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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 1,207 records · Page 67

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NASA NTRS2003

Ultrasail

Ultrasail is a complete sail system for the launch, deployment, stabilization and control of very large solar sails enabling reduced mission times for interplanetary and deep space spacecraft. Ultrasail is an innovative, non-traditional approach to propulsion technology achieved by combining propulsion and control systems developed for formation-flying microsatellites with an innovative solar sail architecture to achieve sq km-class controllable sail areas, sail subsystem area densities of 1 gm per sq m, and thrust levels equivalent to 400 kW ion thruster systems used for comparable deep space missions. Ultrasail can conceivably even achieve outer planetary rendezvous, a deep space capability now reserved for high-mass nuclear and chemical systems. Ultrasail is a Delta IV-launched multi-blade spin-stabilized system with blade lengths as long as 50 km, reminiscent of the MacNeal Heliogyro. The primary innovation is the near-elimination of sail supporting structures by attaching the sail tip to a rigid formation-flying microsatellite truss which deploys the sail blade, and which then articulates the blade to provide attitude control, including spin stabilization and precession of the spin axis. These tip microsatellites are controlled by a solar-powered 3-axis microthruster system (electric or cold gas) to maintain proper sail film tension during deployment and spin-up. The satellite mass also provides a stabilizing centrifugal force on the blade while in rotation. Understanding the dynamics of individual blades is key to the overall dynamics of Ultrasail. Forces and torques that must be modeled include those due to solar pressure, those generated by the microsatellite at the blade tip and by torques applied at the blade root. Centrifugal forces also play a significant role in the deployment and maintenance of the sail configuration. To capture the dynamics of the overall system, the equations of motion for the blades have been derived. Using these differential equations, a control law will be derived to maneuver Ultrasail. This law involves the pitching of the individual blades thereby moving the distribution of the radiation pressure on each individual blade and inducing a resultant torque on the system. The direction of the angular momentum vector and its rate of precession can be controlled through the pitch angle of the blades. The Ultrasail trajectory is also being studied. Optimal or near-optimal trajectories are being generated to showcase Ultrasail performance. Various missions, e.g. outer planet and solar polar missions for observation of the Sun, are currently being investigated to demonstrate the performance enhancements generated by Ultrasail technology. Calculus-of-variations-based optimization software is used to produce optimal Ultrasail trajectories. The performance of these trajectories is being compared to optimal results generated with other propulsion models, including chemical propulsion, ion propulsion, and competing solar sail concepts. Results of these studies will quantify the performance of Ultrasail compared to existing solar sail concepts for high energy missions.

Burton, R.↗

NASA NTRS2004

Overcoming Communication Restrictions in Collectives

Many large distributed system are characterized by having a large number of components (eg., agents, neurons) whose actions and interactions determine a %orld utility which rates the performance of the overall system. Such collectives are often subject to communication restrictions, making it difficult for components which try to optimize their own private utilities, to take actions that also help optimize the world utility. In this article we address that coordination problem and derive four utility functions which present different compromises between how aligned a component s private utility is with the world utility and how readily that component can determine the actions that optimize its utility. The results show that the utility functions specifically derived to operate under communication restrictions outperform both traditional methods and previous collective-based methods by up to 75%.

Tumer, Kagan↗

NASA NTRS2006

On the Need for Multidimensional Stirling Analysis

Contents include the following: Dual opposed convertors. High efficiency. Low mass space power. One-dimensional analysis. Fast computation. Design optimizations are easily done. Need for multidimensional modeling. Axisymmetric simulation. Flow characteristics. Low mach number. Laminar, transitional, and turbulent flow. Conjugate heat transfer. Third order analysis. Recent whole engine modeling. Regenerator geometry. Turbulence modeling. Flat head heater not 1-D. Empirical coefficients needed. Experiment design. Flow distribution. Sensor placement. Calibration. Validation.

Dyson, Rodger↗

NASA NTRS2011

Uncertainty Analysis via Failure Domain Characterization: Unrestricted Requirement Functions

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. The methods developed herein, which are based on nonlinear constrained optimization, are applicable to requirement functions whose functional dependency on the uncertainty is arbitrary and whose explicit form may even be unknown. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the assumed uncertainty model (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

Crespo, Luis G.↗

NASA NTRS2013

Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

Soil Moisture↗

NASA NTRS2017

Radiation, Smoke and Clouds Observed in the Southeastern Atlantic With the Research Scanning Polarimeter During ORACLES

The ObseRvations of Aerosols above Clouds and their interactions (ORACLES) project is making a series of field deployments to the southeastern Atlantic with NASA ER-2 and P3 aircraft to acquire both detailed remote sensing observations and in situ measurements of the aerosols and clouds in that region. This area is home to one of the largest low-level cloud decks on Earth that is seasonally affected by vast plumes of smoke from biomass burning, which in effect provides a natural experiment testing the radiative and microphysical interactions between the smoke and the clouds. The downward solar radiation at the surface, or cloud top, is always reduced by the presence of smoke. However, whether the amount of sunlight reflected back out to space is increased, or decreased by the presence of smoke is sensitively dependent on the brightness of the clouds and the fraction of light that the smoke absorbs each time light hits a smoke particle. In this study we use data from the Research Scanning Polarimeter, an along track scanning instrument, that provides measurements of the Stokes parameters I, Q and U at 410, 470, 555, 670, 865, 960, 1590, 1880 and 2260 nm at 150 viewing angles over a range of +/- 60° from nadir for each contiguous sub-aircraft pixel (~ 300 m in size). A retrieval algorithm is applied to the data acquired with a table look up technique, similar to that of the operational POLDER algorithm, to provide a first guess of the complex refractive index, optical depth and size distribution of the smoke particles together with cloud droplet size and optical depth. A subsequent iterative fitting procedure, where the fact that the doubling/adding method allows the construction of the Green's function for the radiative transfer equation, is used to obtain an efficient and statistically optimal estimate of the aerosol and cloud retrieval parameters. These retrieval parameters are evaluated against in situ observations, when available, and the optical depth and intensive lidar variables that are measured by the High Spectral Resolution Lidar 2. Finally, the aerosol and cloud retrievals are used to evaluate the variations in top of the atmosphere, surface/cloud top shortwave radiative forcing and atmospheric absorption that are caused by variations in the smoke and clouds.

Cairns, Brian↗

NASA NTRS2019

The Updated GEO Population for ORDEM 3.1

The limited availability of data for satellite fragmentations and debris in the geosynchronous orbit (GEO) region creates challenges to building accurate models for the orbital debris environment at such altitudes. Updated methods to properly incorporate and extrapolate measurement data have become a cornerstone of the GEO component in the newest version of the NASA Orbital Debris Engineering Model (ORDEM), ORDEM 3.1. For the GEO region, the Space Surveillance Network (SSN) catalog provides coverage down to a limit of approximately 1 m. A more statistically complete representation of the GEO population for smaller objects, which can pose a high risk to operational spacecraft, is thus dependent on dedicated observations by instruments optimized to observe debris smaller than the SSN cataloging threshold. For ORDEM 3.1, optical data from the Michigan Orbital DEbris Survey Telescope (MODEST) provided the input for building the GEO population down to approximately 30 cm (converting absolute magnitude to size). For smaller sizes, the size distribution of debris in the MODEST dataset was extrapolated down to 10 cm, and orbital parameters were estimated based on the orbits of the larger objects. When compared to previous versions of the model, significant improvements were made to the process of building the GEO population in ORDEM 3.1, both in the assessment of fragmentation debris in the data and assignment of orbital elements within the model. A so-called “debris ring filter,” based on a range of angles between an orbit’s angular momentum vector and that of the stable Laplace plane, was applied to the data to reduce biases from non- GEO objects, such as objects in a GEO-transfer orbit. In addition, a new approach was implemented to assign noncircular mean motions and eccentricities to the fragmentation debris observed by MODEST because the short observation window (5 min) in GEO limits orbit resolution to a circular orbit assumption for assigning orbital parameters. For ORDEM 3.1, non-circular orbital elements were assigned using relationships that were identified between mean motion and the angle between the orbit plane and the stable Laplace plane, as well as between mean motion and eccentricity, based on breakup clouds modeled by the NASA Standard Breakup Model. This approach has yielded a high-fidelity GEO model that has been validated with data from more recent MODEST observation campaigns.

Manis, A.↗

NASA NTRSDate not supplied

Subsonic Single Aft Engine (SUSAN) Transport Aircraft Concept and Trade Space Exploration

A trade space exploration of a new NASA regional transport aircraft concept called the SUbsonic Single Aft eNgine (SUSAN) Electrofan is presented. The SUSAN concept uses a 20MW Electrified Aircraft Propulsion (EAP) system to enable advance Propulsion Airframe Integration (PAI) in transport category aircraft. Alternative fuels will be used to reduce the amount of emissions per energy used. By combining these features there is the potential to reduce aircraft emissions by 50% per passenger/mile while retaining the size, speed, and range of large regional jets. SUSAN is has a 750 mile economic mission, a 2500 mile design range and a maximum capacity of 180 passengers. The SUSAN configuration utilizes a single aft mounted engine and distributed electric wing-mounted thrusters on a tube and wing arrangement with a T-tail empennage. The SUSAN Electrofan employs a hybrid powertrain to enable: single turbofan operation on a large transport category aircraft; increased aerodynamic and propulsive efficiency through placement of electric engines; optimized turbofan sizing and efficiency through control and electric boosting, reduced control surface sizing through thrust augmentation. A single use battery is employed as the power source in case of turbofan failure. The design study also considers the constraints of operating within the current airport, airspace and economic constraints. This paper presents the status of the trade space exploration; however the concept definition is not finished. Forward work includes optimizing the overall aircraft configuration and including certain hard to model features like boundary layer ingestion or natural laminar flow across all appliable subsystems. Additional work forward work is a more extensive analysis of the configuration using alternative fuels.

Ralph H. Jansen↗

NASA NTRSDate not supplied

Brief Overview of Subsonic Single Aft Engine (SUSAN) Transport Aircraft Concept and Trade Space Exploration

The SUSAN concept uses a 20-megawatt Electrified Aircraft Propulsion system to enable advance Propulsion Airframe Integration in transport category aircraft. Alternative fuels will be used to reduce the amount of emissions per energy used. By combining these features there is the potential to reduce aircraft emissions by 50 percent per passenger/mile while retaining the size, speed, and range of large regional jets. The SUSAN is has a 750-mile economic mission, a 2500-mile design range and a maximum capacity of 180 passengers. The SUSAN configuration utilizes a single aft mounted engine and distributed electric wing-mounted thrusters on a tube and wing arrangement with a T-tail empennage. The SUSAN Electrofan employs a hybrid powertrain to enable: single turbofan operation on a large transport category aircraft; increased aerodynamic and propulsive efficiency through placement of electric engines; optimized turbofan sizing and efficiency through control and electric boosting, reduced control surface sizing through thrust augmentation. A single use battery is employed as the power source in case of turbofan failure. The design study also considers the constraints of operating within the current airport, airspace, and economic constraints. Forward work includes optimizing the overall aircraft configuration and including certain hard to model features like boundary layer ingestion or natural laminar flow across all appliable subsystems. Additional work forward work is a more extensive analysis of the configuration using alternative fuels.

Ralph Jansen↗

NASA NTRSDate not supplied

Adding GPU Support to the Markov Chain Monte Carlo Code Catmip

In geophysics, we are confronted with many under-determined inverse problems. For example, all of our observations of earthquakes are made at the Earth’s surface. So, when we try to infer how slip during an earthquake evolves in space and time, we find that there are many potential slip histories that are consistent with our limited observations and our understanding of earthquake physics. One way to approach these problems is with Bayesian analysis which allows us to infer the ensemble of all potential slip models that satisfy the observations and our prior knowledge of earthquake physics. In Bayesian analysis, our prior knowledge is known as the prior probability density function or prior PDF, the fit to the data is known as the data likelihood, and the target PDF that satisfies both the prior PDF and data likelihood is known as the posterior PDF. However, simulating the posterior PDF typically requires using Markov Chain Monte Carlo (MCMC) to draw tens of billions of random realizations of earthquake slip models, which may not be computationally feasible. To make this and similar geophysical inversions computationally tractable, we developed the Cascading Adaptive Transitional Metropolis In Parallel (CATMIP) algorithm. CATMIP is an efficient parallel Markov Chain Monte Carlo (MCMC) sampler that is used for model fitting and uncertainty quantification in geophysics. Example use cases are earthquake rupture modeling, determining mineral composition on Mars, reconstructing the history of ocean salinity, and historical earthquake relocation. CATMIP employs many parallel instances of the Metropolis algorithm for sampling in a transitioning framework. Transitioning is a process in which a set of random samples at equilibrium with a known probability density function (PDF) are used as seeds for the Markov chains to sample successive target PDFs that incrementally move the distribution from the starting seeds to the final desired PDF that describes the relative plausibility of potential values for the model parameters. The algorithm is implemented as a Master-Worker model employing MPI for communication. The worker processes are loosely coupled with global parameters periodically optimized by the master process. This provides a very high amount of parallelism with little communication between updates. During the presentation we will discuss the history of the algorithm and elaborate the earthquake rupture modeling use case for the CATMIP package. Our first step toward GPU optimization was to optimize the code for the CPU. CPU profiling revealed that most of the compute time is spent in calls to level 2 BLAS routines and calls to GSL random number generators. We revised the algorithm to employ level 3 BLAS routines instead. In our presentation we will describe how this was accomplished. Adding GPU support to CATMIP consisted mostly of replacing the calls to GSL with calls to GPU vendor-provided library routines. A small number of loops were directly implemented in CUDA. In the presentation will provide implementation details. Finally, we will discuss methods for profiling and opportunities for further optimizing GPU execution. By creating a code with the flexibility to run on either a CPU or GPU architecture, CATMIP can be used on systems ranging from large CPU-based HPC environments to single servers with GPU acceleration and everything in between.

HECC↗

NASA NTRS1976

The C-5A active lift distribution control system

The ALDCS development and design tasks, ALDCS functional configuration, and resulting challenges encountered while accomplishing the first phase of the program are described. These tasks are establishing system requirements and criteria and synthesizing a system mechanization to meet the desired load alleviation, stability margins, flight safety, and flying qualities performance. Results of the ALDCS development and prototype system flight simulation programs, and control law optimization including system stability, handling qualities and structural load analyses are presented, along with concluding remarks relative to the system design integration.

Hargrove, W. J.↗

NASA NTRS1982

Optimization of the performance of a tandem microchannel plate detector as a function of interplate spacing and voltage

The effect of varying the size of the gap voltage and spacing on the performance of a tandem pair of microchannel plates (MCP) is investigated. Results show that increasing the voltage in the gap increases the gain of the pair and also produces a narrower Gaussian pulse-height distribution, although beyond a critical voltage the gain of the channel plate pair is found to plateau. A model is developed which explains the nonlinear gain behavior of individual microchannels and the behavior of the electron cloud emitted from the first MCP as it spreads out between the two MCPs and hits the surface of the second. The model calculates the plateau voltage as a function of the gap size, the gain of each MCP, and the diameter of the channels, and is found to show good agreement with the observed results. It is concluded that interplate gaps of up to several millimeters can be accommodated without a significant degradation in pulse-height distribution.

Rogers, D.↗

NASA NTRS1990

Neuromorphic learning of continuous-valued mappings from noise-corrupted data. Application to real-time adaptive control

The ability of feed-forward neural network architectures to learn continuous valued mappings in the presence of noise was demonstrated in relation to parameter identification and real-time adaptive control applications. An error function was introduced to help optimize parameter values such as number of training iterations, observation time, sampling rate, and scaling of the control signal. The learning performance depended essentially on the degree of embodiment of the control law in the training data set and on the degree of uniformity of the probability distribution function of the data that are presented to the net during sequence. When a control law was corrupted by noise, the fluctuations of the training data biased the probability distribution function of the training data sequence. Only if the noise contamination is minimized and the degree of embodiment of the control law is maximized, can a neural net develop a good representation of the mapping and be used as a neurocontroller. A multilayer net was trained with back-error-propagation to control a cart-pole system for linear and nonlinear control laws in the presence of data processing noise and measurement noise. The neurocontroller exhibited noise-filtering properties and was found to operate more smoothly than the teacher in the presence of measurement noise.

Troudet, Terry↗

NASA NTRS1993

Interpretation of waverider performance data using computational fluid dynamics

A computational study was conducted to better understand experimental results obtained from wind tunnel tests of a Mach 4 waverider model and a comparative reference configuration. The experimental results showed that the performance of the reference configuration was slightly better than that of the waverider model. These results contradict waverider design theory, which suggests that a waverider optimized for maximum lift-to-drag should provide better performance than any other non-waverider configuration at a given design point, especially at hypersonic speeds. The computational results showed that the predicted surface pressure values and the integrated lift and drag coefficients from the pressure distributions were much lower for the reference model than for the flat-top model, due to the reference model bottom surface having a slight expansion. The lift-to-drag ratios for the flat-top model were higher due to a relatively low drag for the same amount of lift. These results indicate that the performance advantage of the reference model was due to the shape of the bottom surface and not due to the flat top surface. The results also showed that the reference model exhibited the same shock attachment characteristics as the waverider because the planform shapes were identical. CFD predictions show that the planform shape gives the waverider an advantage in performance over conventional hypersonic vehicles and that altering the bottom surface of a waverider does not cause significant performance degradation.

Cockrell, Charles E., Jr.↗

NASA NTRS1993

Interpretation of Waverider Performance Data Using Computational Fluid Dynamics

Cockrell, Charles E., Jr.↗

NASA NTRS1997

Award-Winning CARES/Life Ceramics Durability Evaluation Software Is Making Advanced Technology Accessible

Products made from advanced ceramics show great promise for revolutionizing aerospace and terrestrial propulsion and power generation. However, ceramic components are difficult to design because brittle materials in general have widely varying strength values. The CARES/Life software developed at the NASA Lewis Research Center eases this by providing a tool that uses probabilistic reliability analysis techniques to optimize the design and manufacture of brittle material components. CARES/Life is an integrated package that predicts the probability of a monolithic ceramic component's failure as a function of its time in service. It couples commercial finite element programs--which resolve a component's temperature and stress distribution - with reliability evaluation and fracture mechanics routines for modeling strength - limiting defects. These routines are based on calculations of the probabilistic nature of the brittle material's strength.

Source record↗

NASA NTRS2014

Trim and Structural Optimization of Subsonic Transport Wings Using Nonconventional Aeroelastic Tailoring

Several minimum-mass aeroelastic optimization problems are solved to evaluate the effectiveness of a variety of novel tailoring schemes for subsonic transport wings. Aeroelastic strength and panel buckling constraints are imposed across a variety of trimmed maneuver loads. Tailoring with metallic thickness variations, functionally graded materials, composite laminates, tow steering, and distributed trailing edge control effectors are all found to provide reductions in structural wing mass with varying degrees of success. The question as to whether this wing mass reduction will offset the increased manufacturing cost is left unresolved for each case.

Stanford, Bret K.↗

NASA NTRSDate not supplied

Multiobjective Multidisciplinary Optimization of Low-Boom Supersonic Transports Using Multifidelity Models

A multidisciplinary optimization (MDO) method has been developed to design a computational fluid dynamics (CFD) based low-boom configuration that can be obtained from a Pareto solution of a low-fidelity multiobjective MDO problem with mission constraints. This paper refines the developed MDO method using multifidelity models for CFD-based multiobjective MDO. The refined MDO method can generate a low-boom configuration that satisfies the mission requirements, has the lowest takeoff gross weight and the longest range for the low-boom mission, trims the low-boom cruise flight with fuel redistributions, and has a reversed equivalent area distribution closely matching a low-boom target with ground noise level below 70 PLdB. The validity of the refined MDO method is demonstrated by a design study of a low-boom supersonic transport that carries 40 passengers, flies a low-boom mission with cruise Mach of 1.7 and range of 3500 nm, and cruises overwater at Mach 1.8 with range of 3882 nm. Moreover, the refined MDO method eliminates the difference between the assumed cruise weight for CFD-based low-boom inverse design optimization and the estimated cruise weight of the optimal inverse design solution with respect to the mission requirements.

multidisciplinary optimization↗