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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Review: Flow Electrode Capacitive Deionization for Improved Electrochemical Water Desalination

In many places of the world people have continued to suffer from major droughts and water shortages. With climate change climbing in intensity, these dry conditions will only worsen. With much of the world’s water in the ocean, both saltwater and brackish water have been identified as key water sources. Currently, there are several technologies available for water desalination and treatment such as reverse osmosis, capacitive deionization, electrodialysis, and flow electrode capacitive deionization. This paper will briefly review each of these technologies and propose a new design to improve the current flow electrode capacitive deionization architecture. The new design uses a current collector flow-electrode architecture that has the potential to achieve record thermodynamic energy efficiencies. This formulation is proprietary to Lawrence Livermore National Laboratory.

36 MATERIALS SCIENCE↗
NASA NTRS2002

Better Weather Prediction and Climate Diagnostics Using Rainfall Measurements from Space

Progress in understanding of the role of water in global weather and climate is currently limited by our knowledge of the spatial and temporal variability of primary hydrological fields such as precipitation and evaporation. The Tropical Rainfall Measuring Mission (TRMM) has recently demonstrated that use of microwave-based rainfall observations from space in data assimilation can provide better climate data sets and improve short-range weather forecasting. At NASA, we have been exploring non-traditional approaches to assimilating TRMM Microwave Imager (TMI) and Special Sensor Microwavehager (SSM/I) surface rain rate and latent heating profile information in global systems. In this talk we show that assimilating microwave rain rates using a continuous variational assimilation scheme based on moisture tendency corrections improves quantitative precipitation estimates (QPE) and related clouds, radiation energy fluxes, and large-scale circulations in the Goddard Earth Observing System (GEOS) reanalyses. Short-range forecasts initialized with these improved analyses also yield better QPE scores and storm track predictions for Hurricanes Bonnie and Floyd. We present a status report on current efforts to assimilate convective and stratiform latent heating profile information within the general variational framework of model parameter estimation to seek further improvements. Within the next 5 years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007/2008. Based on what has been learned from TRMM, there is a high degree of confidence that these observations can play a'major role in improving weather forecasts and producing better global datasets for understanding the Earth's water and energy cycle. The key to success is to adopt an integrated approach to retrieval, validation, modeling, and data assimilation in a coordinated end-to-end observation-application program.

Hou, Arthur↗
NASA NTRS2002

LPV Controller Interpolation for Improved Gain-Scheduling Control Performance

In this paper, a new gain-scheduling control design approach is proposed by combining LPV (linear parameter-varying) control theory with interpolation techniques. The improvement of gain-scheduled controllers can be achieved from local synthesis of Lyapunov functions and continuous construction of a global Lyapunov function by interpolation. It has been shown that this combined LPV control design scheme is capable of improving closed-loop performance derived from local performance improvement. The gain of the LPV controller will also change continuously across parameter space. The advantages of the newly proposed LPV control is demonstrated through a detailed AMB controller design example.

Wu, Fen↗
DOE OSTI2023

Enhanced LWR High Burnup Transient Simulation Capabilities to Support AOO Margin Identification

As part of ongoing efforts to support the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s development of a fuel fragmentation, relocation, and dispersal (FFRD) screening methodology, a number of improvements are required for the NEAMS core simulation capabilities, namely the Virtual Environment for Reactor Applications (VERA). Three areas of improvement were identified in VERA which are important for continued development and application of the FFRD screening methodology. First, the FFRD screening methodology will soon be extended to boiling water reactors (BWRs), requiring development and validation of the VERA BWR capabilities. Second, the screening methodology occasionally requires that VERA be used to simulate a transient in addition to nominal operations. Thus, improvements to both accuracy and performance of the VERA transient capabilities are necessary. Third, the VERAOneWay component of VERA is used to develop BISON fuel performance inputs using the rod-by-rod histories calculated by VERA. Prior use of VERAOneWay exposed significant accuracy, robustness, and performance issues with VERAOneWay; these must be addressed for it to be an effective tool in the NEAMS FFRD methodology. This report documents the efforts in FY23 in each of these three areas to enable successful use of VERA and VERAOneWay for FFRD calculations in FY24 and following years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2010

Data Quality Assurance for Supersonic Jet Noise Measurements

The noise created by a supersonic aircraft is a primary concern in the design of future high-speed planes. The jet noise reduction technologies required on these aircraft will be developed using scale-models mounted to experimental jet rigs designed to simulate the exhaust gases from a full-scale jet engine. The jet noise data collected in these experiments must accurately predict the noise levels produced by the full-scale hardware in order to be a useful development tool. A methodology has been adopted at the NASA Glenn Research Center s Aero-Acoustic Propulsion Laboratory to insure the quality of the supersonic jet noise data acquired from the facility s High Flow Jet Exit Rig so that it can be used to develop future nozzle technologies that reduce supersonic jet noise. The methodology relies on mitigating extraneous noise sources, examining the impact of measurement location on the acoustic results, and investigating the facility independence of the measurements. The methodology is documented here as a basis for validating future improvements and its limitations are noted so that they do not affect the data analysis. Maintaining a high quality jet noise laboratory is an ongoing process. By carefully examining the data produced and continually following this methodology, data quality can be maintained and improved over time.

Brown, Clifford A.↗
DOE OSTI2024

Continuous-wave GaAs/AlGaAs quantum cascade laser at 5.7 THz

Design strategies for improving terahertz (THz) quantum cascade lasers (QCLs) in the 5–6 THz range are investigated numerically and experimentally, with the goal of overcoming the degradation in performance that occurs as the laser frequency approaches the Reststrahlen band. Two designs aimed at 5.4 THz were selected: one optimized for lower power dissipation and one optimized for better temperature performance. The active regions exhibited broadband gain, with the strongest modes lasing in the 5.3–5.6 THz range, but with other various modes observed ranging from 4.76 to 6.03 THz. Pulsed and continuous-wave (cw) operation is observed up to temperatures of 117 K and 68 K, respectively. In cw mode, the ridge laser has modes up to 5.71 THz – the highest reported frequency for a THz QCL in cw mode. The waveguide loss associated with the doped contact layers and metallization is identified as a critical limitation to performance above 5 THz.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

FY23 Progress on Computational Modeling of the Water-Based NSTF

This report summarizes the system-level modeling effort by Argonne National Laboratory (Argonne) of the Natural convection Shutdown heat removal Test Facility (NSTF) in FY23. As a continuation of the modeling effort from FY22, this year’s work focuses on improving the RELAP5-3D model developed previously for two-phase flow simulations. The RELAP5-3D model is updated to more accurately capture the heat loss experienced by the facility. The updated model is compared against experimental data for benchmarking purposes of the RELAP5-3D input model. By correctly accounting for heat loss, the updated RELAP5-3D model can now predict the two-phase baseline case more accurately. The onset and the duration of instability are captured well by the model. Furthermore, analyses are performed to better understand the instability mechanism experienced by the flow where the expansion of the boiling boundary in the chimney is studied in details and the fundamental frequencies of the oscillations are obtained. The updated RELAP5-3D model is further compared against four fault conditions, namely the reduction of riser header inlet flow area, depletion of system inventory, blocked riser channels, and static boiling scenario. For each fault condition, minor modifications and tuning are performed to improve the predictions of the model. The purpose of the analyses is to investigate the capability of RELAP5-3D in predicting complex two-phase flows in possible accident scenarios in actual Reactor Cavity Cooling System (RCCS). Overall, the model is able to capture the behaviors and trends of these fault conditions relatively well. Some discrepancies remain between the experimental data and the predictions, many of which are likely due to the differences in the predicted and experimental vapor generation rate. Future work will focus on the continued development of the current RELAP5-3D input model of the NSTF to both improve the accuracy of the model’s predictive capability and continue supporting the experimental program needs. The mutually beneficial relationship between analysis and experimental efforts has become integral to the parent NSTF program, and the greater objective to fully understand and accurately predict the heat removal performance of a full scale RCCS concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Toward Improved Charge Separation through Conformational Control in Copper Coordination Complexes

The continued development of solar energy as a renewable resource necessitates the design and study of new approaches to sustaining photodriven charge separation (CS). To this end, we present a bioinspired approach in which triggered conformational changes are used to control electron transfer (ET) events. We report, photo-induced conformational rearrangements of a ligand are translated into changes in the coordination geometry and environment about a bound metal ion. Taking advantage of the differential coordination properties of Cu I and Cu II , these dynamics facilitate intramolecular ET from Cu I to the ligand to create a CS state. The synthesis and photophysical characterization of CuCl(dpaa R ) (dpaa = dipicolylaminoacetophenone, with R = H and OMe) is presented. These ligands incorporate a fluorophore into their framework that gives rise to a twisted intramolecular charge transfer (TICT) excited state. Excited state ligand twisting provides a tetragonal coordination geometry capable of capturing Cu II in the CS state when an internal ortho-OMe binding site is present (as in dpaaOMe). We employ NMR, IR, EPR, and optical spectroscopies, X-ray diffraction, and electrochemical methods to establish the ground state properties of the Cu I and Cu II complexes. We then investigate the photophysical dynamics of these Cu I complexes via time-resolved photoluminescence (TR-PL), and optical transient absorption (OTA) spectroscopies. We show that relative to controls lacking a TICT-active ligand, the lifetime of the CS state is enhanced ~1000-fold. Further, the presence of the ortho-OMe substituent greatly enhances the lifetime of the TICT* state and biases the coordination environment toward Cu II . The presence of Cu I decreases photoinduced degradation from 14 to <2% but does not result in significant quenching via ET. Factors affecting CS in these systems are discussed, laying the groundwork for our strategy toward solar energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Hyperbranched PDMAEMA-functionalized SiO 2 microparticles: ATRP polymerization and grafting in a continuous flow reactor

Flow chemistry offers high reaction yield, kinetic control, improved safety, reliability, scalability, and greater degree of process control. Herein, hyperbranched polymer-grafted silica microparticles (HP-SMPs) are synthesized in a commercially available flow reactor through atom transfer radical polymerization. Initiator-anchored silica microparticles are obtained by in situ silanization in the flow reactor. Hyperbranched poly[2-(dimethylamino)ethylmethacrylate] chains are grafted onto the initiator-anchored SMPs through inimer–monomer ratio control. To demonstrate the efficiency and universality of this approach in grafting polymers onto SMPs, multiple hyperbranched polymeric structures are obtained by varying the inimer concentration. Dye absorption test is conducted to demonstrate the potential applications of HP-SMPs.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Multi-channel Scaler Cards Improve Data Collection

Scientists interested in exploring the intricacies and dynamics of Earth's climate and ecosystems continually need smaller, lighter instrumentation that can be placed onboard various sensing platforms, such as Unmanned Aerial Vehicles (UAVs). Responding to a need for improved data collection for remote atmospheric measurement systems, ASRC Aerospace Corporation, of Greenbelt, Maryland, developed a series of low-power, highly integrated, multichannel scaler (MCS) cards. The cards were designed to meet the needs of NASA's ground-based and airborne Light Detection and Ranging (LIDAR) photoncounting programs. They can rapidly collect thousands of data points during a continuous scan of the atmosphere.

Source record↗
NASA NTRS2019

Orion Heat Shield Manufacturing Producibility Improvements for the EM-1 Flight Test Program

This paper describes how the Orion program is incorporating improvements in the heat shield design and manufacturing processes reducing programmatic risk and ensuring crew safety in support of NASA’s Exploration Missions. The Orion program successfully completed the EFT-1 flight test in 2014 and is currently developing the EM-1 spacecraft to meet the test objectives of an orbital mission to the moon and return to earth in 2019. Lessons learned from the EFT-1 manufacturing and flight test experience are being incorporated into a wide variety of vehicle systems and manufacturing processes to reduce risk to the Orion missions and flight crew. A critical contributor to crew safety is the heat shield that protects the crew capsule during re-entry through the earth’s atmosphere for return from deep space. The first flight test vehicle, EFT-1, was manufactured and tested in the Neil Armstrong Operations and Checkout (O&C) facility at KSC to demonstrate early risk reduction including the functionality of the Thermal Protection Systems (TPS) for capsule safe return to earth. The approach for the EFT-1 heat shield utilized a low risk approach using Apollo heritage design and manufacturing processes using an Avcoat TPS ablator with a honeycomb substrate to provide a one piece heat shield to meet the mission re-entry heating environments. The manufacturing processes used honeycomb cell injection guns which were redeveloped from the Apollo Lunar Program processes to build the EFT-1 heat shield. The completed heat shield was transported across the country by aircraft to the O&C at KSC for installation onto the capsule. The EFT-1 heat shield successfully performed its mission and experienced ~80% of the re-entry velocity (50% heating rate) for a lunar return for an Exploration Mission. The second flight test vehicle is the EM-1 mission which will have additional flight systems installed to fly to the moon and return. Heat shield design and producibility improvements have been incorporated in the EM-1 vehicle to meet deep space mission and programmatic requirements. The design continues to use the Avcoat material, but in a “block” configuration to enable improvements in the application processes as well as additional improvements in the carrier structure design and manufacturing operations. Incorporating flight test results and producibility improvements from EFT-1 for the heat shield system design and processes have improved the thermal protection capability, improved the producibility, and cost for EM-1 flight test.

Producibility↗
NASA NTRS2023

Soil Moisture and Sea Surface Salinity Derived from Satellite-Borne Sensors

The monitoring of soil moisture and sea surface salinity over the Earth has been profoundly enhanced during the last thirteen years owing to new generation of satellite sensors. L-band radiometry is currently the only technology providing direct measurements of soil moisture, insensitive to surface roughness and distribution of elements in the soil, and the only technology that allows to measure sea surface salinity from space. The SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active Passive) satellite missions resolve global and local variability with a spatial resolution of approximately 43 km, a swath width close to 1000 km, and a sampling time, for each mission, of at least twice every 3 days. These resolutions and samplings can be increased by either merging data from the two sensors, and with complementary informations gathered with other passive or active sensors, or with in situ information at higher spatial resolution. Numerous scientific studies based on the use of this new type of measurement have led to a better understanding and constraint of the processes governing the variability of the water cycle, ocean circulation and the Earth's climate. The continuity of measurements, and the increased spatial and radiometric resolution is critical for fulfilling scientific needs. Future L-band radiometry missions currently being planned in Europe (the Copernicus Imaging Microwave Radiometer), and in China (the Ocean Salinity Mission) should provide better constraint on auxiliary parameters by combining multiple frequencies, but they will not have improved spatial resolution beyond SMOS and SMAP. The temporal continuity with SMOS and SMAP will most likely not be ensured. In parallel, new concepts are being developed to increase spatial resolution of both land and ocean parameters.

J. Boutin↗
NASA NTRS2011

Dynamic Weather Routes: A Weather Avoidance Concept for Trajectory-Based Operations

The integration of convective weather modeling with trajectory automation for conflict detection, trial planning, direct routing, and auto resolution has uncovered a concept that could help controllers, dispatchers, and pilots identify improved weather routes that result in significant savings in flying time and fuel burn. Trajectory automation continuously and automatically monitors aircraft in flight to find those that could potentially benefit from improved weather reroutes. Controllers, dispatchers, and pilots then evaluate reroute options to assess their suitability given current weather and traffic. In today's operations aircraft fly convective weather avoidance routes that were implemented often hours before aircraft approach the weather and automation does not exist to automatically monitor traffic to find improved weather routes that open up due to changing weather conditions. The automation concept runs in real-time and employs two keysteps. First, a direct routing algorithm automatically identifies flights with large dog legs in their routes and therefore potentially large savings in flying time. These are common - and usually necessary - during convective weather operations and analysis of Fort Worth Center traffic shows many aircraft with short cuts that indicate savings on the order of 10 flying minutes. The second and most critical step is to apply trajectory automation with weather modeling to determine what savings could be achieved by modifying the direct route such that it avoids weather and traffic and is acceptable to controllers and flight crews. Initial analysis of Fort Worth Center traffic suggests a savings of roughly 50% of the direct route savings could be achievable.The core concept is to apply trajectory automation with convective weather modeling in real time to identify a reroute that is free of weather and traffic conflicts and indicates enough time and fuel savings to be considered. The concept is interoperable with today's integrated FMS/datalink. Auxiliary(lat/long) waypoints define a minimum delay reroute between current position and a downstream capture fix beyond the weather. These auxiliary waypoints can be uplinked to equipped aircraft and auto-loaded into the FMS. Alternatively, for unequipped aircraft, auxiliary waypoints can be replaced by nearby named fixes, but this could reduce potential savings. The presentation includes an overview of the automation approach and focuses on several cases in terms of potential savings, reroute complexity, best auxiliary waypoint solution vs. named fix solution, and other metrics.

McNally, B. David↗
DOE OSTI2021

Utilizing ensemble learning for performance and power modeling and improvement of parallel cancer deep learning CANDLE benchmarks

Abstract Machine learning (ML) continues to grow in importance across nearly all domains in modeling to learn from data. Often a tradeoff exists between a model's ability to minimize bias and variance. In this article, we utilize ensemble learning to combine linear, nonlinear, and tree‐/rule‐based ML methods to cope with the bias‐variance tradeoff and result in more accurate models. We use the datasets collected for two parallel cancer deep learning CANDLE benchmarks, NT3 and P1B2, to build performance and power models based on hardware performance counters using single‐object and multiple‐objects ensemble learning to identify the most important counters for improvement on the Cray XC40 Theta at Argonne National Laboratory. Based on the insights from these models, we improve the performance and energy of P1B2 and NT3 by optimizing the deep learning environments TensorFlow, Keras, Horovod, and Python under the huge page size of 8 MB. Experimental results show that ensemble learning not only produces more accurate models but also provides more robust performance counter ranking. We achieve up to 61.15% performance improvement and up to 62.58% energy saving for P1B2 and up to 55.81% performance improvement and up to 52.60% energy saving for NT3 on up to 24,576 cores.

Wu, Xingfu↗
DOE OSTI2025

High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Improving the Transportability of a Deep Learning Denoising Model Using Transfer Learning Techniques

The adoption of machine learning techniques in the seismology community has led to great performance improvements in several areas, including signal processing. Specifically, the development of deep learning–based seismic waveform denoising models has the potential to yield improvements in signal detection capabilities for networks operating in particularly noisy environments. Recent advancements in the design of these deep learning denoising models have included the incorporation of continuous and discrete wavelet transform functions into the network architecture to improve the learning capabilities and efficiency of said models. These wavelet transform–based seismic denoising models have shown improved denoising capabilities in regions where there is good agreement between the data features present in the training and evaluation datasets. However, questions remain about the overall transportability of these models to other monitoring regions. Here, in this study, we will determine the baseline transportability of a newly developed multilevel wavelet‐transform convolutional neural network (MWCNN) seismic denoising model. We accomplish this by taking a version of the MWCNN denoising model trained on data collected from the Utah region and evaluating its denoising performance on datasets collected from the neighboring Nevada region, which differ with regard to monitoring sensor types and event histories. We find that there is a notable variability in denoising performance related to the degree of similarity between the initial and new target datasets. The most notable difference in denoising performance is the ability of the denoising model to preserve accurate amplitude information associated with the signal energy present in the waveform data. Finally, we evaluate the ability of transfer learning techniques to improve the transportability of the MWCNN denoising model. We find that although there is still a performance gap present in the denoising results of the MWCNN model, transfer learning did yield improved results.

Quinones, Louis [Sandia National Laboratories (SNL↗
NASA NTRS1990

Multiversion software reliability through fault-avoidance and fault-tolerance

In this project we have proposed to investigate a number of experimental and theoretical issues associated with the practical use of multi-version software in providing dependable software through fault-avoidance and fault-elimination, as well as run-time tolerance of software faults. In the period reported here we have working on the following: We have continued collection of data on the relationships between software faults and reliability, and the coverage provided by the testing process as measured by different metrics (including data flow metrics). We continued work on software reliability estimation methods based on non-random sampling, and the relationship between software reliability and code coverage provided through testing. We have continued studying back-to-back testing as an efficient mechanism for removal of uncorrelated faults, and common-cause faults of variable span. We have also been studying back-to-back testing as a tool for improvement of the software change process, including regression testing. We continued investigating existing, and worked on formulation of new fault-tolerance models. In particular, we have partly finished evaluation of Consensus Voting in the presence of correlated failures, and are in the process of finishing evaluation of Consensus Recovery Block (CRB) under failure correlation. We find both approaches far superior to commonly employed fixed agreement number voting (usually majority voting). We have also finished a cost analysis of the CRB approach.

Vouk, Mladen A.↗
NASA NTRS1999

Fracture Toughness and Reliability in High-Temperature Structural Ceramics and Composites: Prospects and Challenges for the 21st Century

The importance of high fracture toughness and reliability in Si3N4, and SiC-based structural ceramics and ceramic matrix composites is reviewed. The potential of these ceramics and ceramic matrix composites for high temperature applications in defense and aerospace applications such as gas turbine engines, radomes, and other energy conversion hardware have been well recognized. Numerous investigations were pursued to improve fracture toughness and reliability by incorporating various reinforcements such as particulate-, whisker-, and continuous fiber into Si3N4 and SiC matrices. All toughening mechanisms, e.g. crack deflection, crack branching, crack bridging, etc., essentially redistribute stresses at the crack tip and increase the energy needed to propagate a crack through the composite material, thereby resulting in improved fracture toughness and reliability. Because of flaw insensitivity, continuous fiber reinforced ceramic composite (CFCC) was found to have the highest potential for higher operating temperature and longer service conditions. However, the ceramic fibers should display sufficient high temperature strength and creep resistance at service temperatures above 1000 'C. The greatest challenge to date is the development of high quality ceramic fibers with associate coatings able to maintain their high strength in oxidizing environment at high temperature. In the area of processing, critical issues are, preparation of optimum matrix precursors, precursor infiltration into fiber array, and matrix densification at a temperature, where grain crystallization and fiber degradation do not occur. A broad scope of effort is required for improved processing and properties with a better understanding of all candidate composite systems.

Dutta, Sunil↗