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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

FDNS CFD Code Benchmark for RBCC Ejector Mode Operation

Computational Fluid Dynamics (CFD) analysis results are compared with benchmark quality test data from the Propulsion Engineering Research Center's (PERC) Rocket Based Combined Cycle (RBCC) experiments to verify fluid dynamic code and application procedures. RBCC engine flowpath development will rely on CFD applications to capture the multi-dimensional fluid dynamic interactions and to quantify their effect on the RBCC system performance. Therefore, the accuracy of these CFD codes must be determined through detailed comparisons with test data. The PERC experiments build upon the well-known 1968 rocket-ejector experiments of Odegaard and Stroup by employing advanced optical and laser based diagnostics to evaluate mixing and secondary combustion. The Finite Difference Navier Stokes (FDNS) code was used to model the fluid dynamics of the PERC RBCC ejector mode configuration. Analyses were performed for both Diffusion and Afterburning (DAB) and Simultaneous Mixing and Combustion (SMC) test conditions. Results from both the 2D and the 3D models are presented.

Holt, James B.↗
NASA NTRS2020

Formal Verification of a Solution to the n-Queens Problem

This report describes a formal verification of a concise algorithm that computes a solution to the n-Queens problem for all natural numbers n, such that n > 3. The formal proof of the algorithm is completed in the Prototype Verification System (PVS) theorem prover. This verification effort serves two purposes. First, it is presented as a pedagogical example for learning a theorem prover, such as PVS, and second, as a candidate benchmark for comparing other formal methods tools to PVS.

Mahyar R Malekpour↗
NASA NTRS1989

SSME LOX post flow analysis/fluid structure interaction. Volume 2: Fluid structure interaction

The progress made in resolving the computational issues associated with modeling high temperature and pressure viscous flows in advanced propulsion systems is documented. An overview of adaptive computational methods for various classes of fluid-structure interaction problems is presented. The key features associated with several approaches are outlined and the advantages/disadvantages of each are summarized. A mathematical formulation is presented for general fluid-structure interaction problems with a moving domain. The two adaptive approaches are discussed used in solving the benchmark problems. The first scheme is a user interactive scheme which is quite versatile and easy to implement but requires an excessive amount of monitoring by the operator and is computationally inefficient. The second method is a new, local remeshing method for handling a general class of fluid-structure interaction problems. This method couples many of the attractive features of other approaches into a computationally efficient and versatile method. The results obtained for two test cases are presented. Results from both the user interactive and local remeshing procedure are described. The current status of the project and future goals to be completed are summarized.

Source record↗
NASA NTRS2015

Adaptive Shape Control for Aerodynamic Design

We present an approach to aerodynamic optimization in which the shape control is adaptively parameterized. Starting from a coarse set of design variables, a sequence of higher-dimensional nested search spaces is automatically generated. Refinement can be either uniform or adaptive, in which case only the most important shape control is added. The relative importance of candidate design variables is determined by comparing objective and constraint gradients, computed at low cost via adjoint solutions. A search procedure for finding an effective ensemble of shape parameters is also given. We first demonstrate this system on a multipoint drag miminization problem in 2D with many constraints, showing that an adaptive parameterization approach consistently achieves smoother, more robust, and faster design improvement than fixed parameterizations. We also establish a 3D shape- matching benchmark, where we demonstrate that our approach automatically discovers the necessary parameters to match a target shape. By largely automating shape parameterization, this work also aims to remove a time-consuming aspect of shape optimization.

Aerodynamic Design↗
NASA NTRS1986

A performance comparison of the Cray-2 and the Cray X-MP

A suite of thirteen large Fortran benchmark codes were run on Cray-2 and Cray X-MP supercomputers. These codes were a mix of compute-intensive scientific application programs (mostly Computational Fluid Dynamics) and some special vectorized computation exercise programs. For the general class of programs tested on the Cray-2, most of which were not specially tuned for speed, the floating point operation rates varied under a variety of system load configurations from 40 percent up to 125 percent of X-MP performance rates. It is concluded that the Cray-2, in the original system configuration studied (without memory pseudo-banking) will run untuned Fortran code, on average, about 70 percent of X-MP speeds.

Schmickley, Ronald↗
NASA NTRS1992

A low-cost vector processor boosting compute-intensive image processing operations

Low-cost vector processing (VP) is within reach of everyone seriously engaged in scientific computing. The advent of affordable add-on VP-boards for standard workstations complemented by mathematical/statistical libraries is beginning to impact compute-intensive tasks such as image processing. A case in point in the restoration of distorted images from the Hubble Space Telescope. A low-cost implementation is presented of the standard Tarasko-Richardson-Lucy restoration algorithm on an Intel i860-based VP-board which is seamlessly interfaced to a commercial, interactive image processing system. First experience is reported (including some benchmarks for standalone FFT's) and some conclusions are drawn.

Adorf, Hans-Martin↗
NASA NTRS1990

Combined AIE/EBE/GMRES approach to incompressible flows

Adaptive implicit-explicit (AIE), grouped element-by-element (GEBE), and generalized minimum residuals (GMRES) solution techniques for incompressible flows are combined. In this approach, the GEBE and GMRES iteration methods are employed to solve the equation systems resulting from the implicitly treated elements, and therefore no direct solution effort is involved. The benchmarking results demonstrate that this approach can substantially reduce the CPU time and memory requirements in large-scale flow problems. Although the description of the concepts and the numerical demonstration are based on the incompressible flows, the approach presented here is applicable to larger class of problems in computational mechanics.

Liou, J.↗
NASA NTRS2004

Experimentation Toward the Analysis of Gear Noise Sources Controlled by Sliding Friction and Surface Roughness

In helicopters and other rotorcraft, the gearbox is a major source of noise and vibration (N&V). The two N&V excitation mechanisms are the relative displacements between mating gears (transmission errors) and the friction associated with sliding between gear teeth. Historically, transmission errors have been minimized via improved manufacturing accuracies and tooth modifications. Yet, at high torque loads, noise levels are still relatively high though transmission errors might be somewhat minimal. This suggests that sliding friction is indeed a dominant noise source for high power density rotorcraft gearboxes. In reality, friction source mechanism is associated with surface roughness, lubrication regime properties, time-varying friction forces/torques and gear-mesh interface dynamics. Currently, the nature of these mechanisms is not well understood, while there is a definite need for analytical tools that incorporate sliding resistance and surface roughness, and predict their effects on the vibro- acoustic behavior of gears. Toward this end, an experiment was conducted to collect sound and vibration data on the NASA Glenn Gear-Noise Rig. Three iterations of the experiment were accomplished: Iteration 1 tested a baseline set of gears to establish a benchmark. Iteration 2 used a gear-set with low surface asperities to reduce the sliding friction excitation. Iteration 3 incorporated low viscosity oil with the baseline set of gears to examine the effect of lubrication. The results from this experiment will contribute to a two year project in collaboration with the Ohio State University to develop the necessary mathematical and computer models for analyzing geared systems and explain key physical phenomena seen in experiments. Given the importance of sliding friction in the gear dynamic and vibro-acoustic behavior of rotorcraft gearboxes, there is considerable potential for research & developmental activities. Better models and understanding will lead to quiet and reliable gear designs, as well as the selection of optimal manufacturing processes.

Asnani, Vivake M.↗
NASA NTRS1998

AAH Cage Out-Link and In-Link Antenna Characterization

This final report encapsulates the accomplishments of the third year of work on an Advanced Biotelemetry System (ABTS). Overall MU/ABTS project objectives are to provide a biotelemetry system that can collect data from and send commands to an implanted biotransceiver. This system will provide for studies of rodent development in space. The system must be capable of operating in a metal animal cage environment. An important goal is the development of a small, "smart", micropower, implantable biotransceiver with eight-channel data output and single channel command input capabilities with the flexibility for easy customization for a variety of physiologic investigations. The NASA Ames/Marquette University Joint Research work has been devoted to the system design of such a new state of the art biotelemetry system, having multiple physiologic inputs, and bi-directional data transfer capabilities. This work has provided a successful prototype system that connects, by two-way radio links, an addressable biotelemetry system that provides communication between an animal biotelemeter prototype and a personal computer. The operational features of the prototype system are: (1) two-way PCM communication with implanted biotelemeter; (2) microcontroller based biotelemeter; (3) out-link: wideband FSK (60 kBaud); (4) in-link: OOK (2.4 kbaud); (5) septum antenna arrays (In/Out-Links); and (6) personal computer data interface. The important requirement of this third year's work, to demonstrate two-way communication with transmit and receive antennas inside the metal animal cage, has been successfully accomplished. The advances discussed in this report demonstrate that the AAH cage antenna system can provide Out-link and In-link capability for the ABTS bi-directional telemetry system, and can serve as a benchmark for project status. Additions and enhancements to the most recent (April 1997) prototype cage and antenna have been implemented. The implementation, testing, and documentation was accomplished at the Biotelemetry Laboratory at Marquette University with Out-Link (slot) antenna design assistance was provided.

Jeutter, Dean C.↗
NASA NTRS1998

AAH Cage Out-Link and In-Link Antenna Characterization

This final report encapsulates the accomplishments of the third year of work on an Advanced Biotelemetry System (ABTS). Overall MU/ABTS project objectives are to provide a biotelemetry system that can collect data from and send commands to an implanted biotransceiver. This system will provide for studies of rodent development in space. The system must be capable of operating in a metal animal cage environment. An important goal is the development of a small, "smart", micropower, -channel data output and single channel command implantable biotransceiver with eight input capabilities with the flexibility for easy customization for a variety of physiologic investigations. The NASA Ames/Marquette University Joint Research work has been devoted to the system design of such a new state of the art biotelemetry system, having multiple physiologic inputs, and bi-directional data transfer capabilities. This work has provided a successful prototype system that connects, by two-way radio links, an addressable biotelemetry system that provides communication between an animal biotelemeter prototype and a personal computer. The operational features of the prototype system are listed below: Two-Way PCM Communication with Implanted Biotelemeter Microcontroller Based Biotelemeter Out-Link: Wideband FSK (60 kbaud) In-Link: OOK (2.4 kbaud) Septum Antenna Arrays (In/Out-Links) Personal Computer Data Interface The important requirement of this third year's work, to demonstrate two-way communication with transmit and receive antennas inside the metal animal cage, has been successfully accomplished. The advances discussed in this report demonstrate that the AAH cage antenna system can provide Out-link and In-link capability for the ABTS bi-directional telemetry system, and can serve as a benchmark for project status.

Jeutter, Dean C.↗
NASA NTRS2002

Structural Analyses of Stirling Power Convertor Heater Head for Long-Term Reliability, Durability, and Performance

Deep-space missions require onboard electric power systems with reliable design lifetimes of up to 10 yr and beyond. A high-efficiency Stirling radioisotope power system is a likely candidate for future deep-space missions and Mars rover applications. To ensure ample durability, the structurally critical heater head of the Stirling power convertor has undergone extensive computational analyses of operating temperatures (up to 650 C), stresses, and creep resistance of the thin-walled Inconel 718 bill of material. Durability predictions are presented in terms of the probability of survival. A benchmark structural testing program has commenced to support the analyses. This report presents the current status of durability assessments.

Halford, Gary R.↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-ofthe-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Hesham ElAbd↗
NASA NTRS2000

Stereo Imaging Velocimetry of Mixing Driven by Buoyancy Induced Flow Fields

Mixing of two fluids generated by steady and particularly g-jitter acceleration is fundamental towards the understanding of transport phenomena in a microgravity environment. We propose to carry out flight and ground-based experiments to quantify flow fields due to g-jitter type of accelerations using Stereo Imaging Velocimetry (SIV), and measure the concentration field using laser fluorescence. The understanding of the effects of g-jitter on transport phenomena is of great practical interest to the microgravity community and impacts the design of experiments for the Space Shuttle as well as the International Space Station. The aim of our proposed research is to provide quantitative data to the community on the effects of g-jitter on flow fields due to mixing induced by buoyancy forces. The fundamental phenomenon of mixing occurs in a broad range of materials processing encompassing the growth of opto-electronic materials and semiconductors, (by directional freezing and physical vapor transport), to solution and protein crystal growth. In materials processing of these systems, crystal homogeneity, which is affected by the solutal field distribution, is one of the major issues. The understanding of fluid mixing driven by buoyancy forces, besides its importance as a topic in fundamental science, can contribute towards the understanding of how solutal fields behave under various body forces. The body forces of interest are steady acceleration and g-jitter acceleration as in a Space Shuttle environment or the International Space Station. Since control of the body force is important, the flight experiment will be carried out on a tunable microgravity vibration isolation mount, which will permit us to precisely input the desired forcing function to simulate a range of body forces. To that end, we propose to design a flight experiment that can only be carried out under microgravity conditions to fully exploit the effects of various body forces on fluid mixing. Recent flight experiments, by the P.I. through collaboration with the Canadian Space Agency (STS-85, August 1997), aimed at determining the stability of the interface between two miscible liquids inside an enclosure show that a long liquid column (5 cm) under microgravity isolation conditions can be stable, i.e. the interface remains sharp and vertical over a short time scale; thus transport occurs by molecular mass diffusion. On the other hand, when the two liquids were excited from a controlled vibration source (Microgravity Vibration Isolation Mount) two to four mode large amplitude quasi-stationary waves were observed. The data was limited to CCD recording of the dynamics of the interface between the two fluids. We propose to carry out flight experiments to quantify the dynamics of the flow field using Stereo Imaging Velocimetry and measure the concentration field using laser fluorescence. The results will serve as a basis to understand effects of g-jitter on transport phenomena, in this case mass diffusion. As the measurement of the kinematics of the flow field will shed light on the instability mechanism. The research will allow measurement of the flow field in microgravity environment to prove two hypotheses: (1) Maxwell's hypothesis: finite convection always exists in diffusing systems, and (2) Quasi-stationary waves inside a bounded enclosure in a microgravity environment is generated by Kelvin-Helmholtz instability; resonance of the interface which produces incipient mixing is due to Rayleigh-Taylor instability. The first hypothesis can be used as a benchmark experiment to illustrate diffusive mixing. The second hypothesis will lead to the understanding of g-jitter effects on buoyancy driven flow fields which occur in many situations involving materials processing, and other basic fluid physics phenomena. In addition, the second hypothesis will also provide insight in how Rayleigh-Taylor and Kelvin-Helmholtz instabilities propagate concentration fronts during mixing. Measurement of the flow field using SIV is important because it is the flow field which causes instability at the interface between the two fluids. Mixing driven by buoyancy induced flow fields will be addressed both experimentally and computationally. The experimental effort will address the kinematics of mixing: stretching, transport and chaos. Quantification of the mechanisms of mixing will consists of measuring the flow field using the SIV system at Glenn and capturing the dynamics of the interface, to measure mass transport, using a CCD camera. These experiments will be carried out within the framework of Earth's gravity and g-jitter microgravity acceleration as in a Space Shuttle environment or the International Space Station. The g-jitter will be induced and controlled using a tunable vibration isolation platform to isolate against vibration as well as input periodic and random vibration to the system. The parametric range of the microgravity experiment will be extended from the experiments on STS-85 to investigate higher mode quasi-stationary waves (8 to 12), as well as resonance regions which leads to chaos and turbulence. Ground-based experiments will focus on effects of vibration on stably stratified fluid layers in order to scale for possible scenarios in a microgravity environment. These vibrations will be subjected perpendicular to the concentration field on the ground since the parallel case can only be carried out in a microgravity environment. The concept of dynamical similarity will be applied to tune the experiments as closely as possible to a Space Shuttle environment or the International Space Station. The computational effort will take advantage of the Computational Laboratory at Glenn to corroborate the experimental findings with predictions of the dynamics of the flow field using the codes FLUENT (finite difference based) and FIDAP (finite element based). We will investigate two important cases, single-fluid model to address dilute systems with negligible jump in viscosity and the more general two-fluid model which accounts for finite jump in viscosity. Apart from its microgravity relevance, this experiment is well suited to study dynamics in nonlinear systems.

Duval, W. M. B.↗
NASA NTRS1998

Bi-Level Integrated System Synthesis (BLISS)

BLISS is a method for optimization of engineering systems by decomposition. It separates the system level optimization, having a relatively small number of design variables, from the potentially numerous subsystem optimizations that may each have a large number of local design variables. The subsystem optimizations are autonomous and may be conducted concurrently. Subsystem and system optimizations alternate, linked by sensitivity data, producing a design improvement in each iteration. Starting from a best guess initial design, the method improves that design in iterative cycles, each cycle comprised of two steps. In step one, the system level variables are frozen and the improvement is achieved by separate, concurrent, and autonomous optimizations in the local variable subdomains. In step two, further improvement is sought in the space of the system level variables. Optimum sensitivity data link the second step to the first. The method prototype was implemented using MATLAB and iSIGHT programming software and tested on a simplified, conceptual level supersonic business jet design, and a detailed design of an electronic device. Satisfactory convergence and favorable agreement with the benchmark results were observed. Modularity of the method is intended to fit the human organization and map well on the computing technology of concurrent processing.

Sobieszczanski-Sobieski, Jaroslaw↗
NASA NTRS2006

Radiative Forcing by Well-Mixed Greenhouse Gases: Estimates from Climate Models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)

The radiative effects from increased concentrations of well-mixed greenhouse gases (WMGHGs) represent the most significant and best understood anthropogenic forcing of the climate system. The most comprehensive tools for simulating past and future climates influenced by WMGHGs are fully coupled atmosphere-ocean general circulation models (AOGCMs). Because of the importance of WMGHGs as forcing agents it is essential that AOGCMs compute the radiative forcing by these gases as accurately as possible. We present the results of a radiative transfer model intercomparison between the forcings computed by the radiative parameterizations of AOGCMs and by benchmark line-by-line (LBL) codes. The comparison is focused on forcing by CO2, CH4, N2O, CFC-11, CFC-12, and the increased H2O expected in warmer climates. The models included in the intercomparison include several LBL codes and most of the global models submitted to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). In general, the LBL models are in excellent agreement with each other. However, in many cases, there are substantial discrepancies among the AOGCMs and between the AOGCMs and LBL codes. In some cases this is because the AOGCMs neglect particular absorbers, in particular the near-infrared effects of CH4 and N2O, while in others it is due to the methods for modeling the radiative processes. The biases in the AOGCM forcings are generally largest at the surface level. We quantify these differences and discuss the implications for interpreting variations in forcing and response across the multimodel ensemble of AOGCM simulations assembled for the IPCC AR4.

Collins, W. D.↗
NASA NTRS1986

HOST combustion R and T overview

The overall objective of the Turbine Engine Hot Section Technology Combustion Project was to develop and verify improved and more accurate numerical analysis methods for increasing the ability to design with confidence combustion systems for advanced aircraft gas turbine engines. The objective was approached from two directions: computational and experimental. On the computational side, the approach was to first assess and evaluate existing combustor aerothermal analysis models. On the experimental side, three types of experiments are identified; first, fundamental experiments directed toward improved understanding of the flow physics and chemistry; second, experiments run to provide data for the empirical modeling of complex phenomena; and third, benchmark experiments for computer code validation.

Gaugler, Raymond E.↗
NASA NTRSDate not supplied

An Expanded Role for Python in Expediting System Simulation Development

The Python programming language has traditionally been used as a “scripting” language and is not generally recognized as a language for building system simulations, where C++, Java, and other compiled languages are typically used. While very powerful and gaining favor for a large set of programming tasks, Python is generally regarded as not having the speed to directly do the extensive numeric computations required in large-scale simulation. This paper aims to present an approach, supported by case studies, to re-think this assertion. Directly using Python in this new role has the potential to expedite an agile, spiral cycle of development of design-test-modify for systems simulation.

programming language↗