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At least 1,405 records · Page 78

Preliminary Soot Computations Based on a Model Aircraft Combustor With OpenNCC

In a preliminary effort to extend our current capabilities used in the design & testing of aero-engine combustors to particulate emissions, we incorporated several existing 2- equation soot models into the Open National Combustion Code (OpenNCC). The paper presents results from a validation study based on a well-characterized, swirl-stabilized, turbulent sooting flame generated by a model aero-engine combustor developed at DLR, Germany. The calculations are based on a Reynolds-Averaged Navier Stokes (RANS) simulation with standard k-e turbulence model & a finite-rate chemical kinetic mechanism. A separate transport equation is solved for all individual species involved in ethylene/air combustion. The predicted velocity and temperature are mostly in good agreement with the measured data and reasonable agreement was found for soot. While the calculated SVF (Soot Volume Fraction) behavior is similar to some other predicted results reported in literature, the measured soot lasts farther downstream than the calculated soot indicating a need for further improvement in the soot models employed.

Raju, Manthena↗

The 13th Technology of Deep Space One - Abstract

On October 24th, 1998, the Deep Space One (DS-1) spacecraft launched aboard a Delta II rocket as the first step towards the bold task of testing and validating 12 new technologies for future missions. This launch also represented yet another thrilling event; namely, the successful test and validation of a 13th heretofore undisclosed technology: model-based code-generation of the spacecraft's system-level fault-protection (FP) software from behavioral state diagrams and structural models.In this paper, we describe the process we used to leverage model-based code generation from state diagrams and structural specifications to better respond to the evolving requirements and scope of DS- I's system-level fault-protection design, development, test and operation. The evolution of the high-level design and the low-level changes in the flight software architecture and interfaces contributed to multiplying the number and frequency of fault-protection software releases thereby creating a multitude of software integration issues. To address the resulting software integration issues, we broadened the scope of code -eneration to other forms of model- based analysis techniques more traditionally associated with first-principle's reasoning about physical models. Additionally, we describe our in-flight launch and initial acquisition experience.

Rouquette, Nicolas↗

CoCoSim, a Code Generation Framework for Control/command Applications: An Overview of CoCoSim for Multi-Periodic Discrete Simulink Models

We present CoCoSim, a framework to support the design, code generation and analysis of discrete dataflow model expressed in Simulink. In this work, we specifically focus on the analysis and code generation of multi-periodic systems. For that CoCoSim provides two complementary approaches: the first amounts to encode the multiperiodic semantics in a pure-synchronous one – à la Lustre–, enabling the use of model checker for verifying properties. The second provides a faithful code generation into multiple communicating (mono)synchronous components – à la Prelude– that can be then simulated or embedded in the final platform with any real-time scheduler. These approaches have been experimented in various settings.

Bourbouh, Hamza↗

Convection

We review the status of theoretical work on magnetospheric convection in the lower auroral zone and at midlatitudes, and compare with various observed features, such as ionospheric electric fields and plasma flows, the form of the plasmasphere, and the distribution of plasma-sheet particles. We present preliminary results from a new series of computerized convection models, which follow the time evolution of the inner magnetosphere (L less than around 10), self-consistently including ionospheric currents and Birkeland currents, as well as the currents generated in a model plasma sheet with a realistic energy spectrum. We find that the model plasma sheet's inner edge quickly becomes rather sharp. Computed electric field distributions resemble those obtained earlier for a simple single-energy plasma sheet.

Harel, M.↗

Assessment of the risk due to release of carbon fiber in civil aircraft accidents, phase 2

The risk associated with the potential use of carbon fiber composite material in commercial jet aircraft is investigated. A simulation model developed to generate risk profiles for several airports is described. The risk profiles show the probability that the cost due to accidents in any year exceeds a given amount. The computer model simulates aircraft accidents with fire, release of fibers, their downwind transport and infiltration of buildings, equipment failures, and resulting ecomomic impact. The individual airport results were combined to yield the national risk profile.

Pocinki, L.↗

Climate warming due to increasing atmospheric CO2 - Simulations with a multilayer coupled atmosphere-ocean seasonal energy balance model

The transient response of the climate to increasing CO2 is studied using a modified version of the multilayer energy balance model of Peng et al. (1982). The main characteristics of the model are described. Latitudinal and seasonal distributions of planetary albedo, latitude-time distributions of zonal mean temperatures, and latitudinal distributions of evaporation, water vapor transport, and snow cover generated from the model and derived from actual observations are analyzed and compared. It is observed that in response to an atmospheric doubling of CO2, the model reaches within 1/e of the equilibrium response of global mean surface temperature in 9-35 years for the probable range of vertical heat diffusivity in the ocean. For CO2 increases projected by the National Research Council (1983), the model's transient response in annually and globally averaged surface temperatures is 60-75 percent of the corresponding equilibrium response, and the disequilibrium increases with increasing heat diffusivity of the ocean.

Li, Peng↗

The Man-machine Integration Design and Analysis System (MIDAS) Software Training Documentation

This document is a training manual for MIDAS v5 that takes an user through the hardware and software requirements for the MIDAS V5 software, the steps required to download the software, and the steps that a user needs to take to create a MIDAS simulation. The training guide also illustrates how the models interact to generate MIDAS predictions of operator performance along task, workload, and situation awareness timelines and provides the test routines that were conducted to verify the operation of the integrated MIDAS models. The training guide shows the user how the MIDAS task model interacts with and controls an anthropometric model through its use of behavioral primitives. The training documentation also illustrates one approach that has been used to filter and analyze MIDAS output.

Brian F. Gore↗

Wind tunnel investigations of model rotor noise at low tip speeds

Experimental and related analytical results on model rotor rotational and broadband noise obtained in the anechoic wind tunnel and rotor facility are summarized. Factors studied include various noise sources, effects of helicopter performance parameters on noise generated by a model main rotor, appropriate scaling laws for the various types of main rotor noise, and the effects of intensity and size scales of injected turbulence on the intensity and spectra of broadband noise.

Aravamudan, K. S.↗

An evaluation of the role of eddy diffusion in stratospheric interactive two-dimensional models

An interactive two-dimensional model of the stratosphere, consisting of a primitive equation dynamics module, a simplified HO(x) ozone model, and a full radiative transfer scheme, is used to study the effect of eddy diffusion in the model. Consideration is given to the effects of nonlocal forcing from dissipation in the model troposphere and frictional drag at mesospheric levels, mechanical damping in the stratosphere itself, and potential vorticity flux due to large scale waves. It is found that the ozone distributions generated with the model are very sensitive to the choice of values for the friction and the eddy diffusion coefficients. It is shown that reasonable latitudinal gradients of ozone may be obtained by using small values for the mechanical damping for the mid- and high-latitude stratopsphere.

Schneider, Hans R.↗

Low-latitude thermospheric neutral winds determined from AE-E measurements of the 6300-A nightglow at solar maximum

Atmosphere Explorer E (AE-E) measurements of the O(1D) 6300-A emission in the nighttime equatorial thermosphere are used to infer the height of the F2 layer peak as a function of latitude and local time. The investigation is conducted both for northern hemisphere winter solstice and for spring equinox, under solar maximum conditions. The layer heights are used to derive magnetic meridional components of the transequatorial neutral wind, in conjunction with the MSIS-86 model and previous Jicamarca incoherent scatter measurements of the zonal electric field. The AE-E wind estimates indicate a predominant summer to winter flow for the winter solstice case. Comparisons are made with the empirical horizontal wind model HWM87 and with winds generated by the thermospheric general circulation model. The model predictions and experimental results are generally in good agreement, confirming the applicability of visible airglow data to studies of the global neutral wind pattern.

Burrage, M. D.↗

Remote sensing of earth terrain

In remote sensing, the encountered geophysical media such as agricultural canopy, forest, snow, or ice are inhomogeneous and contain scatters in a random manner. Furthermore, weather conditions such as fog, mist, or snow cover can intervene the electromagnetic observation of the remotely sensed media. In the modelling of such media accounting for the weather effects, a multi-layer random medium model has been developed. The scattering effects of the random media are described by three-dimensional correlation functions with variances and correlation lengths corresponding to the fluctuation strengths and the physical geometry of the inhomogeneities, respectively. With proper consideration of the dyadic Green's function and its singularities, the strong fluctuation theory is used to calculate the effective permittivities which account for the modification of the wave speed and attenuation in the presence of the scatters. The distorted Born approximation is then applied to obtain the correlations of the scattered fields. From the correlation of the scattered field, calculated is the complete set of scattering coefficients for polarimetric radar observation or brightness temperature in passive radiometer applications. In the remote sensing of terrestrial ecosystems, the development of microwave remote sensing technology and the potential of SAR to measure vegetation structure and biomass have increased effort to conduct experimental and theoretical researches on the interactions between microwave and vegetation canopies. The overall objective is to develop inversion algorithms to retrieve biophysical parameters from radar data. In this perspective, theoretical models and experimental data are methodically interconnected in the following manner: Due to the complexity of the interactions involved, all theoretical models have limited domains of validity; the proposed solution is to use theoretical models, which is validated by experiments, to establish the region in which the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach.

Yueh, Herng-Aung↗

Modeling Principles Using the Relation Between Lagrange Multipliers and Bond Graphs

Final document is attached. Modeling dynamic systems by bond graphs has become state of the art technology since hundreds of researchers around the world have incorporated the technology in many fields of engineering and science. The legacy of its invertor Prof. Henry Paynter at MIT in 1959 is now a fundamental and practical technique to understand reality by building computer models. This paper addresses a particular aspect of this technology when modeling of mechanical systems require relaxation of constraints by means of Lagrange principles. Lagrange's equations are a useful means of describing and solving systems with kinematic constraints. Lagrange multipliers are variables used in equations to find the extremes of multivariate functions. Here we explore the relation of Lagrange multipliers to solve modeling difficulties of a space vehicle with equations with dependent derivatives. Lagrange multipliers were used in conjunction with bond graphs to simulate a system where joints of kinematic linkages produce dependent derivatives. NASA's Morpheus Project lunar lander was used as a case study. The Morpheus Project is a terrestrial test vehicle designed to fly the terminal descent trajectory of a lunar lander to advance the Autonomous Landing Hazard Avoidance Technology (ALHAT). An objective of this study is to apply the modeling approach herein to capture the dynamic movement of the lander as the propellant is sloshed and consumed. This paper expands further the analysis presented by (Granda, J J. Nguyen, L, Carlson, T, Sahragard-Monfared, G., Fornalski, E., Brocker 2016). Using an automated approach bond graph models of state space equations were generated using the Computer Aided Modeling Program (CAMPG). Integral causality models and derivative causality models were considered in order to find the simpler solution for the mathematical dependencies produced in modeling this vehicle.

Granda, Jose J.↗

(abstract) Navigating through the Venus Atmosphere

This paper presents the problems and challenges of the Magellan Navigation Team. The challenges are: 1) to predict the periapsis time to an accuracy of less than 100 seconds, 2) to accurately predict the dynamic pressure incurred by the spacecraft, 3) to model and to generate this prediction in a timely manner, 4) to provide navigation support 7 days per week for 70 days with 3 navigators and one graphic specialist to generate a daily package for presentation and display. The problems encountered by the Navigation Team in order to meet the above challenges are: 1) the uncertainty in the Venus atmosphere model, 2) the uncertainty in the Venus gravity model, 3) the uncertainty in predicting the attitude control thruster firing, 4) the sparse amount of radiometric tracking data, 5) the radiometric data editing is complicated by the effects of the Venus atmosphere fluctuations.

Venus↗

Framework for Estimating Performance and Associated Uncertainty for Modified Aircraft Configurations

Flight testing has been the historical standard for determining aircraft airworthiness. However, increases in the cost of flight testing and the accuracy of inexpensive CFD encourage the adoption of certification by analysis to reduce or replace flight testing. A framework is introduced to predict the performance in the special case of a modification to an existing, previously certified aircraft. This framework uses a combination of existing flight tests or high fidelity data of the original aircraft as well as lower fidelity data from CFD or wind tunnel testing of the original and modified configurations to create 6-DOF flight dynamics models. Two methods are presented which generate an updated flight dynamics model and estimate the model form uncertainty for the modified aircraft configuration using knowledge of the original aircraft. This updated dynamics model and uncertainty estimate are then used to conduct non-deterministic simulations with wind turbulence included. The framework is applied to an example aircraft system to demonstrate the ability to predict the performance and associated model from the uncertainty of modified aircraft configurations.

uncertainty quantification↗

A forward model-based validation of cardiovascular system identification

We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.

NASA Discipline Cardiopulmonary↗

A Framework for Deep Learning Emulation of Numerical Models With a Case Study in Satellite Remote Sensing

Numerical models based on physics represent the state of the art in Earth system modeling and comprise our best tools for generating insights and predictions. Despite rapid growth in computational power, the perceived need for higher model resolutions overwhelms the latest generation computers, reducing the ability of modelers to generate simulations for understanding parameter sensitivities and characterizing variability and uncertainty. Thus, surrogate models are often developed to capture the essential attributes of the full-blown numerical models. Recent successes of machine learning methods, especially deep learning (DL), across many disciplines offer the possibility that complex nonlinear connectionist representations may be able to capture the underlying complex structures and nonlinear processes in Earth systems. A difficult test for DL-based emulation, which refers to function approximation of numerical models, is to understand whether they can be comparable to traditional forms of surrogate models in terms of computational efficiency while simultaneously reproducing model results in a credible manner. A DL emulation that passes this test may be expected to perform even better than simple models with respect to capturing complex processes and spatiotemporal dependencies. Here, we examine, with a case study in satellite-based remote sensing, the hypothesis that DL approaches can credibly represent the simulations from a surrogate model with comparable computational efficiency. Our results are encouraging in that the DL emulation reproduces the results with acceptable accuracy and often even faster performance. We discuss the broader implications of our results in light of the pace of improvements in high-performance implementations of DL and the growing desire for higher resolution simulations in the Earth sciences.

Bayesian Deep Learning↗

Low Reynolds Number Airfoil Evaluation for the Mars Helicopter Rotor

The present research is aimed at providing a performance model for the Mars Helicopter (MH), to understand the complexity of the flow, and future regions of improvement. The Martian atmosphere's low density and the MH's relatively small rotor result in very low chord-based Reynolds number flows, Rec = O(10(exp 3)-10(exp 4)). The low density and subcritical Reynolds number reduce the lifting force and lifting efficiency, respectively. The high drag coefficients in subcritical flow, especially for thicker sections, are attributed to laminar separation from the rear of the airfoil. The goal is to generate a performance model for the MH rotor for a free wake analysis, since the computational budget for a complete Navier-Stokes solution for a rotating body-fitted rotor is substantial. In this study, a RANS-based approach is used to generate the airfoil deck using OVERFLOW with stitched experimental data for very high angles of attack. The model is presented through airfoil data tables (C81 files) that are used by comprehensive rotor analysis codes such as CAMRADII, or the mid-fidelity CFD solver RotCFD. These codes have proven to provide accurate performance predictions for all rotor operations at only a fraction of the computational expense of three- dimensional body-fitted viscous grids.

Koning, Witold J. K.↗

Computational aerodynamics - The next generation

Continued advances in the various elements that comprise the field of computational fluid dynamics (CFD) are promoting a radically different approach to the aerodynamic design and analysis of aerospace vehicles and systems. The elements of CFD generally include numerical algorithm development, transition and turbulence modeling, surface modeling, and grid generation, scientific visualization and validation methodologies. This paper discusses the research progress and prospects for the future in each of these elements within NASA's CFD and Experimental Validation Program. The applicability of computational methods for the purposes of understanding complex flow phenomena, exploring aerodynamic concepts, and providing vehicle-design input is also addressed.

Hessenius, Kristin A.↗