Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Surrogates”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

Unsteady Extinction of Opposed Jet Ethylene/Methane HIFiRE Surrogate Fuel Mixtures vs Air

A unique idealized study of the subject fuel vs. air systems was conducted using an Oscillatory-input Opposed Jet Burner (OOJB) system and a newly refined analysis. Extensive dynamic-extinction measurements were obtained on unanchored (free-floating) laminar Counter Flow Diffusion Flames (CFDFs) at 1-atm, stabilized by steady input velocities (e.g., U(sub air)) and perturbed by superimposed in-phase sinusoidal velocity inputs at fuel and air nozzle exits. Ethylene (C2H4) and methane (CH4), and intermediate 64/36 and 15/85 molar percent mixtures were studied. The latter gaseous surrogates were chosen earlier to mimic ignition and respective steady Flame Strengths (FS = U(sub air)) of vaporized and cracked, and un-cracked, JP-7 "like" kerosene for a Hypersonic International Flight Research Experimentation (HIFiRE) scramjet. For steady idealized flameholding, the 100% C2H4 flame is respectively approx. 1.3 and approx.2.7 times stronger than a 64/36 mix and CH4; but is still 12.0 times weaker than a 100% H2-air flame. Limited Hot-Wire (HW) measurements of velocity oscillations at convergent-nozzle exits, and more extensive Probe Microphone (PM) measurements of acoustic pressures, were used to normalize Dynamic FSs, which decayed linearly with pk/pk U(sub air) (velocity magnitude, HW), and also pk/pk P (pressure magnitude, PM). Thus Dynamic Flame Weakening (DFW) is defined as % decrease in FS per Pascal of pk/pk P oscillation, namely, DFW = -100 d(U(sub air)/U(sub air),0Hz)/d(pkpk P). Key findings are: (1) Ethylene flames are uniquely strong and resilient to extinction by oscillating inflows below 150 Hz; (2) Methane flames are uniquely weak; (3) Ethylene / methane surrogate flames are disproportionately strong with respect to ethylene content; and (4) Flame weakening is consistent with limited published results on forced unsteady CFDFs. Thus from 0 to approx. 10 Hz and slightly higher, lagging diffusive responses of key species led to progressive phase lags (relative to inputs) in the oscillating flames, and caused maximum weakening. At 20 to 150 Hz, diffusion-rate-limited effects diminished, causing flames to "regain strengnth," and eventually become completely insensitive beyond 300 Hz. Detailed mechanistic understanding is needed. Overall, ethylene flames are remarkably resilient to dynamic extinction by oscillating inflows. They are the strongest, with the notable exception of H2. For HIFiRE tests, the 64%/36% surrogate disproportionally retains the high dynamic FS of ethylene, so the potential for loss of scramjet flameholding (flameout) due to low frequency oscillations is significantly mitigated.

Vaden, Sarah N.↗

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

A surrogate model methodology is described for predicting, during flight, the residual strength of aircraft structures that sustain discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. Two ductile fracture simulations are presented to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data does, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Spear, Ashley D.↗

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Spear, Ashley D.↗

Simulation of Hydrogen Flow in a Nuclear-Thermal Propulsion Reactor Subsystem: Conjugate Heat Transfer in Surrogate Fuel Elements and Flow Through the Dome Inlet to the Fuel Elements

NASA is performing research related to a Nuclear-Thermal Propulsion (NTP) engine as a step toward future manned missions to Mars. BWX Technologies (BWXT), in conjunction with NASA, is developing the reactor subsystem for that NTP engine design. As a subset of the reactor subsystem, the fuel elements have continued to evolve in design, as well. A set of experiments within the Nuclear Thermal Reactor Element Environmental Simulator at NASA Marshall has been developed to compliment that design process, including a series of surrogate fuel elements. Before the experiments of each surrogate can be completed, they must be deemed safe using structural analysis, which itself requires thermal and conjugate heat transfer analyses of the articles. Therefore, conjugate heat transfer simulations of the hydrogen flow through the test article fuel element surrogates were developed to provide estimates of heating, as well as to provide assessments of the fluid flow through the elements. The set of simulations involved not only the separate test conditions, but also a sensitivity study to estimate the effect of physical parameter uncertainty on the selected quantities of interest. Additionally, the fluid flow through the fore section inner plenum dome to the entrances of the fuel elements, another section of the reactor subsystem still under active development, was simulated and analyzed. The simulations show the extent of non-uniformity in the mass flow distribution across the dome outlets. Furthermore, additional analyses estimate the effects of required flow blockages on the potential development of flow dynamics. These analyses were used in the design cycle to make improvements to the reactor subsystem design.

Kalen E. Braman↗

Surrogate measures: A proposed alternative in human factors assessment of operational measures of performance

Surrogate measures are proposed as an alternative to direct assessment of operational performance for purposes of screening agents who may have to work under unusual stresses or in exotic environments. Such measures are particularly proposed when the surrogate can be empirically validated against the operational criterion. The focus is on cognitive (or throughput) performances in humans as opposed to sensory (input) or motor (output) measures, but the methods should be applicable for development of batteries which will tap input/output functions. A menu of performance tasks is under development for implementation on a battery-operated portable microcomputer, with 21 tests currently available. The tasks are reliable and become stable in minimum amounts of time; appear sensitive to some agents; comprise constructs related to actual job tasks; and are easily administered in most environments. Implications for human factors engineering studies in environmental stress are discussed.

Kennedy, Robert S.↗

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases [1]. Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission [2]. Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an advanced design methods (ADM) based approach. This approach applies the concepts of design of experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development effort. In order to fit a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of ground rules and assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated "what if" questions.

Zwack, Mathew R.↗

Near Real-Time Probabilistic Damage Diagnosis Using Surrogate Modeling and High Performance Computing

This work investigates novel approaches to probabilistic damage diagnosis that utilize surrogate modeling and high performance computing (HPC) to achieve substantial computational speedup. Motivated by Digital Twin, a structural health management (SHM) paradigm that integrates vehicle-specific characteristics with continual in-situ damage diagnosis and prognosis, the methods studied herein yield near real-time damage assessments that could enable monitoring of a vehicle's health while it is operating (i.e. online SHM). High-fidelity modeling and uncertainty quantification (UQ), both critical to Digital Twin, are incorporated using finite element method simulations and Bayesian inference, respectively. The crux of the proposed Bayesian diagnosis methods, however, is the reformulation of the numerical sampling algorithms (e.g. Markov chain Monte Carlo) used to generate the resulting probabilistic damage estimates. To this end, three distinct methods are demonstrated for rapid sampling that utilize surrogate modeling and exploit various degrees of parallelism for leveraging HPC. The accuracy and computational efficiency of the methods are compared on the problem of strain-based crack identification in thin plates. While each approach has inherent problem-specific strengths and weaknesses, all approaches are shown to provide accurate probabilistic damage diagnoses and several orders of magnitude computational speedup relative to a baseline Bayesian diagnosis implementation.

Warner, James E.↗

Calibration of a Structural Finite Element Model for a Representative Inflatable Space Structure Utilizing Probabilistic Methods and Surrogate Models

A structural finite element model representing a novel inflatable airlock concept has been calibrated using full‐scale test data. The concept, denoted as the Non‐Axisymmetric Inflatable Pressure Structure (NAIPS), was developed under NASA’s Minimalistic Advanced Softgoods Hatch (MASH) Program. The current studies extended previous numerical efforts by incorporating the midbody section of the NAIPS to the dome section and calibrating the model with test data using a process that included surrogate models. Brief overviews of the finite element model and calibration process are provided. The completion of the calibration process provided a model that adequately replicated the test data. The successful demonstration of calibration of a finite element model representing an inflatable habitat provides confidence in the ability to use numerical simulations and associated surrogate models to support design and certification of inflatable space habitats.

Lyle, Karen H.↗

Surrogate Fuel Chemistry from ReaxFF Molecular Dynamics

Reactive molecular dynamics with ReaxFF simulations are used to study the chemistry of four component jet fuel mixtures of n-dodecane, iso-octane, n-propylbenzene, and mesitylene. ReaxFF does not require knowledge of the chemistry a priori providing insight into reactions otherwise not seen in established chemical kinetic mechanisms. The results show that a difference in the local chemical environment can change the fuel decomposition pathways across the surrogate mixtures where the same fuel species are used. These simulations highlight the need to consider cross-chemical interactions in chemical kinetic mechanism development and the importance of resonance stabilized polyaromatic hydrocarbon reactions for soot growth and formation. A method for predicting the threshold sooting index from the carbon species formed at the end of the simulations is established. The results of the simulations are consistent with measurements of the threshold sooting index with the predicted values within 20% of the measured data

Surrogate Fuels↗

Coaxial Rotor CFD Validation and ML Surrogate Model Generation

A fixed-pitch speed-controlled coaxial rotor system was tested in the NASA Langley Transonic Dynamics Tunnel in September 2022. The rotors have a diameter of 1.35 meters and an inter-rotor spacing of 25% of the diameter. Though this test was focused on the NASA New Frontiers Dragonfly mission, the resulting dataset is relevant to a wide array of applications of multirotor vehicles, especially those using fixed-pitch variable-speed rotors. Most notably beyond Dragonfly, perhaps, is the application of coaxial rotor pair configurations for eVTOL and Urban Air Mobility (UAM) aircraft. This work provides a thorough CFD validation study quantifying coaxial rotor performance estimation with accuracy on order 5-10% using an efficient hybrid BEMT-URANS flow solver over a wide range of operating conditions. This accuracy was achieved using novel approaches for the construction of both the C81 airfoil performance lookup tables and the BEMT rotor model. These novel approaches are combined with advanced scripting to further accelerate the commercial off-the-shelf CFD solver on GPU accelerated machines. Finally, the development of machine learning surrogate models is presented to produce highly efficient and accurate rotor performance predictions for fixed-pitch variable-speed multirotor aircraft over the complete flight regime including scout, cruise, climb, descent, as well as limiting cases of vortex-ring and windmill-brake states.

Coaxial↗

Surrogate-equation technique for simulation of steady inviscid flow

A numerical procedure for the iterative solution of inviscid flow problems is described, and its utility for the calculation of steady subsonic and transonic flow fields is demonstrated. Application of the surrogate equation technique defined herein allows the formulation of stable, fully conservative, type dependent finite difference equations for use in obtaining numerical solutions to systems of first order partial differential equations, such as the steady state Euler equations. Steady, two dimensional solutions to the Euler equations for both subsonic, rotational flow and supersonic flow and to the small disturbance equations for transonic flow are presented.

Johnson, G. M.↗

Surrogate oracles, generalized dependency and simpler models

Software reliability models require the sequence of interfailure times from the debugging process as input. It was previously illustrated that using data from replicated debugging could greatly improve reliability predictions. However, inexpensive replication of the debugging process requires the existence of a cheap, fast error detector. Laboratory experiments can be designed around a gold version which is used as an oracle or around an n-version error detector. Unfortunately, software developers can not be expected to have an oracle or to bear the expense of n-versions. A generic technique is being investigated for approximating replicated data by using the partially debugged software as a difference detector. It is believed that the failure rate of each fault has significant dependence on the presence or absence of other faults. Thus, in order to discuss a failure rate for a known fault, the presence or absence of each of the other known faults needs to be specified. Also, in simpler models which use shorter input sequences without sacrificing accuracy are of interest. In fact, a possible gain in performance is conjectured. To investigate these propositions, NASA computers running LIC (RTI) versions are used to generate data. This data will be used to label the debugging graph associated with each version. These labeled graphs will be used to test the utility of a surrogate oracle, to analyze the dependent nature of fault failure rates and to explore the feasibility of reliability models which use the data of only the most recent failures.

Wilson, Larry↗

A Rigorous Framework for Optimization of Expensive Functions by Surrogates

The goal of the research reported here is to develop rigorous optimization algorithms to apply to some engineering design problems for which design application of traditional optimization approaches is not practical. This paper presents and analyzes a framework for generating a sequence of approximations to the objective function and managing the use of these approximations as surrogates for optimization. The result is to obtain convergence to a minimizer of an expensive objective function subject to simple constraints. The approach is widely applicable because it does not require, or even explicitly approximate, derivatives of the objective. Numerical results are presented for a 31-variable helicopter rotor blade design example and for a standard optimization test example.

Booker, Andrew J.↗

Software Surrogate

In 1994, Blackboard Technology received a NASA Phase I SBIR award entitled "A Blackboard-Based Framework for Mixed-Initiative, Crewed- Space-System Applications." This research continued in Phase II at JSC, where a generic architecture was developed in which a software surrogate serves as the operator's representative in the fast-paced realm of nearly autonomous, intelligent systems. This SBIR research effort addressed the need to support human-operator monitoring and intervention with intelligent systems such as those being developed for NASA's crewed space program.

Source record↗

Experimental Study of the Angle of Repose of Surrogate Martian Dust

Accumulation of wind-blown dust particles on solar cells and instruments will be a great challenge in the exploration of Mars, significantly reducing their lifetime, durability, and power output. For future Mars Lander missions it is crucial to gain information about the ideal angle at which solar panels can be positioned to minimize dust deposition and thus, maximize the power output and lifetime of the solar cells. The major determinant for the optimal panel angle is the angle of repose of the dust particles that is dependent on a variety of physical and chemical properties of the particles, the panel surface, and the environmental conditions on the Mars surface. To gain a basic understanding of the physical and chemical processes that govern dust deposition and to get feedback for the design of an experiment suitable for one of the future Mars Lander missions we simulate atmospheric conditions expected on the Mars surface in a controlled chamber, and observe the angle of repose of Mars dust surrogates. Dust deposition and angle of repose were observed on different sized spheres. To cover a range of potential materials we will use spheres made of 7075 aluminum (10 mm, and 15 mm), alumina oxide ceramic (10 mm), and Teflon(trademark) (10 mm) and wafers of gallium arsenide, silicon.

Moeller, L. E.↗

Myotonometry as a Surrogate Measure of Muscle Strength

Space flight-induced muscle atrophy/neuromuscular degradation and the consequent decrements in crew-member performance are of increasing concern as mission duration lengthens, and planetary exploration after extended space flight is planned. Pre- to post-flight strength measures have demonstrated that specific countermeasures, such as resistive exercise, are effective at countering microgravity-induced muscle atrophy and preventing decrements in muscle strength. However, in-flight assessment/monitoring of exercise countermeasure effectiveness will be essential during exploration class missions due to their duration. The ability to modify an exercise countermeasure prescription based on such real-time information will allow each individual crew member to perform the optimal amount and type of exercise countermeasure to maintain performance. In addition, such measures can be used to determine if a crew member is physically capable of performing a particular mission-related task during exploration class missions. The challenges faced in acquiring such data are those common to all space operations, namely the requirement for light-weight, low power, mechanically reliable technologies that make valid measurements in microgravity, in this case of muscle strength/neuromuscular function. Here we describe a simple, light-weight, low power, non-invasive device, known as the Myotonometer, that measures tissue stiffness as an indirect measure of muscle contractile state and muscle force production. Repeat myotonometer measurements made at the same location on the surface of the rectis femoris muscle (as determined using a 3D locator device, SEM plus or minus 0.34 mm) were shown to be reproducible over time at both maximal voluntary contraction (MVC) and at rest in a total of 17 sedentary subjects assessed three times over a period of seven days. In addition, graded voluntary isometric force production (i.e. 20%, 40%, 60%, 80% & 100% of MVC) during knee extension was shown to be significantly (p less than 0.01) correlated with contemporaneous myotonometer measurements made on the rectis femoris muscle in a total of 16 healthy subjects (8 males, 8 females). Further-more, this device has been operationally tested during parabolic flight demonstrating its suitability for use in a microgravity environment. Our data indicates that the Myotonometer is a viable surrogate measure of muscle contractile state/tone and of muscle strength/force production. Additional studies are required to assess the suitability of this technique for assessing these measures in de-conditioned subjects such as crew-members.

Ang, B. S.↗

Diagnosis of Magnetic Structures and Intermittency in Space Plasma Turbulence using the Method of Surrogate Data

Several observations in space plasmas have reported the presence of coherent structures at different plasma scales. Structure formation is believed to be a direct consequence of nonlinear interactions between the plasma modes, which depend strongly on phase synchronization of those modes. Despite this important role of the phases in turbulence, very limited work has been however devoted to study the phases as a potential tracers of nonlinearities in comparison with the wealth of literature on power spectra of turbulence where phases are totally missed. We present a method based on surrogate data to systematically detect coherent structures in turbulent signals. The new method has been applied successfully to magnetosheath turbulence (Sahraoui, Phys. Rev. E, 2008, in press), where the relationship between the identified phase coherence and intermittency (classically identified as non Gaussian tails of the PDFs) as well as the energy cascade has been studied. Here we review the main results obtained in that study and show further applications to small scale solar wind turbulence. Implications of the results on theoretical modelling of space turbulence (applicability of weak/wave turbulence, its validity limits and its connection to intermittency) will be discussed.

Sahraoui, Fouad↗

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

Leser, Patrick E.↗