of the physical environment. Conventional algorithms were used to process differenced phase and pseudorange data to determine eight-day Global Positioning system (GPS) orbits with several meter accuracy. However, random physical processes drive the errors whose magnitudes prevent improving the GPS orbit accuracy. To improve the orbit accuracy, these random processes should be modeled stochastically. The conventional batch least-squares algorithm cannot accommodate stochastic models, only a stochastic estimation algorithm is suitable, such as a sequential filter/smoother. Also, GEODYNII cannot currently model the correlation among data values. Differenced pseudorange, and especially differenced phase, are precise data types that can be used to improve the GPS orbit precision. To overcome these limitations and improve the accuracy of GPS orbits computed using GEODYNII, we proposed to develop a sequential stochastic filter/smoother processor by using GEODYNII as a type of trajectory preprocessor. Our proposed processor is now completed. It contains a correlated double difference range processing capability, first order Gauss Markov models for the solar radiation pressure scale coefficient and y-bias acceleration, and a random walk model for the tropospheric refraction correction. The development approach was to interface the standard GEODYNII output files (measurement partials and variationals) with software modules containing the stochastic estimator, the stochastic models, and a double differenced phase range processing routine. Thus, no modifications to the original GEODYNII software were required. A schematic of the development is shown. The observational data are edited in the preprocessor and the data are passed to GEODYNII as one of its standard data types. A reference orbit is determined using GEODYNII as a batch least-squares processor and the GEODYNII measurement partial (FTN90) and variational (FTN80, V-matrix) files are generated. These two files along with a control statement file and a satellite identification and mass file are passed to the filter/smoother to estimate time-varying parameter states at each epoch, improved satellite initial elements, and improved estimates of constant parameters.

Goad, Clyde C.↗