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NASA NTRS2017

Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.

Classification; Climate change; Crop model; Ensemb↗

NASA NTRS1989

Partitioning strategy for efficient nonlinear finite element dynamic analysis on multiprocessor computers

A computational procedure is presented for the nonlinear dynamic analysis of unsymmetric structures on vector multiprocessor systems. The procedure is based on a novel hierarchical partitioning strategy in which the response of the unsymmetric and antisymmetric response vectors (modes), each obtained by using only a fraction of the degrees of freedom of the original finite element model. The three key elements of the procedure which result in high degree of concurrency throughout the solution process are: (1) mixed (or primitive variable) formulation with independent shape functions for the different fields; (2) operator splitting or restructuring of the discrete equations at each time step to delineate the symmetric and antisymmetric vectors constituting the response; and (3) two level iterative process for generating the response of the structure. An assessment is made of the effectiveness of the procedure on the CRAY X-MP/4 computers.

Noor, Ahmed K.↗

NASA NTRS1989

A partitioning strategy for efficient nonlinear finite element dynamic analysis on multiprocessor computer

Noor, Ahmed K.↗

NASA NTRS2014

A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

Light Detection & Ranging (LIDAR)↗

NASA NTRS1993

Design for testability and diagnosis at the system-level

The growing complexity of full-scale systems has surpassed the capabilities of most simulation software to provide detailed models or gate-level failure analyses. The process of system-level diagnosis approaches the fault-isolation problem in a manner that differs significantly from the traditional and exhaustive failure mode search. System-level diagnosis is based on a functional representation of the system. For example, one can exercise one portion of a radar algorithm (the Fast Fourier Transform (FFT) function) by injecting several standard input patterns and comparing the results to standardized output results. An anomalous output would point to one of several items (including the FFT circuit) without specifying the gate or failure mode. For system-level repair, identifying an anomalous chip is sufficient. We describe here an information theoretic and dependency modeling approach that discards much of the detailed physical knowledge about the system and analyzes its information flow and functional interrelationships. The approach relies on group and flow associations and, as such, is hierarchical. Its hierarchical nature allows the approach to be applicable to any level of complexity and to any repair level. This approach has been incorporated in a product called STAMP (System Testability and Maintenance Program) which was developed and refined through more than 10 years of field-level applications to complex system diagnosis. The results have been outstanding, even spectacular in some cases. In this paper we describe system-level testability, system-level diagnoses, and the STAMP analysis approach, as well as a few STAMP applications.

Simpson, William R.↗

NASA NTRSDate not supplied

3D Phase-Field Simulations of Pattern Formation During Freeze Casting

We present the results of a combined experimental and phase-field modeling study of pattern formation during freeze casting. Those studies use unidirectional freezing of simple binary liquid mixtures of water and sugars (sucrose and trehalose) in a temperature gradient, which suffice to produce hierarchical templated structures similar to those observed in more complex multi-component freeze-cast systems including lamellae, undulated ridges, and more exotic “jellyfish-like” substructures. Multiscale 3D phase-field simulations reproduce remarkably well those structures quantitatively and identify key properties of the ice-water interface that control their formation. They further reveal that lamellae form as a result of a novel symmetry-breaking secondary instability of partially faceted cellular structures and pinpoint additional secondary instability mechanisms giving rise to smaller-scale substructures.

Kaihua Ji↗

NASA NTRSDate not supplied

3D Phase-Field Simulations of Pattern Formation During Freeze Casting

Kaihua Ji↗

NASA NTRS2016

Improved Convergence and Robustness of USM3D Solutions on Mixed-Element Grids

Several improvements to the mixed-elementUSM3Ddiscretization and defect-correction schemes have been made. A new methodology for nonlinear iterations, called the Hierarchical Adaptive Nonlinear Iteration Method, has been developed and implemented. The Hierarchical Adaptive Nonlinear Iteration Method provides two additional hierarchies around a simple and approximate preconditioner of USM3D. The hierarchies are a matrix-free linear solver for the exact linearization of Reynolds-averaged Navier-Stokes equations and a nonlinear control of the solution update. Two variants of the Hierarchical Adaptive Nonlinear Iteration Method are assessed on four benchmark cases, namely, a zero-pressure-gradient flat plate, a bump-in-channel configuration, the NACA 0012 airfoil, and a NASA Common Research Model configuration. The new methodology provides a convergence acceleration factor of 1.4 to 13 over the preconditioner-alone method representing the baseline solver technology.

Pandya, Mohagna J.↗

NASA NTRS2016

Improved Convergence and Robustness of USM3D Solutions on Mixed-Element Grids

Several improvements to the mixed-element USM3D discretization and defect-correction schemes have been made. A new methodology for nonlinear iterations, called the Hierarchical Adaptive Nonlinear Iteration Method, has been developed and implemented. The Hierarchical Adaptive Nonlinear Iteration Method provides two additional hierarchies around a simple and approximate preconditioner of USM3D. The hierarchies are a matrix-free linear solver for the exact linearization of Reynolds-averaged Navier-Stokes equations and a nonlinear control of the solution update. Two variants of the Hierarchical Adaptive Nonlinear Iteration Method are assessed on four benchmark cases, namely, a zero-pressure-gradient flat plate, a bump-in-channel configuration, the NACA 0012 airfoil, and a NASA Common Research Model configuration. The new methodology provides a convergence acceleration factor of 1.4 to 13 over the preconditioner-alone method representing the baseline solver technology.

Pandya, Mohagna J.↗

NASA NTRS1985

Protostars and planets II

Various papers on the formation of stars and planets are presented. The general topics addressed include: molecular clouds and star formation, young stellar objects and circumstellar disks, chemistry and grains in molecular clouds and the solar nebula, formation of giant planets, and models of the solar nebula and other planetary systems. Individual papers address: molecular cloud cores, physical conditions in isolated dark globules, rotation in dark clouds, and turbulence in molecular clouds. Also discussed are: fragmentation and hierarchical structure in the interstellar medium, formation of bound stellar clusters, ambient radiation field of young solar systems, and magnetic fields.

Black, D. C.↗

NASA NTRS2013

Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

This paper describes the core framework used to implement a Goal-Function Tree (GFT) based systems engineering process using the Systems Modeling Language. It defines a set of principles built upon by the theoretical approach described in the InfoTech 2013 ISHM paper titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management" presented by Dr. Stephen B. Johnson. Using the SysML language, the principles in this paper describe the expansion of the SysML language as a baseline in order to: hierarchically describe a system, describe that system functionally within success space, and allocate detection mechanisms to success functions for system protection.

Breckenridge, Jonathan T.↗

NASA NTRS2016

Airborne Spectral BRDF of Various Surface Types (Ocean, Vegetation, Snow, Desert, Wetlands, Cloud Decks, Smoke Layers) for Remote Sensing Applications

In this paper we describe measurements of the bidirectional reflectance-distribution function (BRDF) acquired over a 30-year period (1984-2014) by the National Aeronautics and Space Administration's (NASA's) Cloud Absorption Radiometer (CAR). Our BRDF database encompasses various natural surfaces that are representative of many land cover or ecosystem types found throughout the world. CAR's unique measurement geometry allows a comparison of measurements acquired from different satellite instruments with various geometrical configurations, none of which are capable of obtaining such a complete and nearly instantaneous BRDF. This database is therefore of great value in validating many satellite sensors and assessing corrections of reflectances for angular effects. These data can also be used to evaluate the ability of analytical models to reproduce the observed directional signatures, to develop BRDF models that are suitable for sub-kilometer-scale satellite observations over both homogeneous and heterogeneous landscape types, and to test future spaceborne sensors. All of these BRDF data are publicly available and accessible in hierarchical data format (http:car.gsfc.nasa.gov/).

albedo↗

NASA NTRS1972

Utilization of a CRT display light pen in the design of feedback control systems

A hierarchical structure of the interlinked programs was developed to provide a flexible computer-aided design tool. A graphical input technique and a data structure are considered which provide the capability of entering the control system model description into the computer in block diagram form. An information storage and retrieval system was developed to keep track of the system description, and analysis and simulation results, and to provide them to the correct routines for further manipulation or display. Error analysis and diagnostic capabilities are discussed, and a technique was developed to reduce a transfer function to a set of nested integrals suitable for digital simulation. A general, automated block diagram reduction procedure was set up to prepare the system description for the analysis routines.

Thompson, J. G.↗

NASA NTRS1990

Analysis and design of algorithm-based fault-tolerant systems

An important consideration in the design of high performance multiprocessor systems is to ensure the correctness of the results computed in the presence of transient and intermittent failures. Concurrent error detection and correction have been applied to such systems in order to achieve reliability. Algorithm Based Fault Tolerance (ABFT) was suggested as a cost-effective concurrent error detection scheme. The research was motivated by the complexity involved in the analysis and design of ABFT systems. To that end, a matrix-based model was developed and, based on that, algorithms for both the design and analysis of ABFT systems are formulated. These algorithms are less complex than the existing ones. In order to reduce the complexity further, a hierarchical approach is developed for the analysis of large systems.

Nair, V. S. Sukumaran↗

NASA NTRS1982

Sensitivity of the boundary layer energy fluxes to forcing parameters in a simple climate model

Winter and summer surface temperatures and time-averaged boundary layer energy fluxes are calculated by utilizing the Saltzman-Ashe parameterization for boundary layer fluxes in a two-level static model. The results are found to agree with observed patterns. Within the framework of this simple model, sensitivity analyses of the time-averaged boundary layer energy fluxes are conducted. Based on these results some of the forcing parameters (such as the subsurface temperature, cloud cover, surface albedo, etc.) are arranged in a hierarchical order of importance. A generalized method of sensitivity analysis is also suggested.

Rao, M. S.↗

NASA NTRS1987

Real-time hierarchically distributed processing network interaction simulation

The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.

Zimmerman, W. F.↗

NASA NTRS1993

The three-point function as a probe of models for large-scale structure

The consequences of models of structure formation for higher-order (n-point) galaxy correlation functions in the mildly non-linear regime are analyzed. Several variations of the standard Omega = 1 cold dark matter model with scale-invariant primordial perturbations were recently introduced to obtain more power on large scales, R(sub p) is approximately 20 h(sup -1) Mpc, e.g., low-matter-density (non-zero cosmological constant) models, 'tilted' primordial spectra, and scenarios with a mixture of cold and hot dark matter. They also include models with an effective scale-dependent bias, such as the cooperative galaxy formation scenario of Bower, etal. It is shown that higher-order (n-point) galaxy correlation functions can provide a useful test of such models and can discriminate between models with true large-scale power in the density field and those where the galaxy power arises from scale-dependent bias: a bias with rapid scale-dependence leads to a dramatic decrease of the hierarchical amplitudes Q(sub J) at large scales, r is approximately greater than R(sub p). Current observational constraints on the three-point amplitudes Q(sub 3) and S(sub 3) can place limits on the bias parameter(s) and appear to disfavor, but not yet rule out, the hypothesis that scale-dependent bias is responsible for the extra power observed on large scales.

Frieman, Joshua A.↗

NASA NTRS1994

Design for dependability: A simulation-based approach

This research addresses issues in simulation-based system level dependability analysis of fault-tolerant computer systems. The issues and difficulties of providing a general simulation-based approach for system level analysis are discussed and a methodology that address and tackle these issues is presented. The proposed methodology is designed to permit the study of a wide variety of architectures under various fault conditions. It permits detailed functional modeling of architectural features such as sparing policies, repair schemes, routing algorithms as well as other fault-tolerant mechanisms, and it allows the execution of actual application software. One key benefit of this approach is that the behavior of a system under faults does not have to be pre-defined as it is normally done. Instead, a system can be simulated in detail and injected with faults to determine its failure modes. The thesis describes how object-oriented design is used to incorporate this methodology into a general purpose design and fault injection package called DEPEND. A software model is presented that uses abstractions of application programs to study the behavior and effect of software on hardware faults in the early design stage when actual code is not available. Finally, an acceleration technique that combines hierarchical simulation, time acceleration algorithms and hybrid simulation to reduce simulation time is introduced.

Goswami, Kumar K.↗