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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

The Role of Aerosols on Precipitation Processes

Cloud physics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distribution below the clouds. Therefore, the size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral--bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Tao, Wei-Kuo↗
NASA NTRS2012

The Role of Aerosols on Precipitation Processes: Cloud Resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, the sub-tropics (Florida) and midlatitudes using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CeN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for these cases. It is shown that since the low (CN case produces fewer droplets, larger sizes develop due to greater condensational and collection growth, leading to a broader size spectrum in comparison to the high CCN case. Sensitivity tests were performed to identify the impact of ice processes, radiation and large-scale influence on cloud-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform types). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by cloud processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.

Tao, Wei-Kuo↗
NASA NTRS1992

Estimation of excitation energy of diatomic molecules in expanding nonequilibrium flows

The energy contained in the highly excited vibrational and rotational states in a diatomic gas in a thermochemical nonequilibrium state during expansion is estimated. The estimation is made on the assumption that the populations of the vibrational and rotational states, when normalized by their respective equilibrium values, are describable by simple functions containing no more than four arbitrary parameters. A cubic polynomial, a logarithmic-cubic polynomial, and a bimodal step function are used for this purpose. The four parameters are determined by imposing conditions known at the ground state and the dissociation limit and the mass conservation law. The energy in excess of that accounted for by assuming a Boltzmann distribution of these states, defined here as excess excitation energy, is calculated for N2, O2, NO, CO, OH, and H2. A calculation made for a typical nozzle flow shows that the excess energy may reach 6 percent of the total enthalpy of the flow, and that the flow velocity may decrease by as much as 4 percent due to the nonequilibrium excitation phenomenon.

Park, Chul↗
NASA NTRS1984

Rational-spline approximation with automatic tension adjustment

An algorithm for weighted least-squares approximation with rational splines is presented. A rational spline is a cubic function containing a distinct tension parameter for each interval defined by two consecutive knots. For zero tension, the rational spline is identical to a cubic spline; for very large tension, the rational spline is a linear function. The approximation algorithm incorporates an algorithm which automatically adjusts the tension on each interval to fulfill a user-specified criterion. Finally, an example is presented comparing results of the rational spline with those of the cubic spline.

Schiess, J. R.↗
NASA NTRS1987

ENO schemes with subcell resolution

The notion is introduced of subcell distribution, which is based on the observation that unlike point values, cell-averages of a discontinuous piecewise-smooth function contain information about the exact location of the discontinuity within the cell. Using this observation an essentially non-oscillatory (ENO) reconstruction technique is designed which is exact for cell averages of discontinuous piecewise-polynomial functions of the appropriate degree. Later on this new reconstruction technique is incorporated into Godunov-type schemes in order to produce a modification of the ENO schemes which prevents the smearing of contact discontinuities.

Harten, Ami↗
NASA NTRS1989

ENO schemes with subcell resolution

The notion is introduced of subcell distribution, which is based on the observation that unlike point values, cell-averages of a discontinuous piecewise-smooth function contain information about the exact location of the discontinuity within the cell. Using this observation, an essentially non-oscillatory (ENO) reconstruction technique is designed which is exact for cell averages of discontinuous piecewise-polynomial functions of the appropriate degree. Later on this new reconstruction technique is incorporated into Godunov-type schemes in order to produce a modification of the ENO schemes which prevents the smearing of contact discontinuities.

Harten, Ami↗
NASA NTRS1991

A new method for simulating atmospheric turbulence for rotorcraft applications

Simulation of atmospheric turbulence as seen by a rotating blade element involves treatment of cyclostationary processes. Conventional filtering techniques do not lend themselves well to the generation of such turbulence sample functions as are required in rotorcraft flight dynamics simulation codes. A method to generate sample functions containing second order statistics of mean and covariance is presented. Compared to ensemble averaging involving excessive computer time, the novelty is to exploit cycloergodicity and thereby, replace ensemble averaging by averaging over a single path sample function of long duration. The method is validated by comparing its covariance results with the analytical and ensemble averaged results for a widely used 1-D turbulence approximation.

J. Riaz↗
NASA NTRS2003

Modelling protein functional domains in signal transduction using Maude

Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.

Signal Transduction↗
NASA NTRS1991

A new method for simulating atmospheric turbulence for rotorcraft applications

Simulation of atmospheric turbulence as seen by a rotating blade element involves treatment of cyclostationary processes. Conventional filtering techniques do not lend themselves well to the generation of such turbulence sample functions as are required in rotorcraft flight dynamics simulation codes. A method to generate sample functions containing second-order statistics of mean and covariance is presented. Compared to ensemble averaging involving excessive computer time, the novelty is to exploit cycloergodicity and thereby, replace ensemble averaging by averaging over a single-path sample function of long duration. The method is validated by comparing its covariance results with the analytical and ensemble-averaged results for a widely used one-dimensional turbulence approximation.

Prasad, J. V. R.↗
NASA NTRS2005

Development of Carbon-Nanotube/Polymer Composites

A report presents a short discussion of one company's effort to develop composites of carbon nanotubes in epoxy and other polymer matrices. The focus of the discussion is on the desirability of chemically modifying carbon nanotubes to overcome their inherent chemical nonreactivity and thereby enable the formation of strong chemical bonds between nanotubes and epoxies (or other polymeric matrix materials or their monomeric precursors). The chemical modification is effected in a process in which discrete functional groups are covalently attached to the nanotube surfaces. The functionalization process was proposed by the company and demonstrated in practice for the first time during this development effort. The covalently attached functional groups are capable of reacting with the epoxy or other matrix resin to form covalent bonds. Furthermore, the company uses this process to chemically modify the nanotube surfaces, affording tunable adhesion to polymers and solubility in select solvents. Flat-sheet composites containing functionalized nanotubes demonstrate significantly improved mechanical, thermal, and electrical properties.

Reynolds, Thomas A.↗
NASA NTRS1986

Necessary conditions for maximax problems with application to aeroglide of hypervelocity vehicles

This paper presents the necessary conditions for solving Chebyshev minimax (or maximax) problems with bounded control. The jump conditions obtained are applicable to problems with single or multiple maxima. By using Contensou domain of maneuverability, it is shown that when the maxima are isolated single points the control is generally continuous at the jump point in the minimax problems and discontinuous in the maximax problems in which the first time derivative of the maximax function contains the control variable. The theory is applied to the problem of maximizing the flight radius in a closed circuit glide of a hypervelocity vehicle and to a maximax optimal control problem in which the control appears explicitly with the first time derivative of the maximax function.

Vinh, N. X.↗
NASA NTRS1995

MPI-IO: A Parallel File I/O Interface for MPI Version 0.3

Thanks to MPI [9], writing portable message passing parallel programs is almost a reality. One of the remaining problems is file I/0. Although parallel file systems support similar interfaces, the lack of a standard makes developing a truly portable program impossible. Further, the closest thing to a standard, the UNIX file interface, is ill-suited to parallel computing. Working together, IBM Research and NASA Ames have drafted MPI-I0, a proposal to address the portable parallel I/0 problem. In a nutshell, this proposal is based on the idea that I/0 can be modeled as message passing: writing to a file is like sending a message, and reading from a file is like receiving a message. MPI-IO intends to leverage the relatively wide acceptance of the MPI interface in order to create a similar I/0 interface. The above approach can be materialized in different ways. The current proposal represents the result of extensive discussions (and arguments), but is by no means finished. Many changes can be expected as additional participants join the effort to define an interface for portable I/0. This document is organized as follows. The remainder of this section includes a discussion of some issues that have shaped the style of the interface. Section 2 presents an overview of MPI-IO as it is currently defined. It specifies what the interface currently supports and states what would need to be added to the current proposal to make the interface more complete and robust. The next seven sections contain the interface definition itself. Section 3 presents definitions and conventions. Section 4 contains functions for file control, most notably open. Section 5 includes functions for independent I/O, both blocking and nonblocking. Section 6 includes functions for collective I/O, both blocking and nonblocking. Section 7 presents functions to support system-maintained file pointers, and shared file pointers. Section 8 presents constructors that can be used to define useful filetypes (the role of filetypes is explained in Section 2 below). Section 9 presents how the error handling mechanism of MPI is supported by the MPI-IO interface. All this is followed by a set of appendices, which contain information about issues that have not been totally resolved yet, and about design considerations. The reader can find there the motivation behind some of our design choices. More information on this would definitely be welcome and will be included in a further release of this document. The first appendix contains a description of MPI-I0's 'hints' structure which is used when opening a file. Appendix B is a discussion of various issues in the support for file pointers. Appendix C explains what we mean in talking about atomic access. Appendix D provides detailed examples of filetype constructors, and Appendix E contains a collection of arguments for and against various design decisions.

Corbett, Peter↗
NASA NTRS1993

Overview of the Systems Special Investigation Group investigation

The Long Duration Exposure Facility (LDEF) carried a remarkable variety of electrical, mechanical, thermal, and optical systems, subsystems, and components. Nineteen of the fifty-seven experiments flown on LDEF contained functional systems that were active on-orbit. Almost all of the other experiments possessed at least a few specific components of interest to the Systems Special Investigation Group (Systems SIG), such as adhesives, seals, fasteners, optical components, and thermal blankets. Almost all top level functional testing of the active LDEF and experiment systems has been completed. Failure analysis of both LDEF hardware and individual experiments that failed to perform as designed has also been completed. Testing of system components and experimenter hardware of interest to the Systems SIG is ongoing. All available testing and analysis results were collected and integrated by the Systems SIG. An overview of our findings is provided. An LDEF Optical Experiment Database containing information for all 29 optical related experiments is also discussed.

Mason, James B.↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗
NASA NTRS1981

Flammability and Photo-Stability of Selected Polymer Systems

A systematic approach to the improvement of the flammability of epoxy resins, bisphenol-A polycarbonate poly(butylene terephthalate), and Nylon 6.6 by introducing halogens and loop functionality into the flame retardants is described. The phthalides (the loop functionality containing molecules) include 3,3-bis(4-bromophenyl)-phthalide, 3,3-bis(4-chlorophenyl)phthalide, and phenolphthalein. The phthalide containing epoxy resins are synthesized and characterized in comparison with the bisphenol-A epoxy resins in terms of flammability in the copolymer systems. The resins include diglycidyl ethers of phenolphthalein, bisphenol-A. tetrabromobisphenol-A, and tetraoromophenolphthalein. The vaporization of the phthalide additive in the polymers is observed in Thermal Gravimetric Analysis. The flame retardancy is primarily due to the presence of halogens. In the poly(butylene terephthalate) system, the cleavage of the C(sub aromatic) -B bond of the flame retardant additive enhances the crosslinking react ions between the aromatic rings resulting in an increase of char formation. In the epoxy resin systems, loop functionality contributes to char formation to a larger extent. The interaction between the epoxy resin and poly-(butylene terephthalate) follows the mechanism of insertion of the oxirane ring into the ester bond. This mechanism is studied by FT-IR. The investigation of the thermal properties of the char-forming phenol-formaldehyde resins is conducted to provide information for the systematic design of high temperature flame-resistant phenolics. NMR and FT-IR are used to characterize the oligomeric resins and the cured resins. The curing agents used in the study include formaldehyde, s-trioxane and terephthaloyl chloride. The brominated phenolic resins are found to have higher oxygen indices with lower char yields.

Lo, Jeelin↗
NASA NTRS1973

The scattering of low energy positrons by helium

Kohn's variational method is used to calculate the positron-helium scattering length and low energy S-wave phase shifts for a quite realistic Hylleraas type of helium function containing an electron-electron correlation term. The zero energy wavefunction is used to calculate the value of the annihilation rate parameter Z sub eff. All the results are significantly different from those for Drachman's helium model B, but are in better agreement with the available experimental data.

Humberston, J. W.↗