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NASA NTRS2006

User-Defined Material Model for Progressive Failure Analysis

An overview of different types of composite material system architectures and a brief review of progressive failure material modeling methods used for structural analysis including failure initiation and material degradation are presented. Different failure initiation criteria and material degradation models are described that define progressive failure formulations. These progressive failure formulations are implemented in a user-defined material model (or UMAT) for use with the ABAQUS/Standard1 nonlinear finite element analysis tool. The failure initiation criteria include the maximum stress criteria, maximum strain criteria, the Tsai-Wu failure polynomial, and the Hashin criteria. The material degradation model is based on the ply-discounting approach where the local material constitutive coefficients are degraded. Applications and extensions of the progressive failure analysis material model address two-dimensional plate and shell finite elements and three-dimensional solid finite elements. Implementation details and use of the UMAT subroutine are described in the present paper. Parametric studies for composite structures are discussed to illustrate the features of the progressive failure modeling methods that have been implemented.

Knight, Norman F. Jr.↗

NASA NTRS2023

Incidence and Progression of Chorioretinal Folds During Long-Duration Spaceflight

Importance: The primary contributing factor for development of chorioretinal folds during spaceflight is unknown. Characterizing fold types that develop and tracking their progression may provide insight into the pathophysiology of spaceflight-associated neuro-ocular syndrome and elucidate the risk of fold progression for future exploration-class missions exceeding 12 months in duration. Objective: To determine the incidence and presentation of chorioretinal folds in long-duration International Space Station crew members and objectively quantify the progression of choroidal folds during spaceflight. Design, Setting, and Participants: In this retrospective cohort study, optical coherence tomography scans of the optic nerve head and macula of crew members completing long-duration spaceflight missions were obtained on Earth prior to spaceflight and during flight. A panel of experts examined the scans for the qualitative presence of chorioretinal folds. Peripapillary total retinal thickness was calculated to identify eyes with optic disc edema, and choroidal folds were quantified based on surface roughness within macular and peripapillary regions of interest. Interventions or Exposures: Spaceflight missions ranging 6 to 12 months. Main Outcomes and Measures: Incidence of peripapillary wrinkles, retinal folds, and choroidal folds; peripapillary total retinal thickness; and Bruch membrane surface roughness. Results: A total of 36 crew members were analyzed (mean [SD] age, 46 [6] years; 7 [19%] female). Chorioretinal folds were observed in 12 of 72 eyes (17%; 6 crew members). In eyes with early signs of disc edema, 10 of 42 (24%) had choroidal folds, 4 of 42 (10%) had inner retinal folds, and 2 of 42 (5%) had peripapillary wrinkles. Choroidal folds were observed in all eyes with retinal folds and peripapillary wrinkles. Macular choroidal folds developed in 7 of 12 eyes (4 of 6 crew members) with folds and progressed with mission duration; these folds extended into the fovea in 6 eyes. Circumpapillary choroidal folds developed predominantly superior, nasal, and inferior to the optic nerve head and increased in prevalence and severity with mission duration. Conclusions and Relevance: Choroidal folds were the most common fold type to develop during spaceflight; this differs from reports in idiopathic intracranial hypertension, suggesting differences in the mechanisms underlying fold formation. Quantitative measures demonstrate the development and progression of choroidal folds during weightlessness, and these metrics may help to assess the efficacy of spaceflight-associated neuro-ocular syndrome countermeasures.

Connor R. Ferguson↗

DOE OSTI2026

Enhancing segmentation fairness through curriculum learning and progressive loss: a centralized and federated perspective on radiograph analysis

Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

QProR: An Efficient Framework for Quantity-of-Interest Based Progressive Retrieval with Guaranteed Error Control

Scientific applications generate an unprecedented volume of data, overwhelming the network and file systems’ bandwidth and posing challenges for efficient and scalable data retrieval and analysis. Progressive data compression offers a promising solution by enabling on-demand retrieval at reduced size. However, existing progressive methods either fail to bound the errors in essential quantities of interest (QoIs) derived from raw data or suffer from suboptimal retrieval efficiency. In this work, we propose QProR, an efficient QoI-based progressive framework that optimizes progressive retrieval for target QoIs. Our key contributions include: (1) a systematic framework that integrates error-controlled lossy compressors with bitplane encoding while decoupling the two processes for high flexibility and adaptability; (2) a novel weighted bitplane encoding method which incorperates QoI knowledge into data refactoring to enhance retrieval efficiency; (3) an optimized retrieval strategy that accounts for the varying impacts of different variables on multivariate QoIs; (4) comprehensive evaluations using six real-world datasets from multiple scientific applications and thorough comparisons against state of the arts. Experimental results demonstrate that QProR achieves up to 80.38% reduction in the retrieval size under the same requested QoI error tolerance, when compared with the best-performing existing methods. When transferring 384 GB of scientific data to remote sites, QProR delivers up to 1.68 × speedup in the end-to-end data transfer performance.

Li, Wenbo [University of Kentucky]↗

DOE OSTI2026

Early Unloading After ACL Rupture and Prior to Surgical Restabilization in Mice Slows Post-Traumatic Osteoarthritis Progression

Purpose: People who sustain joint injuries such as anterior cruciate ligament (ACL) rupture often go on to develop post-traumatic osteoarthritis (PTOA). ACL injuries are often treated with ACL reconstruction, but there is typically a gap of several weeks between injury and surgery. However, it is unclear how loading or unloading of the injured joint during the early postinjury period affects the progression of PTOA. The goal of this study was to determine how unloading between noninvasive ACL injury and surgical restabilization of the injured joint affects PTOA progression in mice. Findings: Mice were subjected to noninvasive ACL injury or no injury followed by 1 week of hindlimb unloading (HLU) or normal cage activity. After 1 week of HLU or cage activity, mice underwent restabilization surgery or no surgery. ACL injury resulted in considerable epiphyseal trabecular bone loss regardless of HLU or cage activity. HLU groups exhibited significantly reduced chondrophyte/osteophyte formation, OA scoring, and synovitis at day 42. Single-cell RNA sequencing revealed that 1 week of HLU resulted in more neutrophils and less monocytes-macrophages in the injured joint. Conclusions: This study establishes that 1 week of HLU after ACL injury effectively slowed PTOA progression, suggesting that the early inflammatory response and joint instability play a key role in PTOA initiation and progression, and neutrophils and monocytes-macrophages play roles in the modulation. However, subsequent joint restabilization surgery caused greater inflammatory protease activity in the joint and exacerbated the loss of epiphyseal trabecular bone but did not significantly diminish OA score or synovitis.

ACL injury↗

NASA NTRS1996

Progressive Fracture of Fiber Composite Builtup Structures

The damage progression and fracture of builtup composite structures was evaluated by using computational simulation to examine the behavior and response of a stiffened composite (0 +/- 45/90)(sub s6) laminate panel subjected to a bending load. The damage initiation, growth, accumulation, progression, and propagation to structural collapse were simulated. An integrated computer code (CODSTRAN) was augmented for the simulation of the progressive damage and fracture of builtup composite structures under mechanical loading. Results showed that damage initiation and progression have a significant effect on the structural response. Also investigated was the influence of different types of bending load on the damage initiation, propagation, and final fracture of the builtup composite panel.

Gotsis, Pascal K.↗

NASA NTRS1997

Progressive Fracture of Fiber Composite Build-Up Structures

Damage progression and fracture of built-up composite structures is evaluated by using computational simulation. The objective is to examine the behavior and response of a stiffened composite (0/ +/- 45/90)(sub s6) laminate panel by simulating the damage initiation, growth, accumulation, progression and propagation to structural collapse. An integrated computer code, CODSTRAN, was augmented for the simulation of the progressive damage and fracture of built-up composite structures under mechanical loading. Results show that damage initiation and progression have significant effect on the structural response. Influence of the type of loading is investigated on the damage initiation, propagation and final fracture of the build-up composite panel.

Gotsis, Pascal K.↗

NASA NTRS1997

Progressive Fracture of Fiber Composite Build-Up Structures

Damage progression and fracture of built-up composite structures is evaluated by using computational simulation. The objective is to examine the behavior and response of a stiffened composite (0 +/-45/90)(sub s6) laminate panel by simulating the damage initiation, growth, accumulation, progression and propagation to structural collapse. An integrated computer code CODSTRAN was augmented for the simulation of the progressive damage and fracture of built-up composite structures under mechanical loading. Results show that damage initiation and progression to have significant effect on the structural response. Influence of the type of loading is investigated on the damage initiation, propagation and final fracture of the build-up composite panel.

Minnetyan, Levon↗

NASA NTRS1999

Progressive Failure Analysis Methodology for Laminated Composite Structures

A progressive failure analysis method has been developed for predicting the failure of laminated composite structures under geometrically nonlinear deformations. The progressive failure analysis uses C(exp 1) shell elements based on classical lamination theory to calculate the in-plane stresses. Several failure criteria, including the maximum strain criterion, Hashin's criterion, and Christensen's criterion, are used to predict the failure mechanisms and several options are available to degrade the material properties after failures. The progressive failure analysis method is implemented in the COMET finite element analysis code and can predict the damage and response of laminated composite structures from initial loading to final failure. The different failure criteria and material degradation methods are compared and assessed by performing analyses of several laminated composite structures. Results from the progressive failure method indicate good correlation with the existing test data except in structural applications where interlaminar stresses are important which may cause failure mechanisms such as debonding or delaminations.

Sleight, David W.↗

NASA NTRS1999

Probabilistic Assessment of Fracture Progression in Composite Structures

This report describes methods and corresponding computer codes that are used to evaluate progressive damage and fracture and to perform probabilistic assessment in built-up composite structures. Structural response is assessed probabilistically, during progressive fracture. The effects of design variable uncertainties on structural fracture progression are quantified. The fast probability integrator (FPI) is used to assess the response scatter in the composite structure at damage initiation. The sensitivity of the damage response to design variables is computed. The methods are general purpose and are applicable to stitched and unstitched composites in all types of structures and fracture processes starting from damage initiation to unstable propagation and to global structure collapse. The methods are demonstrated for a polymer matrix composite stiffened panel subjected to pressure. The results indicated that composite constituent properties, fabrication parameters, and respective uncertainties have a significant effect on structural durability and reliability. Design implications with regard to damage progression, damage tolerance, and reliability of composite structures are examined.

Chamis, Christos C.↗

NASA NTRS2007

Progress Toward the Stars: An Overview of Ares I First Stage Elements

This viewgraph presentation reviews the progress made in the development of the Ares The information includes an overview of the Ares Launch Vehicles, progress toward the Preliminary Design Review (PDR), progress on design, development, test, and evaluation and technical progress in the development of the Ares I First Stage subsystem.

Williams, Thomas J.↗

NASA NTRS2008

Current Scientific Progress and Future Scientific Prospects Enabled by Spaceborne Precipitation Radar Measurements

First, we examine current scientific progress and understanding that have been possible through use of spaceborne precipitation radar measurements being provided by the TRMM and CloudSat satellites. Second, we look across a future 20-year time frame to assess how and why anticipated improvements in space radar systems will further advance scientific progress into topic areas once considered beyond the realm of space-based remote sensing. JAXA's 13.8 GHz Ku-band cross-track scanning Precipitation Radar (PR) developed for flight on NASA's non-sun-synchronous, diurnally-precessing TRMM satellite, was the first Earth radar flown in space that was designed specifically for precipitation measurement. Its proven accuracy in measuring global rainfall in the tropics and sub-tropics and its unanticipated longevity in continuing these measurements beyond a full decade have established the standards against which all follow-up and future space radars will be evaluated. In regards to the current PR measurement time series, we will discuss a selection of major scientific discoveries and impacts which have set the stage for future radar measuring systems. In fact, the 2nd contemporary space radar applicable for terrestrial precipitation measurement, i.e., JPL-CSA's 94 GHz nadir-staring Cloud Profiling Radar (CPR) flown on NASA's sun-synchronous CloudSat satellite, although designed primarily for measurement of non-precipitating cloud hydrometeors and aerosols, has also unquestionably advanced precipitation measurement because CPR's higher frequency and greatly increased sensitivity (approximately 30 dBZ) has enabled global observations of light rain rate spectrum processes (i.e., rain rates below 0.05 mm per hourand of precipitation processes in the high troposphere (particularly ice phase processes). These processes are beyond reach of the TRMM radar because the PR sensitivity limit is approximately 17 dBZ which means its lower rain rate cutoff is around 0.3 mm per hour and its vertical profiling acuity is greatly limited above the melting layer. Thus, the newer CPR measurements have become important for a variety of scientific reasons that will be highlighted and assessed. In considering scientific progress likely to stem from future precipitation radar systems, we will specifically examine possible scientific impacts from three anticipated missions for which NASA and various of its space agency partners are expected to lead the way. These three missions are: (1) the nearterm Global Precipitation Measuring (GPM) Mission; (2) the decadal timeline Aerosol and Cloud Experiment (ACE) Mission; and the post-decadal timeline NEXRAD in Space (NIS) Mission. The observational capabilities of the planned radar systems for each of these three satellite missions are distinct from each other and each provides progressive improvements in precipitation measuring and scientific research capabilities relative to where we are now -- insofar as TRMM PR and the CloudSat CPR capabilities. The potential innovations in scientific research will be discussed in a framework of likely synergisms between next-generation radar capabilities and accessible dynamical and microphysical properties that have heretofore evaded detection.

Smith, Eric A.↗

NASA NTRS2009

Progress of the NASA/USGS Lunar Regolith Simulant Project

Beginning in 2004 personnel at MSFC began serious efforts to develop a new generation of lunar simulants. The first two products were a replication of the previous JSC-1 simulant under a contract to Orbitec and a major workshop in 2005 on future simulant development. Beginning in 2006 the project refocused its efforts and approached simulant development in a new and more comprehensive manner, examining new approaches in simulant development and ways to more accurately compare simulants to actual lunar materials. This led to a multi-year effort with five major tasks running in parallel. The five tasks are Requirements, Lunar Analysis, Process Development, Feed Stocks, and Standards. Major progress has been made in all five areas. A substantial draft of a formal requirements document now exists and has been largely stable since 2007. It does evolve as specific details of the standards and Lunar Analysis efforts proceed. Lunar Analysis has turned out to be vastly more difficult than anticipated. After great effort to mine existing published and gray literature, the team has realized the necessity of making new measurements of the Apollo samples, an effort that is currently in progress. Process development is substantially ahead of expectations in 2006. It is now practical to synthesize glasses of appropriate composition and purity. It is also possible to make agglutinate particles in significant quantities. A series of minerals commonly found on the Moon has been synthesized. Separation of mineral constituents from starting rock material is also proceeding. Customized grinding and mixing processes have been developed and tested are now being documented. Identification and development of appropriate feedstocks has been both easier and more difficult than anticipated. The Stillwater Mining Company, operating in the Stillwater layered mafic intrusive complex of Montana, has been an amazing resource for the project, but finding adequate sources for some of the components remains a difficult problem. For example the ratio of clino- to ortho-pyroxenes in the Stillwater is not an exact match for lunar materials. One of the sources being examined as an alternative pyroxene source is the Bushveld Complex in South Africa. Standards have been a major success for the project. The Figure of Merit algorithms have been created, tested, and are being considered for an ISO standard. Agreement has been reached in the community about how to make many of the critical measurements. There remains much work to do: (1) driving down the cost of simulants remains a major obstacle; (2) documentation and cost data analysis have not kept up with progress; (3) educating users in the complexity of the lunar regolith and the use of simulants remains a major task. In summary the project has made enormous progress and is successfully placing simulant development and use on a rigorous, scientifically defensible, engineering basis.

Rickman, Doug↗

NASA NTRS2009

Progressive Classification Using Support Vector Machines

An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user can halt this reclassification process at any point, thereby obtaining the best possible result for a given amount of computation time. Alternatively, the results can be displayed as they are generated, providing the user with real-time feedback about the current accuracy of classification.

Wagstaff, Kiri↗

NASA NTRS2010

Method and system for progressive mesh storage and reconstruction using wavelet-encoded height fields

Systems and methods are provided for progressive mesh storage and reconstruction using wavelet-encoded height fields. A method for progressive mesh storage includes reading raster height field data, and processing the raster height field data with a discrete wavelet transform to generate wavelet-encoded height fields. In another embodiment, a method for progressive mesh storage includes reading texture map data, and processing the texture map data with a discrete wavelet transform to generate wavelet-encoded texture map fields. A method for reconstructing a progressive mesh from wavelet-encoded height field data includes determining terrain blocks, and a level of detail required for each terrain block, based upon a viewpoint. Triangle strip constructs are generated from vertices of the terrain blocks, and an image is rendered utilizing the triangle strip constructs. Software products that implement these methods are provided.

Baxes, Gregory A.↗

NASA NTRS2010

Predicting Failure Progression and Failure Loads in Composite Open-Hole Tension Coupons

Failure types and failure loads in carbon-epoxy [45n/90n/-45n/0n]ms laminate coupons with central circular holes subjected to tensile load are simulated using progressive failure analysis (PFA) methodology. The progressive failure methodology is implemented using VUMAT subroutine within the ABAQUS(TradeMark)/Explicit nonlinear finite element code. The degradation model adopted in the present PFA methodology uses an instantaneous complete stress reduction (COSTR) approach to simulate damage at a material point when failure occurs. In-plane modeling parameters such as element size and shape are held constant in the finite element models, irrespective of laminate thickness and hole size, to predict failure loads and failure progression. Comparison to published test data indicates that this methodology accurately simulates brittle, pull-out and delamination failure types. The sensitivity of the failure progression and the failure load to analytical loading rates and solvers precision is demonstrated.

Arunkumar, Satyanarayana↗

NASA NTRS2011

Method and system for progressive mesh storage and reconstruction using wavelet-encoded height fields

Baxes, Gregory A.↗

NASA NTRS2011

Investigating the Effect of Damage Progression Model Choice on Prognostics Performance

The success of model-based approaches to systems health management depends largely on the quality of the underlying models. In model-based prognostics, it is especially the quality of the damage progression models, i.e., the models describing how damage evolves as the system operates, that determines the accuracy and precision of remaining useful life predictions. Several common forms of these models are generally assumed in the literature, but are often not supported by physical evidence or physics-based analysis. In this paper, using a centrifugal pump as a case study, we develop different damage progression models. In simulation, we investigate how model changes influence prognostics performance. Results demonstrate that, in some cases, simple damage progression models are sufficient. But, in general, the results show a clear need for damage progression models that are accurate over long time horizons under varied loading conditions.

Daigle, Matthew↗