SEARCH · Engineering Papers

Results for “Computational Physics and Simulations”

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,009 records · Page 56

All sources NASA NTRS DOE OSTI

NASA NTRS1977

Monte Carlo simulation of wave sensing with a short pulse radar

A Monte Carlo simulation is used to study the ocean wave sensing potential of a radar which scatters short pulses at small off-nadir angles. In the simulation, realizations of a random surface are created commensurate with an assigned probability density and power spectrum. Then the signal scattered back to the radar is computed for each realization using a physical optics analysis which takes wavefront curvature and finite radar-to-surface distance into account. In the case of a Pierson-Moskowitz spectrum and a normally distributed surface, reasonable assumptions for a fully developed sea, it has been found that the cumulative distribution of time intervals between peaks in the scattered power provides a measure of surface roughness. This observation is supported by experiments.

Levine, D. M.↗

NASA NTRS1978

Investigation of models for large-scale meteorological prediction experiments

The feasibility of long-range weather prediction through the use of global general circulation models (GCMs) was investigated. A climate model was developed to simulate the monthly mean state of the atmosphere from real global initial data at the beginning of the month. The model contains the same dynamic and physical ingredients as most numerical weather prediction models and GCMs. The model generates a one-day global simulation on the 8 x 10 grid in four minutes (on an IBM 360/95 computer), so that a 30 day forecast can be executed in two hours. The high speed of the model is achieved mainly at the price of its coarse resolution, which requires certain parameterizations of surface boundary conditions, as well as inherent filtering of smaller-scale features of the initial state.

Spar, J.↗

NASA NTRS1989

New atmospheric sensor analysis study

The functional capabilities of the ESAD Research Computing Facility are discussed. The system is used in processing atmospheric measurements which are used in the evaluation of sensor performance, conducting design-concept simulation studies, and also in modeling the physical and dynamical nature of atmospheric processes. The results may then be evaluated to furnish inputs into the final design specifications for new space sensors intended for future Spacelab, Space Station, and free-flying missions. In addition, data gathered from these missions may subsequently be analyzed to provide better understanding of requirements for numerical modeling of atmospheric phenomena.

Parker, K. G.↗

NASA NTRS2000

Distribution of Dust from Kuiper Belt Objects

Using an efficient computational approach, we have reconstructed the structure of the dust cloud in the Solar system between 0.5 and 100 AU produced by the Kuiper belt objects. Our simulations offer a 3-D physical model of the 'kuiperoidal' dust cloud based on the distribution of 280 dust particle trajectories produced by 100 known Kuiper belt objects; the resulting 3-D grid consists of 1.9 x 10' cells containing 1.2 x 10" particle positions. The following processes that influence the dust particle dynamics are taken into account: 1) gravitational scattering on the eight planets (neglecting Pluto); 2) planetary resonances; 3) radiation pressure; and 4) the Poynting-Robertson (P-R) and solar wind drags. We find the dust distribution highly non-uniform: there is a minimum in the kuiperoidal dust between Mars and Jupiter, after which both the column and number densities of kuiperoidal dust sharply increase with heliocentric distance between 5 and 10 AU, and then form a plateau between 10 and 50 AU. Between 25 and 45 AU, there is an appreciable concentration of kuiperoidal dust in the form of a broad belt of mostly resonant particles associated with Neptune. In fact, each giant planet possesses its own circumsolar dust belt consisting of both resonant and gravitationally scattered particles. As with the cometary belts simulated in our related papers, we reveal a rich and sophisticated resonant structure of the dust belts containing families of resonant peaks and gaps. An important result is that both the column and number dust density are more or less flat between 10 and 50 AU, which might explain the surprising data obtained by Pioneers 10 & 11 and Voyager that the dust number density remains approximately distance-independent in this region. The simulated kuiperoidal dust, in addition to asteroidal and cometary dust, might represent a third possible source of the zodiacal light in the Solar system.

Gorkavyi, Nick N.↗

NASA NTRS2012

Numerical Simulation of Fluidic Actuators for Flow Control Applications

Active flow control technology is finding increasing use in aerospace applications to control flow separation and improve aerodynamic performance. In this paper we examine the characteristics of a class of fluidic actuators that are being considered for active flow control applications for a variety of practical problems. Based on recent experimental work, such actuators have been found to be more efficient for controlling flow separation in terms of mass flow requirements compared to constant blowing and suction or even synthetic jet actuators. The fluidic actuators produce spanwise oscillating jets, and therefore are also known as sweeping jets. The frequency and spanwise sweeping extent depend on the geometric parameters and mass flow rate entering the actuators through the inlet section. The flow physics associated with these actuators is quite complex and not fully understood at this time. The unsteady flow generated by such actuators is simulated using the lattice Boltzmann based solver PowerFLOW R . Computed mean and standard deviation of velocity profiles generated by a family of fluidic actuators in quiescent air are compared with experimental data. Simulated results replicate the experimentally observed trends with parametric variation of geometry and inflow conditions.

Vasta, Veer N.↗

NASA NTRS2014

CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences

This report documents the results of a study to address the long range, strategic planning required by NASA's Revolutionary Computational Aerosciences (RCA) program in the area of computational fluid dynamics (CFD), including future software and hardware requirements for High Performance Computing (HPC). Specifically, the "Vision 2030" CFD study is to provide a knowledge-based forecast of the future computational capabilities required for turbulent, transitional, and reacting flow simulations across a broad Mach number regime, and to lay the foundation for the development of a future framework and/or environment where physics-based, accurate predictions of complex turbulent flows, including flow separation, can be accomplished routinely and efficiently in cooperation with other physics-based simulations to enable multi-physics analysis and design. Specific technical requirements from the aerospace industrial and scientific communities were obtained to determine critical capability gaps, anticipated technical challenges, and impediments to achieving the target CFD capability in 2030. A preliminary development plan and roadmap were created to help focus investments in technology development to help achieve the CFD vision in 2030.

Jeffrey P Slotnick↗

DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2011

Direct Numerical Simulations of Transitional/Turbulent Wakes

The interest in transitional/turbulent wakes spans the spectrum from an intellectual pursuit to understand the complex underlying physics to a critical need in aeronautical engineering and other disciplines to predict component/system performance and reliability. Cylinder wakes have been studied extensively over several decades to gain a better understanding of the basic flow phenomena that are encountered in such flows. Experimental, computational and theoretical means have been employed in this effort. While much has been accomplished there are many important issues that need to be resolved. The physics of the very near wake of the cylinder (less than three diameters downstream) is perhaps the most challenging of them all. This region comprises the two detached shear layers, the recirculation region and wake flow. The interaction amongst these three components is to some extent still a matter of conjecture. Experimental techniques have generated a large percentage of the data that have provided us with the current state of understanding of the subject. More recently computational techniques have been used to simulate cylinder wakes, and the data from such simulations are being used to both refine our understanding of such flows as well as provide new insights. A few large eddy and direct numerical simulations (LES and DNS) of cylinder wakes have appeared in the literature in the recent past. These investigations focus on the low Reynolds number range where the cylinder boundary layer is laminar (sub-critical range). However, from an engineering point of view, there is considerable interest in the situation where the upper and/or lower boundary layer of an airfoil is turbulent, and these turbulent boundary layers separate from the airfoil to contribute to the formation of the wake downstream. In the case of cylinders, this only occurs at relatively large unit Reynolds numbers. However, in the case of airfoils, the boundary layer has the opportunity to transition to turbulence on the airfoil surface at a relatively lower unit Reynolds number because the characteristic length of the airfoil is typically one to two orders of magnitude larger than the trailing edge diameter. This transition to turbulence would occur unless there is a strong favorable pressure gradient that results in the boundary layer remaining laminar or transitional over the surface of the airfoil. This presentation will focus on two direct numerical simulations that have been performed at NASA ARC. The first is of a cylinder wake with laminar separating boundary layers. The second is the wake of a flat plate with a circular trailing edge. The upper and lower plate surface boundary layers are both turbulent and statistically identical. Thus the computed wake is symmetric in a statistical sense. This flow is more representative of airfoil wakes than cylinder wakes. Results from the two simulations including flow visualization and turbulence statistics in the near wake will be presented at the seminar.

wakes↗

NASA NTRS2014

Pre-Test CFD for the Design and Execution of the Enhanced Injection and Mixing Project at NASA Langley Research Center

With the increasing costs of physics experiments and simultaneous increase in availability and maturity of computational tools it is not surprising that computational fluid dynamics (CFD) is playing an increasingly important role, not only in post-test investigations, but also in the early stages of experimental planning. This paper describes a CFD-based effort executed in close collaboration between computational fluid dynamicists and experimentalists to develop a virtual experiment during the early planning stages of the Enhanced Injection and Mixing project at NASA Langley Research Center. This projects aims to investigate supersonic combustion ramjet (scramjet) fuel injection and mixing physics, improve the understanding of underlying physical processes, and develop enhancement strategies and functional relationships relevant to flight Mach numbers greater than 8. The purpose of the virtual experiment was to provide flow field data to aid in the design of the experimental apparatus and the in-stream rake probes, to verify the nonintrusive measurements based on NO-PLIF, and to perform pre-test analysis of quantities obtainable from the experiment and CFD. The approach also allowed for the joint team to develop common data processing and analysis tools, and to test research ideas. The virtual experiment consisted of a series of Reynolds-averaged simulations (RAS). These simulations included the facility nozzle, the experimental apparatus with a baseline strut injector, and the test cabin. Pure helium and helium-air mixtures were used to determine the efficacy of different inert gases to model hydrogen injection. The results of the simulations were analyzed by computing mixing efficiency, total pressure recovery, and stream thrust potential. As the experimental effort progresses, the simulation results will be compared with the experimental data to calibrate the modeling constants present in the CFD and validate simulation fidelity. CFD will also be used to investigate different injector concepts, improve understanding of the flow structure and flow physics, and develop functional relationships. Both RAS and large eddy simulations (LES) are planned for post-test analysis of the experimental data.

Drozda, Tomasz G.↗

NASA NTRS1998

Physics of Boundaries and their Interactions in Space Plasmas

This final report describes a brief summary of our accomplishments during the complete contract period. Traditionally, due to computational limitations, it has been impossible to obtain a global view of the magnetosphere on ion time and spatial scales. As a result, kinetic-simulations have concentrated on the local structure of different magnetospheric discontinuities and boundaries. However, due to the emergence of low cost supercomputers, as well as by taking full advantage of latest advances in data mining and visualization technology, we were able to bypass our planned (proposed) regional simulations and proceed to large-scale 3-D and 2-D global hybrid simulations of the magnetosphere. As a result, although we are only finishing the second year of the proposed activity, much of the original scientific objectives have been surpassed and new avenues of investigation have been opened. Such simulations have led us to possible explanations of some long-standing issues in magnetospheric physics. They have also enables us to make a number of important discoveries predictions, which need to be looked for in satellite data. Examples include the finding that the bow shock can become unstable to the Kelvin-Helmholtz (KH), (2) the discovery of a mechanism for intermittent reconnection due to ion physics which may be relevant to the explanation of the recurrence rate of flux transfer events (FTEs), and (3) this finding that the current sheet in the near-Earth magnetotail region can become unstable to KH with detectable, unique ionospheric signatures. Further, we demonstrated a viable mechanism for the onset of reconnection at the magnetopause, examined the detailed structure of the boundary layer incorporating curvature effects, and provided an explanation for the large core fields observed within FTEs as well as flux ropes in the magnetotail.

Omidi, Nojan↗

NASA NTRS2005

Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System (GLDAS) Land Surface States

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly sensitive to precipitation, with differences in spring and summer as large as 45% depending on the choice of precipitation input.

Gottschalck, Jon↗

DOE OSTI2024

Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1996

User Interface Developed for Controls/CFD Interdisciplinary Research

The NASA Lewis Research Center, in conjunction with the University of Akron, is developing analytical methods and software tools to create a cross-discipline "bridge" between controls and computational fluid dynamics (CFD) technologies. Traditionally, the controls analyst has used simulations based on large lumping techniques to generate low-order linear models convenient for designing propulsion system controls. For complex, high-speed vehicles such as the High Speed Civil Transport (HSCT), simulations based on CFD methods are required to capture the relevant flow physics. The use of CFD should also help reduce the development time and costs associated with experimentally tuning the control system. The initial application for this research is the High Speed Civil Transport inlet control problem. A major aspect of this research is the development of a controls/CFD interface for non-CFD experts, to facilitate the interactive operation of CFD simulations and the extraction of reduced-order, time-accurate models from CFD results. A distributed computing approach for implementing the interface is being explored. Software being developed as part of the Integrated CFD and Experiments (ICE) project provides the basis for the operating environment, including run-time displays and information (data base) management. Message-passing software is used to communicate between the ICE system and the CFD simulation, which can reside on distributed, parallel computing systems. Initially, the one-dimensional Large-Perturbation Inlet (LAPIN) code is being used to simulate a High Speed Civil Transport type inlet. LAPIN can model real supersonic inlet features, including bleeds, bypasses, and variable geometry, such as translating or variable-ramp-angle centerbodies. Work is in progress to use parallel versions of the multidimensional NPARC code.

Source record↗

NASA NTRS1995

Unsteady numerical simulations of the stability and dynamics of flames

In this report we describe the research performed at the Naval Research Laboratory in support of the NASA Microgravity Science and Applications Program over the past three years (from Feb. 1992) with emphasis on the work performed since the last microgravity combustion workshop. The primary objective of our research is to develop an understanding of the differences in the structure, stability, dynamics and extinction of flames in earth gravity and in microgravity environments. Numerical simulations, in which the various physical and chemical processes can be independently controlled, can significantly advance our understanding of these differences. Therefore, our approach is to use detailed time-dependent, multi-dimensional, multispecies numerical models to perform carefully designed computational experiments. The basic issues we have addressed, a general description of the numerical approach, and a summary of the results are described in this report. More detailed discussions are available in the papers published which are referenced herein. Some of the basic issues we have addressed recently are (1) the relative importance of wall losses and gravity on the extinguishment of downward-propagating flames; (2) the role of hydrodynamic instabilities in the formation of cellular flames; (3) effects of gravity on burner-stabilized flames, and (4) effects of radiative losses and chemical-kinetics on flames near flammability limits. We have also expanded our efforts to include hydrocarbon flames in addition to hydrogen flames and to perform simulations in support of other on-going efforts in the microgravity combustion sciences program. Modeling hydrocarbon flames typically involves a larger number of species and a much larger number of reactions when compared to hydrogen. In addition, more complex radiation models may also be needed. In order to efficiently compute such complex flames recent developments in parallel computing have been utilized to develop a state-of-the-art parallel flame code. This is discussed below in some detail after a brief discussion of the numerical models.

Kailasanath, K.↗

DOE OSTI2025

Capability in Theory, Modeling, and Validation for a Range of Innovative Fusion Concepts using High-Fidelity Moment-Kinetic Models

A computational modeling capability is created and available to the fusion community to understand and design lower-cost and innovative fusion concepts. The approach uses high- fidelity kinetic, moment-kinetic, and moment models and includes sophisticated plasma- boundary interactions. A majority of fusion-relevant simulations are performed with magnetohydrodynamic models and hybrid particle-in-cell codes, with limited-fidelity electron and kinetic physics. However, in fusion configurations like Z-pinches, field-reversed- configurations, plasma jet magneto-inertial fusion, spinning mirrors, and others, kinetic effects (both electron and ions) are critical to understand the physics and design scaling into the highly kinetic regime of a burning fusion plasma. Furthermore, as present fusion machines move towards a burning plasma regime, liquid-metal blankets are needed to handle first-wall heat- flux, reduce erosion, and eventually for energy conversion and fuel breeding. The work performed under this ARPA-E BETHE Capability Team advances the state-of-the-art in modeling and understanding plasma dynamics in fusion devices and its coupling with liquid-metal dynamics. These are critical areas of research for fusion energy to become realizable. To address these complex problems, we have leveraged and extended computational capabilities through the code, Gkeyll (developed jointly with Princeton Plasma Physics Laboratory and academic partners), for kinetic and moment modeling of fusion plasmas. The Concept Teams supported by this Capability Team include the Wisconsin High-field Axisymmetric Mirror (WHAM), Centrifugal Mirror Experiment (CFME), Plasma-Jet Magneto- Inertial Fusion (PJMIF), and solid and liquid wall plasma-material interaction studies relevant to a number of fusion concepts including Zap Energy’s Z-pinch. This software is open-source and available to the fusion community as a high-fidelity tool for the design of lower-cost fusion experiments. 3D gyrokinetic simulations of WHAM are now possible for long enough time scales to understand the evolution of interchange instabilities. 3D multi-fluid simulations of CMFE at higher Mach numbers are now possible for detailed design iterations with the goal of stability. The state-of-the-art in understanding shock formation and shock mitigation regimes in merging liners for PJMIF have been furthered by our kinetic simulations. Our novel models and frameworks studying plasma-material interaction by incorporating wall emission for various solid wall materials of relevance to pulsed and steady fusion concepts have advanced the state-of-the-art in our understanding of particle fluxes, heat fluxes, and other quantities at cathodes and anodes. The results from this work may explain discrepancies between experimental and theoretical predictions of achieved current densities in pulsed concepts such as Z-pinches. Another significant contribution of this Capability Team is the development and deployment of a novel experimental platform, LEX (Liquid Electrode eXperiment), at Virginia Tech to understand liquid metal free-surface response to electromagnetic pulses. The novel experiments along with model validation quantified the effect of different materials and sizes of liquid metal droplets on the radiative power balance of fusion plasmas for pulsed concepts. Furthermore, these experiments provided mitigation strategies for violent liquid metal response for high current pulses as would be expected in fusion regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Static actuator-sharing algorithm for concurrent control of multiple plasma properties

Simultaneous regulation of multiple properties in next-generation tokamaks like ITER and fusion pilot plant may require the integration of different plasma control algorithms. Such integration requires the conversion of individual controller commands into physical actuator requests while accounting for the coupling between different plasma properties. This work proposes a tokamak and scenario-agnostic actuator-sharing algorithm (ASA) to perform the above-mentioned command-request conversion and, hence, integrate multiple plasma controllers. The proposed algorithm implicitly solves a quadratic programming (QP) problem formulated to account for the saturation limits and the relation between the controller commands and physical actuator requests. Since the constraints arising in the QP program are linear, the proposed ASA is highly computationally efficient and can be implemented in the tokamak plasma control system in real time. Furthermore, the proposed algorithm is designed to handle real-time changes in the control objectives and actuators’ availability. Nonlinear simulations carried out using the Control Oriented Transport SIMulator illustrate the effectiveness of the proposed algorithm in achieving multiple control objectives simultaneously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2017

Comparisons Between NO PLIF Imaging and CFD Simulations of Mixing Flowfields for High-Speed Fuel Injectors

The current work compares experimentally and computationally obtained nitric oxide (NO) planar laser-induced fluorescence (PLIF) images of the mixing flowfields for three types of high-speed fuel injectors: a strut, a ramp, and a rectangular flush-wall. These injection devices, which exhibited promising mixing performance at lower flight Mach numbers, are currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, and improve the understanding of underlying physical processes relevant to flight Mach numbers greater than eight. In the experiments, conducted in the NASA Langley Arc-Heated Scramjet Test Facility (AHSTF), the injectors are placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number air flow at the entrance of a scramjet combustor. Helium is used as an inert substitute for hydrogen fuel. The PLIF is obtained by using a tunable laser to excite the NO, which is present in the AHSTF air as a direct result of arc-heating. Consequently, the absence of signal is an indication of pure helium (fuel). The PLIF images computed from the computational fluid dynamics (CFD) simulations are obtained by combining a fluorescence model for NO with the Reynolds-Averaged Simulation results carried out using the VULCAN-CFD solver to obtain a computational equivalent of the experimentally measured PLIF signal. The measured NO PLIF signal is mainly a function of NO concentration allowing for semi-quantitative comparisons between the CFD and the experiments. The PLIF signal intensity is also sensitive to pressure and temperature variations in the flow, allowing additional flow features to be identified and compared with the CFD. Good agreement between the PLIF and the CFD results provides increased confidence in the CFD simulations for investigations of injector performance.

Drozda, Tomasz, G.↗

NASA NTRS2010

Data-Based Predictive Control with Multirate Prediction Step

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Barlow, Jonathan S.↗