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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 55 records · Page 3

Dynamic stability test results on an 0.024 scale B-1 air vehicle

Dynamic longitudinal and lateral-directional stability characteristics of the B-1 air vehicle were investigated in three wind tunnels at the Langley Research Center. The main rotary derivatives were obtained for an angle of attack range of -3 degrees to +16 degrees for a Mach number range of 0.2 to 2.16. Damping in roll data could not be obtained at the supersonic Mach numbers. The Langley 7 x 10 foot high speed tunnel, the 8 foot transonic pressure tunnel, and the 4 foot Unitary Plan wind tunnel were the test sites. An 0.024 scale light-weight model was used on a forced oscillation type balance. Test Reynolds number varied from 474,000/ft to 1,550,000/ft. through the Mach number range tested. The results showed that the dynamic stability characteristics of the model in pitch and roll were generally satisfactory up to an angle attack of about +6 degrees. In the wing sweep range from 15 to 25 degrees the positive damping levels in roll deteriorated rapidly above +2 degrees angle of attack. This reduction in roll damping is believed to be due to the onset of separation over the wing as stall is approached.

Beeman, R. R.↗

Millimeter wave communication satellite concepts

Methodology has been developed for identifying viable and appropriate technologies for future NASA millimeter wave research as based upon the technical requirements of potential space communication services. Applicability of the methodology has been verified through its use with two conceptual communications systems. The subsystem cost and weight models are the appropriate level of detail for this study. Application of the methodology to the detailed design of a satellite system would require further model refinement.

Holland, L. D.↗

The inverse problem of constructing a gravimetric geoid

Computation of a single geoidal height from gravity acceleration data formally requires that the latter be known everywhere on the earth. A computational procedure based on linear inverse theory for estimating geoidal heights from incomplete sets of data is presented. The same scheme can be used to estimate gravity accelerations from altimetry-derived geoids. The systematic error owing to lack of data and the choice of a particular inverse operator is described by using resolution functions and their spherical harmonic expansions. An rms value of this error is also estimated by assuming a spectrum for the unknown geoid. The influence of the size of the data region, the spacing between data, the filtering applied to the data, and the model weighting function chosen are all quantified in a spherical geometry. The examples presented show that when low degree spherical harmonic coefficients are available - from satellite orbit analysis - a band-passed version of the geoid can be constructed from local gravity data, even with a relatively restricted data set.

Zlotnicki, V.↗

Design study of a dual-cycle turbofan-ramjet engine for a hypersonic aircraft

Computer modelling was used with two different designs of an advanced turbofan-ramjet in order to derive performance predictions. The engine would enable an aircraft to take-off, accelerate to Mach 5.0, and climb to 90,000 ft. The two concepts included a turbofan with a ramjet annularly wrapped around it and a side-by-side configuration with the ramjet having a rectangular shape and mounted alongside the turbofan. The studies were performed to model weight, length, fuel efficiency, and the requirements of the thrust/drag ratio to exceed unity over the entire flight path. LH2 would be used for fuel and to regeneratively cool the combustion chamber. Turbofan operation with and without afterburner and with and without the ramjet inlet open were examined, as were variable areas for the burners. A side-by-side configuration displayed the best performance predictions, with a ramjet mass flow being 75 percent that of the turbofan and maximum temperatures being equal.

Zumwalt, G. W.↗

Infrared spectroscopy and photometry of Comet Austin 1990 V

3-micron and 10-micron spectra and IR photometry of the dynamically new Comet Austin 1990 V were obtained for March-May 1990. An unusual 9-11 micron emission feature 15-20 percent above the continuum is evident at 0.78 AU postperihelion. The shape, in particular a peak at 11.06 micron, differs from that seen in Halley and several other comets, suggesting a difference in the mineralogy of the silicate grains. The 3.1-7.7 micron spectrum at 0.35 AU shows no obvious feature; feature/continuum contrast of the 3.36 micron emission feature is less than about 5 percent. Based on the IR photometry and a dust model weighted toward small grains, the dust production rate on 6 May at 0.78 AU was about 3 x 10 exp 5 g/s. The corresponding dust/gas mass ratio was about 0.1, classifying Austin as a dust-poor comet. This designation refers only to the relative dust cross section, not to the total mass.

Hanner, Martha S.↗

Advanced Design Methodology for Robust Aircraft Sizing and Synthesis

Contract efforts are focused on refining the Robust Design Methodology for Conceptual Aircraft Design. Robust Design Simulation (RDS) was developed earlier as a potential solution to the need to do rapid trade-offs while accounting for risk, conflict, and uncertainty. The core of the simulation revolved around Response Surface Equations as approximations of bounded design spaces. An ongoing investigation is concerned with the advantages of using Neural Networks in conceptual design. Thought was also given to the development of systematic way to choose or create a baseline configuration based on specific mission requirements. Expert system was developed, which selects aerodynamics, performance and weights model from several configurations based on the user's mission requirements for subsonic civil transport. The research has also resulted in a step-by-step illustration on how to use the AMV method for distribution generation and the search for robust design solutions to multivariate constrained problems.

Mavris, Dimitri N.↗

Cure Chemistry of Phenylethynyl Terminated Oligomers

The ability to process high performance polymers into quality, void-free composites has been significantly advanced using oligomers terminated with reactive groups which cure or crosslink at elevated temperature without the evolution of volatile byproducts. Several matrix resin systems of considerable interest to the aerospace community utilize phenylethynyl-terminated imide (PETI) technology to achieve this advantage. The present paper addresses the cure chemistry of PETI oligomers. The thermal cure of a low molecular weight model compound was studied using a variety of analytical techniques including differential scanning calorimetry, Fourier transform infrared spectroscopy, and liquid chromatography-mass spectroscopy. The studies indicate an extremely complex cure process. Many stable products were isolated and this paper reports current work on identification of those products. The intent of this research is to provide fundamental insight into the molecular structure of the cured PETI engineering materials so that performance and durability can be more fully assessed.

Wood, Karen H.↗

Improved Discrimination of Volcanic Complexes, Tectonic Features, and Regolith Properties in Mare Serenitatis from Earth-Based Radar Mapping

Radar images at 70 cm wavelength show 4-5 dB variations in backscatter strength within regions of relatively uniform spectral reflectance properties in central and northern Mare Serenitatis, delineating features suggesting lava flow margins, channels, and superposition relationships. These backscatter differences are much less pronounced at 12.6 cm wavelength, consistent with a large component of the 70 cm echo arising from the rough or blocky transition zone between the mare regolith and the intact bedrock. Such deep probing is possible because the ilmenite content, which modulates microwave losses, of central Mare Serenitatis is generally low (2-3% by weight). Modeling of the radar returns from a buried interface shows that an average regolith thickness of 10m could lead to the observed shifts in 70 cm echo power with a change in TiO2 content from 2% to 3%. This thickness is consistent with estimates of regolith depth (10-15m) based on the smallest diameter for which fresh craters have obvious blocky ejecta. The 70 cm backscatter differences provide a view of mare flow-unit boundaries, channels, and lobes unseen by other remote sensing methods. A localized pyroclastic deposit associated with Rima Calippus is identified based on its low radar echo strength. Radar mapping also improves delineation of units for crater age dating and highlights a 250 km long, east-west trending feature in northern Mare Serenitatis that we suggest is a large graben flooded by late-stage mare flows.

Radar echoes↗

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗

ESD Reviews: Model Dependence in Multi-Model Climate Ensembles: Weighting, Sub-Selection and Out-Of-Sample Testing

The rationale for using multi-model ensembles in climate change projections and impacts research is often based on the expectation that different models constitute independent estimates; therefore, a range of models allows a better characterisation of the uncertainties in the representation of the climate system than a single model. However, it is known that research groups share literature, ideas for representations of processes, parameterisations, evaluation data sets and even sections of model code. Thus, nominally different models might have similar biases because of similarities in the way they represent a subset of processes, or even be near-duplicates of others, weakening the assumption that they constitute independent estimates. If there are near-replicates of some models, then treating all models equally is likely to bias the inferences made using these ensembles. The challenge is to establish the degree to which this might be true for any given application. While this issue is recognised by many in the community, quantifying and accounting for model dependence in anything other than an ad-hoc way is challenging. Here we present a synthesis of the range of disparate attempts to define, quantify and address model dependence in multi-model climate ensembles in a common conceptual framework, and provide guidance on how users can test the efficacy of approaches that move beyond the equally weighted ensemble. In the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6), several new models that are closely related to existing models are anticipated, as well as large ensembles from some models. We argue that quantitatively accounting for dependence in addition to model performance, and thoroughly testing the effectiveness of the approach used will be key to a sound interpretation of the CMIP ensembles in future scientific studies.

Abramowitz, Gab↗

What is the Relationship Between Altitude and Weight in a Model Rocket?

This experiment was designed to find a function of payload weight for altitude. The same rocket was launched a repeated number of times with the same engine and varying amounts of weight. After performing experimentation, it was calculated that the altitude in meters could be predicted with the equation A = (2.8(W exp 2)) - (70.6W + 310.3), with weight expressed in the unit ounces.

Betz, Jonathan↗

Influence of analysis and design models on minimum weight design

The results of numerical experiments designed to illustrate how the minimum weight design, accuracy, and cost can be influenced by: (1) refinement of the finite element analysis model and associated load path problems, and (2) refinement of the design variable linking model are examined. The numerical experiments range from simple structures where the modelling decisions are relatively obvious and less costly to the more complex structures where such decisions are less obvious and more costly. All numerical experiments used employ the dual formulation in ACCESS-3 computer program. Guidelines are suggested for creating analysis and design models that predict a minimum weight structure with greater accuracy and less cost. These guidelines can be useful in an interactive optimization environment and in the design of heuristic rules for the development of knowledge-based expert optimization systems.

Salama, M.↗

Model reduction by weighted Component Cost Analysis

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called 'component cost' to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. A reduced-order model of the given system may be obtained by deleting those components that have the smallest component costs. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. Closed-form analytical expressions of component costs are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems. A numerical example for MINIMAST system is presented.

Kim, Jae H.↗

Evaluation of Human Spaceflight-Related Tissue Weight Relief Using Whole Body Finite Element Model Simulations

Tissue Weight Relief (TWR) is a physiological condition observed in human spaceflight. It not only impacts the injury biomechanics of soft tissue but also the physiological responses of the cardiovascular system both due to fluid redistribution and the effect of tissue-related transmural pressure on the large venous blood vessels. Understanding the effects of tissue weight relief is especially important because of the role it may play in understanding the cause of Space Associated Neuro-Ocular Syndrome (SANS). SANS can be characterized by a number of ocular changes which reduce visual acuity and SANS related symptoms occur in up to 51% of astronauts. A prevailing theory for the causation of SANS is that of headward (cephalad) fluid shift and a prolonged increase of Intracranial Pressure (ICP) similar to intracranial hypertension, which is not fully supported by the experimental data or astronaut symptom reporting. However, it is still believed that SANS is caused by a pressure change in the eye and the surrounding tissues. It has been proposed that TWR plays a substantial role in affecting internal pressures and fluid shifts in microgravity. In this effort, two whole-body Finite Element (FE) models – Elemance and THUMS – are used to ascertain the microgravity-associated TWR of the musculature surrounding the lower body veins. Elemance and THUMS are physics-based computational models that have been validated and verified for several automotive and domestic applications, and as such, can simulate the relief of soft tissue weight due to changes in the gravitation vector. Specifically, the current effort modeled the transition of the gravitational vector from 1G to 0G, applied across the whole-body model in a supine position. For each 1G to 0G transition simulation, the lower body vein’s transmural pressure-time profile was extracted and averaged around the anterior portion of the thigh muscle. The ascertained transmural pressure changes from 1G to 0G transition are given in Figure 1 for the Elemance and the THUMS FE models. The transmural pressure changes of 10 mmHg and 21 mmHg are in the same order of magnitude as Lu’s value of 44 mmHg. It is to be noted that Lu implemented a 0D to 1D lumped parameter model and the Elemance and THUMS are 3D higher order computational models. This proof-of-concept approach demonstrates that TWR pressure can be adequately estimated with in silico techniques however, further in silico investigations need to be conducted to address the unique contributions to the transmural pressure from each of the computational models.

Finite element modeling↗

Optimal model reduction and frequency-weighted extension

In this paper the quadratically optimal model reduction problem for single-input, single-output systems is considered. The reduced order model is determined by minimizing the integral of the magnitude-squared of the transfer function error. It is shown that the numerator coefficients of the optimal approximant satisfy a weighted least squares problem and, on this basis, a two-step iterative algorithm is developed combining a least squares solver with a gradient minimizer. The existence of globally optimal stable solutions to the optimization problem is established, and convergence of the algorithm to stationary values of the cost function is proved. The formulation is extended to handle the frequency-weighted optimal model reduction problem. Three examples demonstrate the optimization algorithm.

Spanos, J. T.↗

Lessons from Climate Modeling on the Design and Use of Ensembles for Crop Modeling

Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.

Model ensembles↗

Improving Kinetic Consistency Across Elastic Model Transitions With Quadratic Inequality Constrained Weighted Least Squares (WLSQI)

Flexible body modeling presents a large challenge in the development of simulations to aid in design of flight control systems for launch and landing vehicles. Typically, the flexible body model is not a single continuous model but are rather discrete sets of Linear Time Invariant (LTI) Finite Element Models (FEM) incremented by propellant levels. This introduces the problem of smoothly transitioning modal and physical states of the vehicle when switching from one FEM to the next. This paper introduces a new approach to optimally transition flexible body states with weighted least squares, building off previous methods.

Convex Optimization↗