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At least 217 records · Page 12

Mathematical model partitioning and packing for parallel computer calculation

This paper deals with the development of multiprocessor simulations from a serial set of ordinary differential equations describing a physical system. The identification of computational parallelism within the model equations is discussed. A technique is presented for identifying this parallelism and for partitioning the equations for parallel solution on a multiprocessor. Next, an algorithm which packs the equations into a minimum number of processors is described. The results of applying the packing algorithm to a turboshaft engine model are presented.

Arpasi, Dale J.↗

Plant and Animal Gravitational Biology

Session TA2 includes short reports covering: (1) The Interaction of Microgravity and Ethylene on Soybean Growth and Metabolism; (2) Structure and G-Sensitivity of Root Statocytes under Different Mass Acceleration; (3) Extracellular Production of Taxanes on Cell Surfaces in Simulated Microgravity and Hypergravity; (4) Current Problems of Space Cell Phytobiology; (5) Biological Consequences of Microgravity-Induced Alterations in Water Metabolism of Plant Cells; (6) Localization of Calcium Ions in Chlorella Cells Under Clinorotation; (7) Changes of Fatty Acids Content of Plant Cell Plasma Membranes under Altered Gravity; (8) Simulation of Gravity by Non-Symmetrical Vibrations and Ultrasound; and (9) Response to Simulated weightlessness of In Vitro Cultures of Differentiated Epithelial Follicular Cells from Thyroid.

Source record↗

A Probabilistic Framework for the Validation and Certification of Computer Simulations

The paper presents a methodology for quantifying, propagating, and managing the uncertainty in the data required to initialize computer simulations of complex phenomena. The purpose of the methodology is to permit the quantitative assessment of a certification level to be associated with the predictions from the simulations, as well as the design of a data acquisition strategy to achieve a target level of certification. The value of a methodology that can address the above issues is obvious, specially in light of the trend in the availability of computational resources, as well as the trend in sensor technology. These two trends make it possible to probe physical phenomena both with physical sensors, as well as with complex models, at previously inconceivable levels. With these new abilities arises the need to develop the knowledge to integrate the information from sensors and computer simulations. This is achieved in the present work by tracing both activities back to a level of abstraction that highlights their commonalities, thus allowing them to be manipulated in a mathematically consistent fashion. In particular, the mathematical theory underlying computer simulations has long been associated with partial differential equations and functional analysis concepts such as Hilbert spares and orthogonal projections. By relying on a probabilistic framework for the modeling of data, a Hilbert space framework emerges that permits the modeling of coefficients in the governing equations as random variables, or equivalently, as elements in a Hilbert space. This permits the development of an approximation theory for probabilistic problems that parallels that of deterministic approximation theory. According to this formalism, the solution of the problem is identified by its projection on a basis in the Hilbert space of random variables, as opposed to more traditional techniques where the solution is approximated by its first or second-order statistics. The present representation, in addition to capturing significantly more information than the traditional approach, facilitates the linkage between different interacting stochastic systems as is typically observed in real-life situations.

Ghanem, Roger↗

Latitudinal Transport of Angular Momentum by Cellular Flows Observed with MDI

We have analyzed Doppler velocity images from the MDI instrument on SOHO to determine the latitudinal transport of angular momentum by the cellular photospheric flows. Doppler velocity images from 60-days in May to July of 1996 were processed to remove the p-mode oscillations, the convective blue shift, the axisymmetric flows, and any instrumental artifacts. The remaining cellular flows were examined for evidence of latitudinal angular momentum transport. Small cells show no evidence of any such transport. Cells the size of supergranules (30,000 km in diameter) show strong evidence for a poleward transport of angular momentum. This would be expected if supergranules are influenced by the Coriolis force, and if the cells are elongated in an east-west direction. We find good evidence for just such an east-west elongation of the supergranules. This elongation may be the result of differential rotation shearing the cellular structures. Data simulations of this effect support the conclusion that elongated supergranules transport angular momentum from the equator toward the poles, Cells somewhat larger than supergranules do not show evidence for this poleward transport. Further analysis of the data is planned to determine if the direction of angular momentum transport reverses for even larger cellular structures. The Sun's rapidly rotating equator must be maintained by such transport somewhere within the convection zone.

Hathaway, David H.↗

Field-Programmable Gate Array Computer in Structural Analysis: An Initial Exploration

This paper reports on an initial assessment of using a Field-Programmable Gate Array (FPGA) computational device as a new tool for solving structural mechanics problems. A FPGA is an assemblage of binary gates arranged in logical blocks that are interconnected via software in a manner dependent on the algorithm being implemented and can be reprogrammed thousands of times per second. In effect, this creates a computer specialized for the problem that automatically exploits all the potential for parallel computing intrinsic in an algorithm. This inherent parallelism is the most important feature of the FPGA computational environment. It is therefore important that if a problem offers a choice of different solution algorithms, an algorithm of a higher degree of inherent parallelism should be selected. It is found that in structural analysis, an 'analog computer' style of programming, which solves problems by direct simulation of the terms in the governing differential equations, yields a more favorable solution algorithm than current solution methods. This style of programming is facilitated by a 'drag-and-drop' graphic programming language that is supplied with the particular type of FPGA computer reported in this paper. Simple examples in structural dynamics and statics illustrate the solution approach used. The FPGA system also allows linear scalability in computing capability. As the problem grows, the number of FPGA chips can be increased with no loss of computing efficiency due to data flow or algorithmic latency that occurs when a single problem is distributed among many conventional processors that operate in parallel. This initial assessment finds the FPGA hardware and software to be in their infancy in regard to the user conveniences; however, they have enormous potential for shrinking the elapsed time of structural analysis solutions if programmed with algorithms that exhibit inherent parallelism and linear scalability. This potential warrants further development of FPGA-tailored algorithms for structural analysis.

Singleterry, Robert C., Jr.↗

A Global Model of Meteoric Sodium

A global model of sodium in the mesosphere and lower thermosphere has been developed within the framework of the National Center for Atmospheric Research's Whole Atmosphere Community Climate Model (WACCM). The standard fully interactive WACCM chemistry module has been augmented with a chemistry scheme that includes nine neutral and ionized sodium species. Meteoric ablation provides the source of sodium in the model and is represented as a combination of a meteoroid input function (MIF) and a parameterized ablation model. The MIF provides the seasonally and latitudinally varying meteoric flux which is modeled taking into consideration the astronomical origins of sporadic meteors and considers variations in particle entry angle, velocity, mass, and the differential ablation of the chemical constituents. WACCM simulations show large variations in the sodium constituents over time scales from days to months. Seasonality of sodium constituents is strongly affected by variations in the MIF and transport via the mean meridional wind. In particular, the summer to winter hemisphere flow leads to the highest sodium species concentrations and loss rates occurring over the winter pole. In the Northern Hemisphere, this winter maximum can be dramatically affected by stratospheric sudden warmings. Simulations of the January 2009 major warming event show that it caused a short-term decrease in the sodium column over the polar cap that was followed by a factor of 3 increase in the following weeks. Overall, the modeled distribution of atomic sodium in WACCM agrees well with both ground-based and satellite observations. Given the strong sensitivity of the sodium layer to dynamical motions, reproducing its variability provides a stringent test of global models and should help to constrain key atmospheric variables in this poorly sampled region of the atmosphere.

meteoric flux↗

Uncertainty Quantification using Deep Ensembles for Decision Making in Cyber-Physical-Human Systems

In this paper and its companion, Differential Equation Approximation Using Gradient-Boosted Quantile Regression, Robison et al., we examine an approach to quantifying model uncertainty with the aim of increasing the trustworthiness of computational models in human-machine interactions. In Differential Equation Approximation Using Gradient-Boosted Quantile Regression, we focus on gradient-boosted decision trees, while in this one, we give more details about deep ensembles. Uncertainty quantification is crucial for building trustworthy autonomous decision-making agents in human-machine teams. There are two types of uncertainties: aleatoric and epistemic. The former is related to the inherent stochasticity (noise) of the process, whereas the latter is associated with the lack of knowledge or representation capability of models, such as neural networks. By lack of knowledge, we mean the model’s inability to accurately predict outputs for all possible inputs. The aleatory uncertainty can be estimated fairly easily with, for example, filters, whereas epistemic uncertainty is challenging to compute. This paper uses deep ensembles to quantify both aleatory and epistemic uncertainty. It can act as an uncertainty-aware surrogate transition model for decision-making frameworks. "Uncertainty-aware" means that the surrogate transition model should make predictions along with confidence in those predictions. In the context of decision-making, the transition models are ordinary differential equations (ODEs). Since ODEs can be simulated to make one-step or multi-step predictions, a good surrogate model for them should perform reasonably well in both modes. In a multi-step approach, the trajectory sampling method TS∞ was used to propagate uncertainty over multiple steps. The cartpole dynamical system was selected to demonstrate the ability of deep ensembles as good surrogate transition models for decision-making frameworks. The deep ensembles modeled the dynamics of cartpole ODEs and made uncertainty-aware predictions in single-step and multi-step transition modes.

CPH systems↗

Inductive Learning Approaches for Improving Pilot Awareness of Aircraft Faults

Neural network flight controllers are able to accommodate a variety of aircraft control surface faults without detectable degradation of aircraft handling qualities. Under some faults, however, the effective flight envelope is reduced; this can lead to unexpected behavior if a pilot performs an action that exceeds the remaining control authority of the damaged aircraft. The goal of our work is to increase the pilot s situational awareness by informing him of the type of damage and resulting reduction in flight envelope. Our methodology integrates two inductive learning systems with novel visualization techniques. One learning system, the Inductive Monitoring System (IMS), learns to detect when a simulation includes faulty controls, while two others, Inductive Classification System (INCLASS) and multiple binary decision tree system (utilizing C4.5), determine the type of fault. In off-line training using only non-failure data, IMS constructs a characterization of nominal flight control performance based on control signals issued by the neural net flight controller. This characterization can be used to determine the degree of control augmentation required in the pitch, roll, and yaw command channels to counteract control surface failures. This derived information is typically sufficient to distinguish between the various control surface failures and is used to train both INCLASS and C4.5. Using data from failed control surface flight simulations, INCLASS and C4.5 independently discover and amplify features in IMS results that can be used to differentiate each distinct control surface failure situation. In real-time flight simulations, distinguishing features learned during training are used to classify control surface failures. Knowledge about the type of failure can be used by an additional automated system to alter its approach for planning tactical and strategic maneuvers. The knowledge can also be used directly to increase the pilot s situational awareness and inform manual maneuver decisions. Our multi-modal display of this information provides speech output to issue control surface failure warnings to a lesser-used communication channel and provides graphical displays with pilot-selectable !eve!s of details to issues additional information about the failure. We also describe a potential presentation for flight envelope reduction that can be viewed separately or integrated with an existing attitude indicator instrument. Preliminary results suggest that the inductive approach is capable of detecting that a control surface has failed and determining the type of fault. Furthermore, preliminary evaluations suggest that the interface discloses a concise summary of this information to the pilot.

Spikovska, Lilly↗

A study of the application of differential techniques to the global positioning system for a helicopter precision approach

The results of a simulation study to define the functional characteristics of a airborne and ground reference GPS receiver for use in a Differential GPS system are doumented. The operations of a variety of receiver types (sequential-single channel, continuous multi-channel, etc.) are evaluated for a typical civil helicopter mission scenario. The math model of each receiver type incorporated representative system errors including intentional degradation. The results include the discussion of the receiver relative performance, the spatial correlative properties of individual range error sources, and the navigation algorithm used to smooth the position data.

Mccall, D. L.↗

Clinical Outcome Metrics for Optimization of Robust Training

Introduction: The emphasis of this research is on the Human Research Program (HRP) Exploration Medical Capability's (ExMC) "Risk of Unacceptable Health and Mission Outcomes Due to Limitations of In-Flight Medical Capabilities." Specifically, this project aims to contribute to the closure of gap ExMC 2.02: We do not know how the inclusion of a physician crew medical officer quantitatively impacts clinical outcomes during exploration missions. The experiments are specifically designed to address clinical outcome differences between physician and non-physician cohorts in both near-term and longer-term (mission impacting) outcomes. Methods: Medical simulations will systematically compare success of individual diagnostic and therapeutic procedure simulations performed by physician and non-physician crew medical officer (CMO) analogs using clearly defined short-term (individual procedure) outcome metrics. In the subsequent step of the project, the procedure simulation outcomes will be used as input to a modified version of the NASA Integrated Medical Model (IMM) to analyze the effect of the outcome (degree of success) of individual procedures (including successful, imperfectly performed, and failed procedures) on overall long-term clinical outcomes and the consequent mission impacts. The procedures to be simulated are endotracheal intubation, fundoscopic examination, kidney/urinary ultrasound, ultrasound-guided intravenous catheter insertion, and a differential diagnosis exercise. Multiple assessment techniques will be used, centered on medical procedure simulation studies occurring at 3, 6, and 12 months after initial training (as depicted in the following flow diagram of the experiment design). Discussion: Analysis of procedure outcomes in the physician and non-physician groups and their subsets (tested at different elapsed times post training) will allow the team to 1) define differences between physician and non-physician CMOs in terms of both procedure performance (pre-IMM analysis) and overall mitigation of the mission medical impact (IMM analysis); 2) refine the procedure outcome and clinical outcome metrics themselves; 3) refine or develop innovative medical training products and solutions to maximize CMO performance; and 4) validate the methods and products of this experiment for operational use in the planning, execution, and quality assurance of the CMO training process The team has finalized training protocols and developed a software training/testing tool in collaboration with Butler Graphics (Detroit, MI). In addition to the "hands on" medical procedure modules, the software includes a differential diagnosis exercise (limited clinical decision support tool) to evaluate the diagnostic skills of participants. Human subject testing will occur over the next year.

Ebert, D.↗

Differentiation of mammalian skeletal muscle cells cultured on microcarrier beads in a rotating cell culture system

The growth and repair of adult skeletal muscle are due in part to activation of muscle precursor cells, commonly known as satellite cells or myoblasts. These cells are responsive to a variety of environmental cues, including mechanical stimuli. The overall goal of the research is to examine the role of mechanical signalling mechanisms in muscle growth and plasticity through utilisation of cell culture systems where other potential signalling pathways (i.e. chemical and electrical stimuli) are controlled. To explore the effects of decreased mechanical loading on muscle differentiation, mammalian myoblasts are cultured in a bioreactor (rotating cell culture system), a model that has been utilised to simulate microgravity. C2C12 murine myoblasts are cultured on microcarrier beads in a bioreactor and followed throughout differentiation as they form a network of multinucleated myotubes. In comparison with three-dimensional control cultures that consist of myoblasts cultured on microcarrier beads in teflon bags, myoblasts cultured in the bioreactor exhibit an attenuation in differentiation. This is demonstrated by reduced immunohistochemical staining for myogenin and alpha-actinin. Western analysis shows a decrease, in bioreactor cultures compared with control cultures, in levels of the contractile proteins myosin (47% decrease, p < 0.01) and tropomyosin (63% decrease, p < 0.01). Hydrodynamic measurements indicate that the decrease in differentiation may be due, at least in part, to fluid stresses acting on the myotubes. In addition, constraints on aggregate size imposed by the action of fluid forces in the bioreactor affect differentiation. These results may have implications for muscle growth and repair during spaceflight.

Non-NASA Center↗

A Space Station/Payload Pointing System simulation using TREETOPS

A rigid body model of NASA's Space Station (SS)/Payload Pointing System (PPS) was built and simulated using the multibody, large angle simulation package TREETOPS, whose name refers to the tree-topology class of structures that may be simulated. SS/PPS data from a previous feasibility study utilizing the MultiOptimal Differential Equation language was used as a test case to evaluate the built-in dynamical formulation capabilities of TREETOPS. The simulation results showed close agreement with NASA-Goddard data, demonstrating the validity of the nonlinear, large angle, multi-degree of freedom TREETOPS model.

Ram, Mohan↗

The combustion program at CTR

Understanding and modeling of turbulent combustion are key problems in the computation of numerous practical systems. Because of the lack of analytical theories in this field and of the difficulty of performing precise experiments, direct numerical simulation (DNS) appears to be one of the most attractive tools to use in addressing this problem. The general objective of DNS of reacting flows is to improve our knowledge of turbulent combustion but also to use this information for turbulent combustion models. For the foreseeable future, numerical simulation of the full three-dimensional governing partial differential equations with variable density and transport properties as well as complex chemistry will remain intractable; thus, various levels of simplification will remain necessary. On one hand, the requirement to simplify is not necessarily a handicap: numerical simulations allow the researcher a degree of control in isolating specific physical phenomena that is inaccessible in experiments. CTR has pursued an intensive research program in the field of DNS for turbulent reacting flows since 1987. DNS of reacting flows is quite different from DNS of non-reacting flows: without reaction, the equations to solve are clearly the five conservation equations of the Navier Stokes system for compressible situations (four for incompressible cases), and the limitation of the approach is the Reynolds number (or in other words the number of points in the computation). For reacting flows, the choice of the equations, the species (each species will require one additional conservation equation), the chemical scheme, and the configuration itself is more complex.

Poinsot, Thierry J.↗

Numerical Study of Buoyancy and Differential Diffusion Effects on the Structure and Dynamics of Triple Flames

Triple flames arise in a number of practical configurations where fuel and oxidizer are partially premixed, such as in the base of a lifted jet flame. Past experimental studies, theoretical analyses, and numerical modeling of triple flames suggested the potential role of triple flames in stabilizing turbulent flames and in promoting flame propagation. From recent numerical simulations of laminar triple flames, a strong influence of differential diffusion among species and heat on the triple flame structure has been gradually appreciated. This paper reports preliminary numerical results on the influence of gravity and differential diffusion effects on the structure and dynamics of triple flames with a one-step global irreversible chemistry model.

Chen, J. -Y.↗

Double-Pulse Two-Micron IPDA Lidar Simulation for Airborne Carbon Dioxide Measurements

An advanced double-pulsed 2-micron integrated path differential absorption lidar has been developed at NASA Langley Research Center for measuring atmospheric carbon dioxide. The instrument utilizes a state-of-the-art 2-micron laser transmitter with tunable on-line wavelength and advanced receiver. Instrument modeling and airborne simulations are presented in this paper. Focusing on random errors, results demonstrate instrument capabilities of performing precise carbon dioxide differential optical depth measurement with less than 3% random error for single-shot operation from up to 11 km altitude. This study is useful for defining CO2 measurement weighting, instrument setting, validation and sensitivity trade-offs.

Refaat, Tamer F.↗

LIPA: Lunar Ice Perception Algorithm

Introduction: The highest concentration of Lu-nar water-ice stores exists within the Permanently Shadowed Regions (PSRs) of the Lunar South Pole [1-3]. As such, the ability to locate in situ water-ice stores in an accurate, systematic, and safe manner will prove vital for future Lunar activities which rely on hydrogen-based resources. Here we show how the strong absorptive properties of ice can be exploited so that surface ice located in PSRs can be easily differentiated from the surrounding frozen regolith. Testbeds which simulate an icy lunar landscape were created and then systematically imaged using a mid-wave infrared (MWIR) camera system. Testbeds were imaged under two filter modes (1) high-absorption (high-abs) mode: whereby imagery captured were confined to a single central wave-length (CWL) of 3.15 ± 0.03 μm and (2) low-absorption (low-abs) mode: whereby imagery cap-tured were confined to a single CWL of 3.80 ± 0.04 μm (Figure 1). High- and low-absorption modes are related to the absorptive properties of ice at each selected wavelength, respectively. Corresponding images from each filter mode were differenced (i.e., pixels were subtracted) to enhance contrast between ice-bearing and non-ice-bearing pixels, and then fed into a semantic segmen-tation model. The model was trained to detect and differentiate between water, ice, shadows, and lunar regolith. Results: Modeling results accurately discrimi-nated ice from other materials (such as frozen lunar regolith) and were used to visually resolve the spa-tial extent of surface ice. Further, outputs produced through semantic segmentation were used to estimate water-ice contents in collected imagery [(Pixels with Class = “Water Ice”)/(Sum of Pixels)*100]. Summary: These works prove promising for future in situ resource utilization (ISRU) missions which employ robotics in combination with infrared camera systems to advance science objectives (e.g., locate water-ice in frozen regolith) on the lunar sur-face. References: [1] Cannon K. M., Deutsch A. N., Head J. W., and Britt D. T. (2020) Geophysical Re-search Letters, 46, e2020GL088920. [2] Honniball C. I. et al. (2021) Nature Astronomy 5, no. 2, 121-127. [3] Li S. et al. (2018) Proceedings of the National Academy of Sciences, 115(36), 8907-8912.

A. Slabic↗

Sensitivity of a GCM climate simulation to differences in continental versus maritime cloud drop size

Extensive observations indicate a distinct difference between maritime and continental effective drop size, r(sub e), for warm clouds. The latest version of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM2) is used to explore the sensitivity of differentiating between continental and maritime r(sub e) on the simulated climate. The results of this study indicate that the smaller drop size over continents leads to a reduction of surface-absorbed solar radiation from 20 to 60 W/sq m. This reduction in surface solar flux leads to a cooling of the continents by up to -3.5 K. The reduction in surface solar flux and temperature also leads to a reduction in latent heat flux and precipitation over land. In the January simulation, there is a significant shift in tropical precipitation associated with the Australian monsoon. This shift leads to a response in the extra tropical geopotential height field over the western United States. All of these changes reduce biases in the current version of CCM2.

Kiehl, J. T.↗