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NASA NTRS2007

CFD Modeling of Helium Pressurant Effects on Cryogenic Tank Pressure Rise Rates in Normal Gravity

A recently developed computational fluid dynamics modeling capability for cryogenic tanks is used to simulate both self-pressurization from external heating and also depressurization from thermodynamic vent operation. Axisymmetric models using a modified version of the commercially available FLOW-3D software are used to simulate actual physical tests. The models assume an incompressible liquid phase with density that is a function of temperature only. A fully compressible formulation is used for the ullage gas mixture that contains both condensable vapor and a noncondensable gas component. The tests, conducted at the NASA Marshall Space Flight Center, include both liquid hydrogen and nitrogen in tanks with ullage gas mixtures of each liquid's vapor and helium. Pressure and temperature predictions from the model are compared to sensor measurements from the tests and a good agreement is achieved. This further establishes the accuracy of the developed FLOW-3D based modeling approach for cryogenic systems.

Grayson, Gary↗

NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model-Based Engineering

The emergence of model-based engineering is transforming design and analysis methodologies [5]. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses [1], GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System

NASA↗

NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model Based Engineering

Model Based Engineering↗

DOE OSTI2018

Structural Health Monitoring of Nuclear Spent Fuel Storage Facilities

Interim storage of spent nuclear fuel from reactor sites has gained additional importance and urgency for resolving waste-management-related technical issues. To ensure that nuclear power remains clean energy, monitoring has been identified by DOE as a high priority cross-cutting need, necessary to determine and predict the degradation state of the systems, structures, and components (SSCs) important to safety (ITS). Therefore, nondestructive structural condition monitoring becomes a need to be installed on existing or to be integrated into future storage system to quantify the state of health or to guarantee the safe operation of nuclear power plants (NPPs) during their extended life span. In this project, the lead university and the collaborating national laboratory teamed to develop a nuclear structural health monitoring (n-SHM) system based on in-situ piezoelectric sensing technologies that can monitor structural degradation and aging for nuclear spent fuel DCSS and similar structures. We also aimed to identify and quantify possible influences of nuclear spent fuel environment (temperature and radiation) to the piezoelectric sensor system and come up with adequate solutions and guidelines therefore. We have therefore developed analytical model for piezoelectric based n-SHM methods, with considerations of temperature and irradiation influence on the model of sensing and algorithms in acoustic emission (AE), guided ultrasonic waves (GUW), and electromechanical impedance spectroscopy (EMIS). On the other side, experimentally the temperature and irradiation influence on the piezoelectric sensors and sensing capabilities were investigated. Both short-term and long-term irradiation investigation with our collaborating national laboratory were performed. Moreover, we developed multi-modal sensing, validated in laboratory setup, and conducted the testing on the We performed multi-modal sensing development, verification and validation tests on very complex structures including a medium-scale vacuum drying chamber and a small-scale mockup canister available for the desired testing. Our work developed the potential candidate for long term structural health monitoring of spent fuel canister through piezoelectric wafer sensors and provided the sensing methodologies based on AE and GUW methodologies. It overall provides an innovative system and methodology for enhancing the safe operation of nuclear power plant. All major accomplishments planned in the original proposal were successfully achieved.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1997

Extension of a Kolmogorov Atmospheric Turbulence Model for Time-Based Simulation Implementation

The development of any super/hypersonic aircraft requires the interaction of a wide variety of technical disciplines to maximize vehicle performance. For flight and engine control system design and development on this class of vehicle, realistic mathematical simulation models of atmospheric turbulence, including winds and the varying thermodynamic properties of the atmosphere, are needed. A model which has been tentatively selected by a government/industry group of flight and engine/inlet controls representatives working on the High Speed Civil Transport is one based on the Kolmogorov spectrum function. This report compares the Dryden and Kolmogorov turbulence forms, and describes enhancements that add functionality to the selected Kolmogorov model. These added features are: an altitude variation of the eddy dissipation rate based on Dryden data, the mapping of the eddy dissipation rate database onto a regular latitude and longitude grid, a method to account for flight at large vehicle attitude angles, and a procedure for transitioning smoothly across turbulence segments.

McMinn, John D.↗

NASA NTRS2020

Demonstrating Assurance of Model-Based Fault Diagnosis Systems on an Operational Mission

Developers of robotic scientific and commercial spacecraft are trending towards use of onboard autonomous capabilities for responding quickly to dynamic environments and rapidly changing situations. These capabilities need to know the state of the spacecraft’s health. Model-based fault diagnosis (MBFD) is an approach to estimating health by continuously verifying accurate behavior and diagnosing off-nominal behavior. Proper functioning of MBFD depends on 1) the quality of the diagnostic system model that is analyzed and compared to commands and onboard measurements to estimate a system’s health state, and 2) the correct functionality of the diagnosis engine interrogating the model and comparing its analyses to observed system behavior. Our goal is to develop Verification and Validation (V&V) techniques for MBFD to provide future missions sufficient confidence in its functionality and performance to deploy it on the systems they develop. Our work has been focused on infusing the techniques we developed earlier to an operational mission. First, we are constructing diagnostic models of a spacecraft attitude control system and updating our diagnostic engine so they can be demonstrated aboard the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, an operational spacecraft for which experiments in autonomy are being planned and executed, using the V&V techniques we have previously developed to assure they are both correct and complete. Since it is nearing the end of its life, ASTERIA provides a unique opportunity to demonstrate MBFD since the monitored components are expected to fail. Our demonstration will give system developers additional confidence to make timely, informed MBFD deployment decisions. Second, we will be completing performance assessments of the diagnostic engine/diagnostic model ensemble both on the flight system and ground-based testbeds to gain confidence in MBFD’s ability to run successfully in a spacecraft’s resource-constrained environment without adversely affecting other on-board activities. Finally, we are capturing our experience in preparing this demonstration in a set of checklists and guidance documents. Current practice includes high-level institutional guidance documents and standards, but at a high level of abstraction that does not necessarily address specific MBFD concerns. The purpose of the new checklists is to provide future mission developers clear, unambiguous, procedure-oriented guidance on assuring MBFD. This paper describes our work in these areas. For the first area, we describe the diagnostic models and updated diagnostic engine that will be used for the on-board demonstration. We describe how the V&V techniques we developed earlier are used to assure model and engine correctness and completeness. For the second area, we identify the performance measurement and assessment techniques used to characterize the diagnostic engine and diagnostic models, and discuss the effect of measured performance on overall mission operation. Finally, we present the checklist and guidance documents and describe how they meet the goals of providing system developers with clear, unambiguous, procedure-oriented guidance on MBFD assurance. We show how the techniques we have developed map into those artifacts.

Nikora, Allen↗

NASA NTRS1985

The blackboard model - A framework for integrating multiple cooperating expert systems

The use of an artificial intelligence (AI) architecture known as the blackboard model is examined as a framework for designing and building distributed systems requiring the integration of multiple cooperating expert systems (MCXS). Aerospace vehicles provide many examples of potential systems, ranging from commercial and military aircraft to spacecraft such as satellites, the Space Shuttle, and the Space Station. One such system, free-flying, spaceborne telerobots to be used in construction, servicing, inspection, and repair tasks around NASA's Space Station, is examined. The major difficulties found in designing and integrating the individual expert system components necessary to implement such a robot are outlined. The blackboard model, a general expert system architecture which seems to address many of the problems found in designing and building such a system, is discussed. A progress report on a prototype system under development called DBB (Distributed BlackBoard model) is given. The prototype will act as a testbed for investigating the feasibility, utility, and efficiency of MCXS-based designs developed under the blackboard model.

Erickson, W. K.↗

NASA NTRS2011

A Stochastic Model of Space Radiation Transport as a Tool in the Development of Time-Dependent Risk Assessment

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and heavy ions that have been studied at the NASA Space Radiation Laboratory (NSRL) [1] for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of heavy ions in tissue and shielding materials is made with a stochastic approach that includes both ion track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model [2]. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections

Kim, Myung-Hee Y.↗

DOE OSTI2023

Hydrogen Storage System Modeling: Public Access, Maintenance, and Enhancements

The hydrogen storage system modeling project aims to develop new and enhance existing material-based hydrogen storage system models and make them accessible to the research community through a public web page. Updating existing storage systems models supports material developers in evaluating the performance of their new materials in mobile and stationary applications relative to the available DOE Technical Targets. Developing new tools helps researchers evaluate the performance of hydrogen storage materials developed under HyMARC activities or other fundamental hydrogen storage materials discovery research. New models will also work for validating alternatives to material-based systems (liquefied & gaseous hydrogen), comparing various mobile and stationary use cases, and expand to include medium-, heavy-duty, and mining vehicles and stationary application(s).

AMR↗

NASA NTRS1993

A finite-element-based perturbation model for the rotordynamic analysis of shrouded pump impellers: Part 1: Model development and applications

This study concerns the rotor dynamic characteristics of fluid-encompassed rotors, with special emphasis on shrouded pump impellers. The core of the study is a versatile and categorically new finite-element-based perturbation model, which is based on a rigorous flow analysis and what we have generically termed the 'virtually' deformable finite-element approach. The model is first applied to the case of a smooth annular seal for verification purposes. The rotor excitation components, in this sample problem, give rise to a purely cylindrical, purely conical, and a simultaneous cylindrical/conical rotor whirl around the housing centerline. In all cases, the computed results are compared to existing experimental and analytical data involving the same seal geometry and operating conditions. Next, two labyrinth-seal configurations, which share the same tooth-to-tooth chamber geometry but differ in the total number of chambers, were investigated. The results, in this case, are compared to experimental measurements for both seal configurations. The focus is finally shifted to the shrouded-impeller problem, where the stability effects of the leakage flow in the shroud-to-housing secondary passage are investigated. To this end, the computational model is applied to a typical shrouded-impeller pump stage, fabricated and rotor dynamically tested by Sulzer Bros., and the results compared to those of a simplified 'bulk-flow' analysis and Sulzer Bros.' test data. In addition to assessing the computed rotor dynamic coefficients, the shrouded-impeller study also covers a controversial topic, namely that of the leakage-passage inlet swirl, which was previously cited as the origin of highly unconventional (resonance-like) trends of the fluid-exerted forces. In order to validate this claim, a 'microscopic' study of the fluid/shroud interaction mechanism is conducted, with the focus being on the structure of the perturbed flow field associated with the impeller whirl. The conclusions of this study were solidified by the outcome of a numerical-certainty exercise, where the grid dependency of the numerical results is objectively examined. The final phase of the shrouded-impeller investigation involves the validation of a built-in assumption, in all other perturbation models, whereby single-harmonic tangential distributions of all the flow thermophysical properties are imposed. The last phase of the investigation course is aimed at verifying the fine details of the perturbed flow field in light of recent set of detailed LDA measurements in a smooth annular seal. Grid dependency of the fluid-induced forces is also investigated, and specific recommendations are made.

Baskharone, Erian A.↗

NASA NTRS2005

MRI-Based Computational Fluid Dynamics in Experimental Vascular Models: Toward the Development of an Approach for Prediction of Cardiovascular Changes During Prolonged Space Missions

A priority of NASA is to identify and study possible risks to astronauts health during prolonged space missions [l]. The goal is to develop a procedure for a preflight evaluation of the cardiovascular system of an astronaut and to forecast how it will be affected during the mission. To predict these changes, a computational cardiovascular model must be constructed. Although physiology data can be used to make a general model, a more desirable subject-specific model requires anatomical, functional, and flow data from the specific astronaut. MRI has the unique advantage of providing images with all of the above information, including three-directional velocity data which can be used as boundary conditions in a computational fluid dynamics (CFD) program [2,3]. MRI-based CFD is very promising for reproduction of the flow patterns of a specific subject and prediction of changes in the absence of gravity. The aim of this study was to test the feasibility of this approach by reconstructing the geometry of MRI-scanned arterial models and reproducing the MRI-measured velocities using CFD simulations on these geometries.

Spirka, T. A.↗

DOE OSTI2014

Prediction of U-Mo dispersion nuclear fuels with Al-Si alloy using artificial neural network

Dispersion nuclear fuels, consisting of U-Mo particles dispersed in an Al-Si matrix, are being developed as fuel for research reactors. The equilibrium relationship for a mixture component can be expressed in the phase diagram. It is important to analyze whether a mixture component is in equilibrium phase or another phase. The purpose of this research it is needed to built the model of the phase diagram, so the mixture component is in the stable or melting condition. Artificial neural network (ANN) is a modeling tool for processes involving multivariable non-linear relationships. The objective of the present work is to develop code based on artificial neural network models of system equilibrium relationship of U-Mo in Al-Si matrix. This model can be used for prediction of type of resulting mixture, and whether the point is on the equilibrium phase or in another phase region. The equilibrium model data for prediction and modeling generated from experimentally data. The artificial neural network with resilient backpropagation method was chosen to predict the dispersion of nuclear fuels U-Mo in Al-Si matrix. This developed code was built with some function in MATLAB. For simulations using ANN, the Levenberg-Marquardt method was also used for optimization. The artificial neural network is able to predict the equilibrium phase or in the phase region. The develop code based on artificial neural network models was built, for analyze equilibrium relationship of U-Mo in Al-Si matrix.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Multiscale Modeling of Deformation, Fracture and Failure of Fusion Materials and Structures Final Report

The main objective of the research performed at UCLA under grant number DE-FG02-03ER54708 was to develop a physical understanding of the underlying mechanisms that control high-temperature deformation and fracture of fusion structural materials. The key aspect is the synergistic interaction between thermo-mechanical damage phenomena (e.g. creep, fatigue, and fracture), and irradiation damage phenomena (helium and hydrogen bubbles, and irradiation-induced defects). Another thrust area of the research was on the development of constitutive equations for the mechanical behavior of irradiated structures in fusion components (mainly the First Wall and Plasma-Facing components), and in utilizing them in descriptions in large-scale Finite Element Modeling of fusion structures. A parallel experimental effort on thermo-mechanical and plasma-induced damage is designed to validate and confront the developed theoretical and computational predictions. The models have been experimentally validated through experimental tests in simulated plasma transients on specially-designed W samples. This grant started at UCLA on November 14, 2003 and has had successive continuations till November 14, 2017. Research performed under the grant was to develop a range of hierarchical models for the post-elastic deformation, fracture and failure of fusion structural materials. The developed multiscale modeling approach has been based on rigorous mathematical, physical, and computational methods at the forefront of computational materials science. At the fundamental and smallest length scale (nm-μm), we developed advanced rate theory and Monte Carlo approaches to model microstructure evolution, non-equilibrium phase transformations, and dislocation-defect interactions. Microscopic and mesoscopic models of radiation hardening, ductile-to-brittle-transition, post-elastic deformation, plastic instabilities, and fracture processes are based on Dislocation Dynamics (DD) and Grain Growth Dynamics (GGD). At the continuum level, we focused on modeling fracture and failure mechanisms for Virtual Integrated Testing (VISTA), and for understanding the limits of both materials-by-design versus structural component design through advancing the new approach of multiscale-multiphysics. The overall research has been strongly coupled with the U.S. national experimental program to ascertain and verify the range of investigated phenomena. In the following, we give a summary of research progress supported by this grant since its inception till November 14, 2017. Detailed research results are available in our publications, listed in the publications section of this report.

36 MATERIALS SCIENCE↗

NASA NTRS1997

High Temperature Degradation Mechanisms in Polymer Matrix Composites

Polymer matrix composites are increasingly used in demanding structural applications in which they may be exposed to harsh environments. The durability of such materials is a major concern, potentially limiting both the integrity of the structures and their useful lifetimes. The goal of the current investigation is to develop a mechanism-based model of the chemical degradation which occurs, such that given the external chemical environment and temperatures throughout the laminate, laminate geometry, and ply and/or constituent material properties, we can calculate the concentration of diffusing substances and extent of chemical degradation as functions of time and position throughout the laminate. This objective is met through the development and use of analytical models, coupled to an analysis-driven experimental program which offers both quantitative and qualitative information on the degradation mechanism. Preliminary analyses using coupled diffusion/reaction model are used to gain insight into the physics of the degradation mechanisms and to identify crucial material parameters. An experimental program is defined based on the results of the preliminary analysis which allows the determination of the necessary material coefficients. Thermogravimetric analyses are carried out in nitrogen, air, and oxygen to provide quantitative information on thermal and oxidative reactions. Powdered samples are used to eliminate diffusion effects. Tests in both inert and oxidative environments allow the separation of thermal and oxidative contributions to specimen mass loss. The concentration dependency of the oxidative reactions is determined from the tests in pure oxygen. Short term isothermal tests at different temperatures are carried out on neat resin and unidirectional macroscopic specimens to identify diffusion effects. Mass loss, specimen shrinkage, the formation of degraded surface layers and surface cracking are recorded as functions of exposure time. Geometry effects in the neat resin, and anisotropic diffusion effects in the composites, are identified through the use of specimens with different aspect ratios. The data is used with the model to determine reaction coefficients and effective diffusion coefficients. The empirical and analytical correlations confirm the preliminary model results which suggest that mass loss at lower temperatures is dominated by oxidative reactions and that these reaction are limited by diffusion of oxygen from the surface. The mechanism-based model is able to successfully capture the basic physics of the degradation phenomena under a wide range of test conditions. The analysis-based test design is successful in separating out oxidative, thermal, and diffusion effects to allow the determination of material coefficients. This success confirms the basic picture of the process; however, a more complete understanding of some aspects of the physics are required before truly predictive capability can be achieved.

Cunningham, Ronan A.↗

DOE OSTI2019

Nuclear Thermal Propulsion Dynamic Modeling with Modelica

Oak Ridge National Laboratory (ORNL) is participating in the nuclear thermal propulsion (NTP) research and development effort supported by the National Aeronautics and Space Administration (NASA). This effort involves collaboration between multiple research groups, representing various government agencies and industry partners. ORNL has developed a Modelica-based modeling package for dynamic system modeling of nuclear reactors called the Transient Simulation Framework of Reconfigurable Models (TRANSFORM). While this software has been successfully demonstrated in simulations of traditional pressurized-water reactors, boiling-water reactors, liquid-metal reactors and molten-salt reactors, it has also been adapted for non-traditional use in modeling hybrid energy systems, and tritium transport. This versatility is being applied to the current NTP project, where specific modules within TRANSFORM are being developed for and applied to transient modeling of the NASA NTP design. This paper presents the current state of the ORNL-NTP model, the utility of TRANSFORM methodologies in NTP transient simulations, the ability to develop NTP-specific modules, and future work for the model.

Rader, Jordan↗

DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2013

A Novel Zr-1Nb Alloy and a New Look at Hydriding

A novel Zr-1Nb has begun development based on a working model that takes into account the hydrogen permeabilities for zirconium and niobium metals. The beta-Nb secondary phase particles (SPPs) in Zr-1Nb are believed to promote more rapid hydrogen dynamics in the alloy in comparison to other zirconium alloys. Furthermore, some hydrogen release is expected at the lower temperatures corresponding to outages when the partial pressure of H2 in the coolant is less. These characteristics lessen the negative synergism between corrosion and hydriding that is otherwise observed in cladding alloys without niobium. In accord with the working model, development of nanoscale precursors was initiated to enhance the performance of existing Zr-1Nb alloys. Their characteristics and properties can be compared to oxide-dispersion strengthened alloys, and material additions have been proposed to zirconium-based LWR cladding to guard further against hydriding and to fix the size of the SPPs for microstructure stability enhancements. A preparative route is being investigated that does not require mechanical alloying, and 10 nanometer molybdenum particles have been prepared which are part of the nanoscale precursors. If successful, the approach has implications for long term dry storage of used fuel and for new routes to nanoferritic and ODS alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1996

High Temperature Degradation Mechanisms in Polymer Matrix Composites

Polymer matrix composites are increasingly used in demanding structural applications in which they may be exposed to harsh environments. The durability of such materials is a major concern, potentially limiting both the integrity of the structures and their useful lifetimes. The goal of the current investigation is to develop a mechanism-based model of the chemical degradation which occurs, such that given the external chemical environment and temperatures throughout the laminate, laminate geometry, and ply and/or constituent material properties, we can calculate the concentration of diffusing substances and extent of chemical degradation as functions of time and position throughout the laminate. This objective is met through the development and use of analytical models, coupled to an analysis-driven experimental program which offers both quantitative and qualitative information on the degradation mechanism. Preliminary analyses using a coupled diffusion/reaction model are used to gain insight into the physics of the degradation mechanisms and to identify crucial material parameters. An experimental program is defined based on the results of the preliminary analysis which allows the determination of the necessary material coefficients. Thermogravimetric analyses are carried out in nitrogen, air, and oxygen to provide quantitative information on thermal and oxidative reactions. Powdered samples are used to eliminate diffusion effects. Tests in both inert and oxidative environments allow the separation of thermal and oxidative contributions to specimen mass loss. The concentration dependency of the oxidative reactions is determined from the tests in pure oxygen. Short term isothermal tests at different temperatures are carried out on neat resin and unidirectional macroscopic specimens to identify diffusion effects. Mass loss, specimen shrinkage, the formation of degraded surface layers and surface cracking are recorded as functions of exposure time. Geometry effects in the neat resin, and anisotropic diffusion effects in the composites, are identified through the use of specimens with different aspect ratios. The data is used with the model to determine reaction coefficients and effective diffusion coefficients. The empirical and analytical correlations confirm the preliminary model results which suggest that mass loss at lower temperatures is dominated by oxidative reactions and that these reaction are limited by diffusion of oxygen from the surface. The mechanism-based model is able to successfully capture the basic physics of the degradation phenomena under a wide range of test conditions. The analysis-based test design is successful in separating out oxidative, thermal, and diffusion effects to allow the determination of material coefficients. This success confirms the basic picture of the process; however, a more complete understanding of some aspects of the physics are required before truly predictive capability can be achieved.

Cunningham, Ronan A.↗