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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Adversarial Sampling-Based Motion Planning

In this report there are many scenarios in which a mobile agent may not want its path to be predictable. Examples include preserving privacy or confusing an adversary. However, this desire for deception can conflict with the need for a low path cost. Optimal plans such as those produced by RRT* may have low path cost, but their optimality makes them predictable. Similarly, a deceptive path that features numerous zig-zags may take too long to reach the goal. We address this trade-off by drawing inspiration from adversarial machine learning. We propose a new planning algorithm, which we title Adversarial RRT*. Adversarial RRT* attempts to deceive machine learning classifiers by incorporating a predicted measure of deception into the planner cost function. Adversarial RRT* considers both path cost and a measure of predicted deceptiveness in order to produce a trajectory with low path cost that still has deceptive properties. We demonstrate the performance of Adversarial RRT*, with two measures of deception, using a simulated Dubins vehicle. We show how Adversarial RRT* can decrease cumulative RNN accuracy across paths to 10%, compared to 46% cumulative accuracy on near-optimal RRT* paths, while keeping path length within 16% of optimal. We also present an example demonstration where the Adversarial RRT* planner attempts to safely deliver a high value package while an adversary observes the path and tries to intercept the package.

42 ENGINEERING↗
DOE OSTI2024

Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, scripts, model files

This model-data archive supports the research paper that demonstrates the integration of agricultural drainage features—specifically, narrow engineered ditches and tile drains—into a fully distributed, basin-scale integrated surface-subsurface hydrology model (ISSHM), Amanzi-ATS. The model employs innovative computational meshes aligned with agricultural ditches and incorporates the physically based Hooghoudt's drainage equation to simulate tile drainage, offering a novel strategy that enhances the accuracy of hydrological simulations.The archived dataset includes input parameters, model configurations, and select simulation outputs for the Amanzi-ATS model that successfully captured the streamflow patterns in the Portage River Watershed as validated by USGS gauge readings. Jupyter notebook for the preparation of model inputs and post-processing of outputs are also included. The model's predictive performance achieved a normalized Kling-Gupta Efficiency (KGE) of 0.81, surpassing SWAT without the necessity for site-specific calibration.The Amanzi-ATS model presented in this modeL-data archive allows for numerical experiments to explore the shifts in the flow structure under different drainage scenarios. As a tool for advancing the understanding of distributed hydrological responses and nutrient cycling, this archived model provides valuable insights for researchers, modelers, and decision-makers involved in watershed management and environmental modeling.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model, are in XML format and can be edited in any commonly used text editors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Evaluating Uncertainties in Marine Biogeochemical Models: Benchmarking Aerosol Precursors

The effort to accurately estimate global radiative forcing has long been hampered by a degree of uncertainty in the tropospheric aerosol contribution. Reducing uncertainty in natural aerosol processes, the baseline of the aerosol budget, thus becomes a fundamental task. The appropriate representation of aerosols in the marine boundary layer (MBL) is essential to reduce uncertainty and provide reliable information on offsets to global warming. We developed an International Ocean Model Benchmarking package to assess marine biogeochemical process representations in Earth System Models (ESMs), and the package was employed to evaluate surface ocean concentrations and the sea–air fluxes of dimethylsulfide (DMS). Model performances were scored based on how well they captured the distribution and variability contained in high-quality observational datasets. Results show that model-data biases increased as DMS enters the MBL, but unfortunately over three-quarters of the models participating in the fifth Coupled Model Intercomparison Project (CMIP5) did not have a dynamic representation of DMS. When it is present, models tend to over-predict sea surface concentrations in the productive region of the eastern tropical Pacific by almost a factor of two, and the sea–air fluxes by a factor of three. Systematic model-data benchmarking as described here will help to identify such deficiencies and subsequently lead to improved subgrid-scale parameterizations and ESM development.

58 GEOSCIENCES↗
DOE OSTI2024

SCALE inventory and reactivity analysis as part of the Hermes 2021 PSAR review

The readiness of SCALE for comprehensive studies of pebble-bed reactors has been demonstrated through detailed analysis of a fluoride salt–cooled, high-temperature pebble-bed reactor (PB-FHR). The methods developed for pebble-bed reactor modeling in SCALE, particularly for inventory generation, have proven effective in gaining insights into the reactor physics of this advanced reactor. Excellent agreement with another code package has been observed, further highlighting SCALE’s strong performance. The SCALE results supported the US Nuclear Regulatory Commission’s construction permit application review of the Hermes low-power PB-FHR demonstration reactor. A SCALE model of the Hermes reactor was developed at Oak Ridge National Laboratory using information from the Preliminary Safety Analysis Report (PSAR) and supplemented with publicly available data. SCALE reactivity coefficient simulations reproduced PSAR results within 1σ statistical uncertainties. Sensitivity studies emphasized the importance of graphite specifications for accurate keff predictions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Mesh-based multiphysics coupling acceleration for fusion neutronics through clustering for fusion blanket applications

Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.

Bae, Jin Whan [ORNL] (ORCID:0000000326548907)↗
DOE OSTI2014

Rapid Monte Carlo simulation of detector DQE(f)

Purpose: Performance optimization of indirect x-ray detectors requires proper characterization of both ionizing (gamma) and optical photon transport in a heterogeneous medium. As the tool of choice for modeling detector physics, Monte Carlo methods have failed to gain traction as a design utility, due mostly to excessive simulation times and a lack of convenient simulation packages. The most important figure-of-merit in assessing detector performance is the detective quantum efficiency (DQE), for which most of the computational burden has traditionally been associated with the determination of the noise power spectrum (NPS) from an ensemble of flood images, each conventionally having 10{sup 7} − 10{sup 9} detected gamma photons. In this work, the authors show that the idealized conditions inherent in a numerical simulation allow for a dramatic reduction in the number of gamma and optical photons required to accurately predict the NPS. Methods: The authors derived an expression for the mean squared error (MSE) of a simulated NPS when computed using the International Electrotechnical Commission-recommended technique based on taking the 2D Fourier transform of flood images. It is shown that the MSE is inversely proportional to the number of flood images, and is independent of the input fluence provided that the input fluence is above a minimal value that avoids biasing the estimate. The authors then propose to further lower the input fluence so that each event creates a point-spread function rather than a flood field. The authors use this finding as the foundation for a novel algorithm in which the characteristic MTF(f), NPS(f), and DQE(f) curves are simultaneously generated from the results of a single run. The authors also investigate lowering the number of optical photons used in a scintillator simulation to further increase efficiency. Simulation results are compared with measurements performed on a Varian AS1000 portal imager, and with a previously published simulation performed using clinical fluence levels. Results: On the order of only 10–100 gamma photons per flood image were required to be detected to avoid biasing the NPS estimate. This allowed for a factor of 10{sup 7} reduction in fluence compared to clinical levels with no loss of accuracy. An optimal signal-to-noise ratio (SNR) was achieved by increasing the number of flood images from a typical value of 100 up to 500, thereby illustrating the importance of flood image quantity over the number of gammas per flood. For the point-spread ensemble technique, an additional 2× reduction in the number of incident gammas was realized. As a result, when modeling gamma transport in a thick pixelated array, the simulation time was reduced from 2.5 × 10{sup 6} CPU min if using clinical fluence levels to 3.1 CPU min if using optimized fluence levels while also producing a higher SNR. The AS1000 DQE(f) simulation entailing both optical and radiative transport matched experimental results to within 11%, and required 14.5 min to complete on a single CPU. Conclusions: The authors demonstrate the feasibility of accurately modeling x-ray detector DQE(f) with completion times on the order of several minutes using a single CPU. Convenience of simulation can be achieved using GEANT4 which offers both gamma and optical photon transport capabilities.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit

Here, extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundation for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Spatial Resolution Characterization for Aerial Digital Imagery

The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration have jointly conducted characterizations of aerial digital imagery from commercial data providers. In a typical scenario, a vendor acquired imagery over the Stennis Space Center test range and provided a common data package to SSC. SSC personnel analyzed the geopositional accuracy and spatial resolution of the images, then documented the characterization results in a report and delivered the report to the USGS. Spatial resolution characterization was based on edge response measurements using one of the SSC edge targets and the tilted-edge technique. Relative Edge Response (RER) has been estimated for aerial digital imagery from several commercial data providers. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale.

Blonski, Slawomir↗
DOE OSTI2022

Phoebe: a high-performance framework for solving phonon and electron Boltzmann transport equations

Understanding the electrical and thermal transport properties of materials is critical to the design of electronics, sensors, and energy conversion devices. Computational modeling can accurately predict material properties but, in order to be reliable, requires accurate descriptions of electron and phonon states and their interactions. While first-principles methods are capable of describing the energy spectrum of each carrier, using them to compute transport properties is still a formidable task, both computationally demanding and memory intensive, requiring integration of fine microscopic scattering details for estimation of macroscopic transport properties. To address this challenge, we present Phoebe—a newly developed software package that includes the effects of electron–phonon, phonon–phonon, boundary, and isotope scattering in computations of electrical and thermal transport properties of materials with a variety of available methods and approximations. This open source C++ code combines MPI-OpenMP hybrid parallelization with GPU acceleration and distributed memory structures to manage computational cost, allowing Phoebe to effectively take advantage of contemporary computing infrastructures. We demonstrate that Phoebe accurately and efficiently predicts a wide range of transport properties, opening avenues for accelerated computational analysis of complex crystals.

36 MATERIALS SCIENCE↗
NASA NTRS2007

Micromechanics of Spray-On Foam Insulation

Understanding the thermo-mechanical response of the Space Shuttle External Tank spray-on foam insulation (SOFI) material is critical, to NASA's Return to Flight effort. This closed-cell rigid polymeric foam is used to insulate the metallic Space Shuttle External Tank, which is at cryogenic temperatures immediately prior to and during lift off. The shedding of the SOFI during ascent led to the loss of the Columbia, and eliminating/minimizing foam lass from the tank has become a priority for NASA as it seeks to resume scheduled space shuttle missions. Determining the nature of the SOFI material behavior in response to both thermal and mechanical loading plays an important role as any structural modeling of the shedding phenomenon k predicated on knowledge of the constitutive behavior of the foam. In this paper, the SOFI material has been analyzed using the High-Fidelity Generalized Method of Cells (HFGMC) micromechanics model, which has recently been extended to admit a triply-periodic 3-D repeating unit cell (RUC). Additional theoretical extensions that mere made in order to enable modeling of the closed-cell-foam material include the ability to represent internal boundaries within the RUC (to simulated internal pores) and the ability to impose an internal pressure within the simulated pores. This latter extension is crucial as two sources contribute to significant internal pressure changes within the SOFI pores. First, gas trapped in the pores during the spray process will expand or contract due to temperature changes. Second, the pore pressure will increase due to outgassing of water and other species present in the foam skeleton polymer material. With HFGMC's new pore pressure modeling capabilities, a nonlinear pressure change within the simulated pore can be imposed that accounts for both of these sources, in addition to stmdar&-thermal and mechanical loading; The triply-periodic HFGMC micromechanics model described above was implemented within NASA GRC's MAC/GMC software package, giving the model access to a range of nonlinear constitutive models for the polymeric foam skeleton material. A repeating unit cell architecture was constructed that, while relatively simple, still accounts for the geometric anisotropy of the porous foam microstructure and its thin walls and thicker edges. With the lack of reliable polymeric foam skeleton materia1 properties, many simulations were executed aimed at backing out these material properties. Then, using these properties, predictions of the thermo-mechanical behavior of the foam, including calculated internal applied pressure profiles, were performed and compared with appropriate experimental data.

Bednarcyk, Brett A.↗
DOE OSTI2021

Developing an Automated Uncertainty Quantification Tool to Improve Watershed-Scale Predictions of Water and Nutrient Cycling

Managing the flow of water, nutrients, and contaminants in watersheds is vital to addressing pressing issues related to water scarcity, access to clean drinking water, energy production, resilience to natural and anthropogenic perturbations, and ecological restoration. Decisions about the management of watersheds critically depend on the accuracy with which the flow of water and chemicals through the watershed can be predicted by computer models. Prediction uncertainty can be reduced by matching the model to data, which are collected in the field at great expense. The contribution of watershed characterization data to reducing uncertainty of relevant model predictions can be evaluated in a so-called data-worth analysis, which provides transparent, quantitative metrics about a data set’s value for the support of relevant watershed management objectives. To achieve this goal, we developed a software package that implements the data-worth analysis approach for use with state-of-the-art watershed models. The purpose of the proposed data-worth analysis is to help decision-makers allocate resources for watershed characterization such that the uncertainty in model predictions can be significantly reduced, which leads to better, more effective management decisions. At the same time, watershed characterization costs can be reduced. The specific technical objectives of this SBIR/STTR Phase II project were to develop a framework and associated software toolsets that implement the uncertainty quantification and data-worth analysis approach for use with state-of-the-art watershed models. This goal was achieved by (A) developing a user-friendly, robust software package that is accessible to a wide audience, including watershed managers, policy-makers, and public stakeholders; (B) by demonstrating application of the prototype on several use cases that are representative of complex watershed management challenges spanning a range of scales and that consider different open-source, DOE-based codes and other modeling platforms; and (C) by gathering information about the needs and requirements from potential users to help guide future developments, ensuring that the final product will be commercially viable. The developed software consists of a graphical user interface that guides the user through a sequence of analysis steps, supported by toolsets that leverage state-of-the-art computational simulation-optimization capabilities. A prototype of the software runs on multiple platforms (PC, Mac, multi-processor Linux environment), is linked to diverse watershed simulators (e.g., ECOSYS, TOUGH2, TOUGHREACT, Amanzi-ATS), performs multiple analysis tasks (predictive simulations, sensitivity analysis, uncertainty analysis, automatic parameter estimation, and data-worth analysis, multicomponent geothermometry), and is readily extensible to include external simulators and analysis tools. The software is being commercialized and will be continually updated to address user needs.

58 GEOSCIENCES↗
DOE OSTI2015

Evaluation of Cooling Conditions for a High Heat Flux Testing Facility Based on Plasma-Arc Lamps

The new Irradiated Material Target Station (IMTS) facility for fusion materials at Oak Ridge National Laboratory (ORNL) uses an infrared plasma-arc lamp (PAL) to deliver incident heat fluxes as high as 27 MW/m 2 . The facility is being used to test irradiated plasma-facing component materials as part of the joint US-Japan PHENIX program. The irradiated samples are to be mounted on molybdenum sample holders attached to a water-cooled copper rod. Depending on the size and geometry of samples, several sample holders and copper rod configurations have been fabricated and tested. As a part of the effort to design sample holders compatible with the high heat flux (HHF) testing to be conducted at the IMTS facility, numerical simulations have been performed for two different water-cooled sample holder designs using the ANSYS FLUENT 14.0 commercial computational fluid dynamics (CFD) software package. The primary objective of this work is to evaluate the cooling capability of different sample holder designs, i.e. to estimate their maximum allowable incident heat flux values. 2D axisymmetric numerical simulations are performed using the realizable k-ε turbulence model and the RPI nucleate boiling model within ANSYS FLUENT 14.0. The results of the numerical model were compared against the experimental data for two sample holder designs tested in the IMTS facility. The model has been used to parametrically evaluate the effect of various operational parameters on the predicted temperature distributions. The results were used to identify the limiting parameter for safe operation of the two sample holders and the associated peak heat flux limits. The results of this investigation will help guide the development of new sample holder designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2000

Noise-Reduction Benefits Analyzed for Over-the-Wing-Mounted Advanced Turbofan Engines

As we look to the future, increasingly stringent civilian aviation noise regulations will require the design and manufacture of extremely quiet commercial aircraft. Also, the large fan diameters of modern engines with increasingly higher bypass ratios pose significant packaging and aircraft installation challenges. One design approach that addresses both of these challenges is to mount the engines above the wing. In addition to allowing the performance trend towards large diameters and high bypass ratio cycles to continue, this approach allows the wing to shield much of the engine noise from people on the ground. The Propulsion Systems Analysis Office at the NASA Glenn Research Center at Lewis Field conducted independent analytical research to estimate the noise reduction potential of mounting advanced turbofan engines above the wing. Certification noise predictions were made for a notional long-haul commercial quadjet transport. A large quad was chosen because, even under current regulations, such aircraft sometimes experience difficulty in complying with certification noise requirements with a substantial margin. Also, because of its long wing chords, a large airplane would receive the greatest advantage of any noise-shielding benefit.

Berton, Jeffrey J.↗
DOE OSTI2017

Ceramic Plugs for Deep Borehole Seals - 17316

In the deep borehole nuclear waste disposal concept, waste packages are emplaced deep in crystalline rock formations under conditions of high pressures, high mineral content water, and elevated temperatures. Well seals and plugs must perform for thousands of years. A novel ceramic plug system under development capitalizes on the thermal energy of thermite mixtures and engineered additives to react and form ceramic-like plugs in place with favorable structural, flow, and geochemical properties. Depending on the ingredients, the reaction can produce aluminosilicates, plagioclase feldspars, or other combinations in crystalline or amorphous forms. Normative mineralogy techniques were applied to predict product mineralogy and evaluate compatibility with host rocks, and showed they are comparable to igneous rock analogs. The results support a tentative geochemical compatibility between these formulations and granitic host rock. Because the reaction produces a significant amount of thermal energy, the thermal/structural/fluid response of the plug and surrounding media was evaluated with the FEHM code. Temperatures near the plug/rock interface are estimated to peak at less than 600 deg. C and cool to near ambient temperature within a day. Rock stresses resulting from the thermal pulse are predicted to be similar to the unconfined compressive strength of granites, and generally lower than triaxial test results. Entrained fluid expansion due to heating was shown to be lower than failure stresses. Little or no failure in the surrounding media would be expected due to the plug formation process. The present efforts are focused on refining the material formulations, evaluating the geochemical and mechanical interactions between the plug and host rock, and testing the plug formation process in scaled granite and basalt masses. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Abatement of ionizing radiation for superconducting quantum devices

Ionizing radiation has been shown to reduce the performance of superconducting quantum circuits. In this report, we evaluate the expected contributions of different sources of ambient radioactivity for typical superconducting qubit experiment platforms. Our assessment of radioactivity inside a typical cryostat highlights the importance of selecting appropriate materials for the experiment components nearest to qubit devices, such as packaging and electrical interconnects. We present a shallow underground facility (30-meter water equivalent) to reduce the flux of cosmic rays and a lead shielded cryostat to abate the naturally occurring radiogenic gamma-ray flux in the laboratory environment. We predict that superconducting qubit devices operated in this facility could experience a reduced rate of correlated multi-qubit errors by a factor of approximately 20 relative to the rate in a typical above-ground, unshielded facility. Finally, we outline overall design improvements that would be required to further reduce the residual ionizing radiation rate, down to the limit of current generation direct detection dark matter experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

ML-based Dimension Reduction Strategies

Deep learning (DL)--based surrogate models have achieved success in various applications in carbon capture and storage (CCS). However, the model training on high-dimensional spaces is computationally expensive and impractical for large-scale and complex geological models, because the models usually contain hundreds of thousands to millions of grid cells, each with a set of parameters. Furthermore, the high cost of generating training data with sufficient variation is another limitation of model training on high-dimensional spaces, which may result in overfitting and reduce the model efficiency and prediction performance. We proposed the workflow incorporating dimension reduction methods and deep learning models, which aim to extract the latent variables of input parameters and output state variables, and then build the mapping function at the latent spaces. The proposed workflow can significantly reduce the computational complexity in solving both forward and inverse problems compared to models trained on high-dimensional spaces. Dimensionality reduction models showed great potential in workflows for fast reservoir simulation, history matching, prior model generation, visualization, and more, ultimately enhancing DL model performance in related SMART Work Packages.

Hosseini, Seyyed↗
DOE OSTI2021

Hydropower Biological Evaluation Toolset Best Practice Guide

Field studies using live fish are necessary for the evaluation of turbine biological performance, but they cannot determine the specific hydraulic conditions or physical stresses experienced by the fish, the locations where deleterious conditions occur, or the specific causes of the biological response. Using the Sensor Fish (SF) sensing technology, this deficiency can be overcome because the SF can be released independently or concurrently with live fish directly into operating infrastructure, and it takes high-frequency measurements of hydraulic conditions such as pressure, acceleration, and rotation acting on a body in situ during downstream passage. The Hydropower Biological Evaluation Tools (HBET; Hou et al. 2018) software package, developed by Pacific Northwest National Laboratory (PNNL), is designed to assemble, organize, and process data collected by the PNNL-developed SF and by live fish. HBET was developed specifically to design SF field studies, process the raw data, and analyze the processed data efficiently and scientifically. Its objectives are to facilitate SF studies focused on characterizing hydraulic conditions and to apply SF data for evaluating the impacts on fish from passage through hydro-structures. HBET allows users to design new studies, analyze data, perform statistical analyses, and evaluate predicted biological responses. It can be used by researchers, turbine designers, hydropower operators, and regulators to evaluate hydro-structures to enhance environmental sustainability in a cost-effective manner.

13 HYDRO ENERGY↗
NASA NTRS2010

Heat Flux and Wall Temperature Estimates for the NASA Langley HIFiRE Direct Connect Rig

An objective of the Hypersonic International Flight Research Experimentation (HIFiRE) Program Flight 2 is to provide validation data for high enthalpy scramjet prediction tools through a single flight test and accompanying ground tests of the HIFiRE Direct Connect Rig (HDCR) tested in the NASA LaRC Arc Heated Scramjet Test Facility (AHSTF). The HDCR is a full-scale, copper heat sink structure designed to simulate the isolator entrance conditions and isolator, pilot, and combustor section of the HIFiRE flight test experiment flowpath and is fully instrumented to assess combustion performance over a range of operating conditions simulating flight from Mach 5.5 to 8.5 and for various fueling schemes. As part of the instrumentation package, temperature and heat flux sensors were provided along the flowpath surface and also imbedded in the structure. The purpose of this paper is to demonstrate that the surface heat flux and wall temperature of the Zirconia coated copper wall can be obtained with a water-cooled heat flux gage and a sub-surface temperature measurement. An algorithm was developed which used these two measurements to reconstruct the surface conditions along the flowpath. Determinations of the surface conditions of the Zirconia coating were conducted for a variety of conditions.

Cuda, Vincent, Jr.↗