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At least 703 records · Page 39

Lifing of Engine Components

The successful development of advanced aerospace engines depends greatly on the capabilities of high performance materials and structures. Advanced materials, such as nickel based single crystal alloys, metal foam, advanced copper alloys, and ceramics matrix composites, have been engineered to provide higher engine temperature and stress capabilities. Thermal barrier coatings have been developed to improve component durability and fuel efficiency, by reducing the substrate hot wall metal temperature and protecting against oxidation and blanching. However, these coatings are prone to oxidation and delamination failures. In order to implement the use of these materials in advanced engines, it is necessary to understand and model the evolution of damage of the metal substrate as well as the coating under actual engine conditions. The models and the understanding of material behavior are utilized in the development of a life prediction methodology for hot section components. The research activities were focused on determining the stress and strain fields in an engine environment under combined thermo-mechanical loads to develop life prediction methodologies consistent with the observed damage formation of the coating and the substrates.

Source record↗

Shuttle Return To Flight Experimental Results: Cavity Effects on Boundary Layer Transition

The effect of an isolated rectangular cavity on hypersonic boundary layer transition of the windward surface of the Shuttle Orbiter has been experimentally examined in the Langley Aerothermodynamics Laboratory in support of an agency-wide effort to prepare the Shuttle Orbiter for return to flight. This experimental study was initiated to provide a cavity effects database for developing hypersonic transition criteria to support on-orbit decisions to repair a damaged thermal protection system. Boundary layer transition results were obtained using 0.0075-scale Orbiter models with simulated tile damage (rectangular cavities) of varying length, width, and depth. The database contained within this report will be used to formulate cavity-induced transition correlations using predicted boundary layer edge parameters.

Liechty, Derek S.↗

Progressive Damage Failure Analysis of a Multi-Stringer Post-Buckled Panel

Validation of a progressive damage finite element analysis model using the CompDam material model was performed on a large multi-stringer panel subjected to compressive loading. The panel had a Teflon insert embedded between the skin panel and stiffener to cause an ultimate failure mode of stiffener separation. The compressive loading of the panel caused the skin between the stiffeners to locally buckle before any damage began to occur. The post-buckled behavior of the panel was the driving mechanism to the onset of damage and the damage growth that led to skin-stiffener separation. An integrated global-local modeling approach was used to validate several aspects the overall behavior of the panel from start to failure. The global region captured the pre-buckled stiffness of the test panel within 10% and the buckling load of the skin panel at the critical location within 2%. The skin’s five half-wave buckled mode shape was accurately predicted by the model. The integrated local model captured the load corresponding to the onset of damage within 5% of the average test data. Comparisons are made for key aspects of the damage morphology, such as a growth pattern that included a significant matrix split in the first ply of the skin and a migration of the delamination from the skin-stiffener interface to the skin’sply1-ply2 interface. The ultimate failure mode was shown to be an unstable growth of delamination damage under the stiffeners which led to a peak load of the analysis that was approximately 5% above the average peak load of the testing. The validated global-local modeling approach used on the multi-stringer post-buckled panel with a Teflon insert used a methodology and lessons learned using smaller specimens applied to a subcomponent that captured several aspects of a modern aircraft design.

Jason Action↗

Statistical and Machine Learning Approaches to Analyzing Pipeline Incidents in the United States (2010–2024)

This study applies machine learning methods to analyze natural gas pipeline incidents in the United States using the Pipeline and Hazardous Materials Safety Administration (PHMSA) Gas Distribution Incident Dataset (2010–2024). The dataset includes over 600 variables describing incident characteristics, infrastructure attributes, and contributing factors associated with unintentional gas releases. The objective is to assess whether these features can reliably predict the underlying cause of pipeline failures. Multinomial logistic regression and Random Forest models were developed to classify incident causes, including excavation damage, corrosion, equipment failure, and natural forces. Results show that excavation damage is both the most frequent and most predictable cause, with models achieving strong performance for this category. However, when excavation damage is excluded, model accuracy declines significantly, with some models performing near random levels. Across all approaches, severe class imbalance and limited variability in key predictors constrain predictive performance. Pipeline age and diameter emerge as the most influential variables, but they provide insufficient discriminatory power to distinguish among less frequent failure types. These findings indicate that non-excavation-related incidents are rare, heterogeneous, and weakly represented in the dataset, limiting the effectiveness of machine learning classification. Overall, this study highlights the structural limitations of the PHMSA dataset for predictive modeling and underscores the need for improved data balance and feature enrichment. The results reinforce excavation damage prevention as the most impactful strategy for reducing pipeline incidents.

03 NATURAL GAS↗

On The Development of Biophysical Models for Space Radiation Risk Assessment

Experimental techniques in molecular biology are being applied to study biological risks from space radiation. The use of molecular assays presents a challenge to biophysical models which in the past have relied on descriptions of energy deposition and phenomenological treatments of repair. We describe a biochemical kinetics model of cell cycle control and DNA damage response proteins in order to model cellular responses to radiation exposures. Using models of cyclin-cdk, pRB, E2F's, p53, and GI inhibitors we show that simulations of cell cycle populations and GI arrest can be described by our biochemical approach. We consider radiation damaged DNA as a substrate for signal transduction processes and consider a dose and dose-rate reduction effectiveness factor (DDREF) for protein expression.

Cucinotta, F. A.↗

Inference of phase field fracture models

The phase field approach to modeling fracture uses a diffuse damage field to represent cracks. This representation mollifies singularities that arise in computations with sharp interface models and some of the resultant difficulties in the mathematical and numerical treatment of fracture. Phase field fracture models have proven effective at representing crack propagation, branching, and merging. Specific formulations, beginning with brittle fracture, have also been shown to converge to classical solutions. Extensions to cover the range of material failure, including ductile and cohesive fracture, lead to an array of possible models. There exists a large body of literature focusing on this class of models and on the impact of model form on the predicted crack evolution. However, there have not been systematic studies into how optimal models may be chosen. Here, we take a first step in this direction by developing formal methods for identification of the best parsimonious model of phase field fracture given full-field data on the damage and deformation fields. We consider some of the main models that have been used for the degradation of elastic response due to damage and its propagation. Our approach builds upon Variational System Identification (VSI), a weak form variant of the Sparse Identification of Nonlinear Dynamics (SINDy). Furthermore, in this first communication we focus on synthetically generated data but we also consider central issues associated with the use of experimental full-field data, such as data sparsity and noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Gallium arsenide solar cell radiation damage study

A thorough analysis has been made of electron- and proton- damaged GaAs solar cells suitable for use in space. It is found that, although some electrical parametric data and spectral response data are quite similar, the type of damage due to the two types of radiation is different. An I-V analysis model shows that electrons damage the bulk of the cell and its currents relatively more, while protons damage the junction of the cell and its voltages more. It is suggested that multiple defects due to protons in a strong field region such as a p/n junction cause the greater degradation in cell voltage, whereas the individual point defects in the quasi-neutral minority-carrier-diffusion regions due to electrons cause the greater degradation in cell current and spectral response.

Maurer, R. H.↗

Assessment of Intralaminar Progressive Damage and Failure Analysis Using an Efficient Evaluation Framework

Reducing the timeline for development and certification for composite structures has been a long standing objective of the aerospace industry. This timeline can be further exacerbated when attempting to integrate new fiber-reinforced composite materials due to the large number of testing required at every level of design. computational progressive damage and failure analysis (PDFA) attempts to mitigate this effect; however, new PDFA methods have been slow to be adopted in industry since material model evaluation techniques have not been fully defined. This study presents an efficient evaluation framework which uses a piecewise verification and validation (V&V) approach for PDFA methods. Specifically, the framework is applied to evaluate PDFA research codes within the context of intralaminar damage. Methods are incrementally taken through various V&V exercises specifically tailored to study PDFA intralaminar damage modeling capability. Finally, methods are evaluated against a defined set of success criteria to highlight successes and limitations.

Hyder, Imran↗

A NASTRAN investigation of simulated projectile damage effects on a UH-1B tail boom model

A NASTRAN model of a UH-1B tail boom that had been designed for another project was used to investigate the effect on structural integrity of simulated projectile damage. Elements representing skin, and sections of stringers, longerons and bulkheads were systematically deleted to represent projectile damage. The structure was loaded in a manner to represent the flight loads that would be imposed on the tail boom at a 130 knot cruise. The deflection of four points on the rear of the tail boom relative to the position of these points for the unloaded, undamaged condition of the tail boom was used as a measure of the loss of structural rigidity. The same procedure was then used with the material properties of the aluminum alloys replaced with the material properties of T300/5208 high strength graphite/epoxy fibrous composite material, (0, + or - 45, 90)s for the skin and (0, + or - 45)s for the longerons, stringers, and bulk heads.

Futterer, A. T.↗

Agent-Based Modeling of Microbes in Space

Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal gravity, and much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER growth curves recapitulate experimental results, and allow comparison between direct effects (DNA damage) and indirect effects (reactive oxygen species generation, metabolic impairment) of radiation.

microbiology↗

Adaptive model-based control systems and methods for controlling a gas turbine

Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).

Brunell, Brent Jerome↗

A numerical model for predicting crack path and modes of damage in unidirectional metal matrix composites

A finite element-based numerical technique has been developed to simulate damage growth in unidirectional composites. This technique incorporates elastic-plastic analysis, micromechanics analysis, failure criteria, and a node splitting and node force relaxation algorithm to create crack surfaces. Any combination of fiber and matrix properties can be used. One of the salient features of this technique is that damage growth can be simulated without pre-specifying a crack path. In addition, multiple damage mechanisms in the forms of matrix cracking, fiber breakage, fiber-matrix debonding and plastic deformation are capable of occurring simultaneously. The prevailing failure mechanism and the damage (crack) growth direction are dictated by the instantaneous near-tip stress and strain fields. Once the failure mechanism and crack direction are determined, the crack is advanced via the node splitting and node force relaxation algorithm. Simulations of the damage growth process in center-slit boron/aluminum and silicon carbide/titanium unidirectional specimens were performed. The simulation results agreed quite well with the experimental observations.

Bakuckas, J. G.↗

Simulation-Based Height of Burst Map for Asteroid Airburst Damage Prediction

Entry and breakup models predict that airburst in the Earth's atmosphere is likely for asteroids up to approximately 200 meters in diameter. Objects of this size can deposit over 250 megatons of energy into the atmosphere. Fast-running ground damage prediction codes for such events rely heavily upon methods developed from nuclear weapons research to estimate the damage potential for an airburst at altitude. (Collins, 2005; Mathias, 2017; Hills and Goda, 1993). In particular, these tools rely upon the powerful yield scaling laws developed for point-source blasts that are used in conjunction with a Height of Burst (HOB) map to predict ground damage for an airburst of a specific energy at a given altitude. While this approach works extremely well for yields as large as tens of megatons, it becomes less accurate as yields increase to the hundreds of megatons potentially released by larger airburst events. This study revisits the assumptions underlying this approach and shows how atmospheric buoyancy becomes important as yield increases beyond a few megatons. We then use large-scale three-dimensional simulations to construct numerically generated height of burst maps that are appropriate at the higher energy levels associated with the entry of asteroids with diameters of hundreds of meters. These numerically generated HOB maps can then be incorporated into engineering methods for damage prediction, significantly improving their accuracy for asteroids with diameters greater than 80-100 m.

Burst Map↗

Agent-based modeling of microbes in space

Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal microgravity; however, much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER results agree with experimental data indicating that indirect effects of radiation (reactive oxygen species generation, metabolic impairment) have a greater impact on microorganisms than direct effects (DNA damage).

Jessica A Lee↗

Clusters of DNA induced by ionizing radiation: formation of short DNA fragments. I. Theoretical modeling

We have developed a general theoretical model for the interaction of ionizing radiation with chromatin. Chromatin is modeled as a 30-nm-diameter solenoidal fiber comprised of 20 turns of nucleosomes, 6 nucleosomes per turn. Charged-particle tracks are modeled by partitioning the energy deposition between primary track core, resulting from glancing collisions with 100 eV or less per event, and delta rays due to knock-on collisions involving energy transfers >100 eV. A Monte Carlo simulation incorporates damages due to the following molecular mechanisms: (1) ionization of water molecules leading to the formation of OH, H, eaq, etc.; (2) OH attack on sugar molecules leading to strand breaks: (3) OH attack on bases; (4) direct ionization of the sugar molecules leading to strand breaks; (5) direct ionization of the bases. Our calculations predict significant clustering of damage both locally, over regions up to 40 bp and over regions extending to several kilobase pairs. A characteristic feature of the regional damage predicted by our model is the production of short fragments of DNA associated with multiple nearby strand breaks. The shapes of the spectra of DNA fragment lengths depend on the symmetries or approximate symmetries of the chromatin structure. Such fragments have subsequently been detected experimentally and are reported in an accompanying paper (B. Rydberg, Radiat, Res. 145, 200-209, 1996) after exposure to both high- and low-LET radiation. The overall measured yields agree well quantitatively with the theoretical predictions. Our theoretical results predict the existence of a strong peak at about 85 bp, which represents the revolution period about the nucleosome. Other peaks at multiples of about 1,000 bp correspond to the periodicity of the particular solenoid model of chromatin used in these calculations. Theoretical results in combination with experimental data on fragmentation spectra may help determine the consensus or average structure of the chromatin fibers in mammalian DNA.

Non-NASA Center↗

The analysis of fatigue crack growth mechanism and oxidation and fatigue life at elevated temperatures

Two quantitative models based on experimentally observed fatigue damage processes have been made: (1) a model of low cycle fatigue life based on fatigue crack growth under general-yielding cyclic loading; and (2) a model of accelerated fatigue crack growth at elevated temperatures based on grain boundary oxidation. These two quantitative models agree very well with the experimental observations.

Liu, H. W.↗