SEARCH · Search NASA
Results for “Bagging”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
LANL PVC bag-out-bag replacement [Slides]
The US material at 8 months aging, at room temperature and exposed to gamma at 80 degrees C has been completed. The FTIR data does not show any discernible difference between the US APU-ether material and the British material. There are some differences and the curves of the FTIR, but the behavior shows that the US material is behaving comparable to the British material. The British Blue sample exposed to gamma at 70 degrees C did have an observable change in the contact angle. This was the only notable change between the two different types of polymer the TGA on both the US and the British had no observable difference. Mechanical testing samples (dog-bones) are being prepared for tensile, shear, and puncture testing. This data will be provided in later meetings. Mass spec testing is needed to measure the headspace gases that are being seen during the aging study to better health characterize the radiolytic degradation of the APU ether samples, this is also ongoing.
Development and Implementation of a Bag Degradation Predictive Tool at Los Alamos National Laboratory
Nuclear material packaging involves many complex variables derived from the stored material's properties, the storage environment, and the synergistic interaction of said material and its environment on the containment boundary. In the Plutonium Facility (PF-4) at Los Alamos National Laboratory (LANL) the typical containment boundary found, starting from the stored material itself to the outermost containment layer, consists of the material contained within a stainless steel (typically 304) slip-lid (or other equivalent stainless steel packaging layer) wrapped in an sPVC bag-out bag contained within a facility approved outer container stored within the boundaries of an approved facility (i.e., a building designed and approved to store nuclear material). This packaging configuration, though occasionally deviated from in the past, represents the current procedurally enforced, expected containment structure for all interim nuclear material containment outside of an engineered control barrier (e.g., a glovebox). Over the life of containerization research at LANL, packaging engineers have become increasingly concerned with the degradation of the sPVC bag-out bag, which can cause corrosion to the outermost packaging layer as well as possible exposure to alpha contamination if the bag-out bag layer is degraded to the point of containment failure. A bag-out bag degradation predictive tool (BDT) is therefore needed to assess the current and future nuclear material inventory for possible bag degradation in order to continue to ensure safe operations for the facility and its workers to deliver on the vital national security mission of 30 PPY.
Chiral-odd GPDs in the bag model
A study of chiral-odd generalized parton distributions (GPDs) of the nucleon is presented in the bag model demonstrating that in this model all four chiral-odd GPDs are nonzero contrary to other claims in literature. The bag model results for the GPDs H T q ( x , ξ , t ) , E T q ( x , ξ , t ) , H ˜ T q ( x , ξ , t ) agree with other models within a typical quark model accuracy. We present one of the few quark model calculations where polynomiality is satisfied and the sum rule ∫ d x E ˜ T q ( x , ξ , t ) = 0 holds. We confront our results with predictions from the large- N c limit, and with lattice QCD calculations. We conclude that the bag model successfully catches the main features of chiral-odd GPDs. Published by the American Physical Society 2024
Fermion-bag inspired Hamiltonian lattice field theory for fermionic quantum criticality
Motivated by the fermion-bag approach, in this work we construct a new class of Hamiltonian lattice field theories that can help us to study fermionic quantum critical points, particularly those with four-fermion interactions. Although these theories are constructed in discrete time with a finite temporal lattice spacing ϵ, when ϵ → 0, conventional continuous-time Hamiltonian lattice field theories are recovered. The fermion-bag algorithms run relatively faster when ϵ = 1 as compared to ϵ → 0 but still allow us to compute universal quantities near the quantum critical point even at such a large value of ϵ. As an example of this new approach, here we study the $N_f$ = 1 Gross-Neveu chiral-Ising universality class in 2 + 1 dimensions by calculating the critical scaling of the staggered mass order parameter. We show that we are able to study lattice sizes up to 100 2 sites when ϵ = 1, while with comparable resources we can reach lattice sizes of only up to 64 2 when ϵ → 0. The critical exponents obtained in both these studies match within errors.
In-Use Interfacial Stability of Monoclonal Antibody Formulations Diluted in Saline i.v. Bags
The use of monoclonal antibodies (mAbs) for the treatment of a variety of diseases is rapidly growing each year. Many mAbs are administered intravenously using i.v. bags containing 0.9% NaCl (normal saline). We studied the aggregation propensity of these antibody solutions in saline and compared it with a low ionic strength formulation buffer. Furthermore, the mAb studied in this work is prone to aggregate, and is known to form a viscoelastic network at the air-solution interface. We observed that this interfacial elasticity increased when formulated in saline. In the bulk, the mAbs exhibited a tendency to self-associate that was higher in saline. We also studied the aggregation of the mAbs in the presence of polysorbate-20, typically added to formulations to mitigate interfacial aggregation. We observed that with surfactants, the presence of salt in the buffer led to a greater mAb adsorption at the interface and resulted in the formation of more particulate aggregates. Our results show that the addition of salt to the buffer led to differences in the interfacial aggregation in mAb formulations, showing that stress studies used to screen for mAb aggregation intended for i.v. administration should be performed in conditions representative of their intended route of administration.
Addressing bias in bagging and boosting regression models
As artificial intelligence (AI) becomes widespread, there is increasing attention on investigating bias in machine learning (ML) models. Previous research concentrated on classification problems, with little emphasis on regression models. This paper presents an easy-to-apply and effective methodology for mitigating bias in bagging and boosting regression models, that is also applicable to any model trained through minimizing a differentiable loss function. Our methodology measures bias rigorously and extends the ML model's loss function with a regularization term to penalize high correlations between model errors and protected attributes. We applied our approach to three popular tree-based ensemble models: a random forest model (RF), a gradient-boosted model (GBT), and an extreme gradient boosting model (XGBoost). We implemented our methodology on a case study for predicting road-level traffic volume, where RF, GBT, and XGBoost models were shown to have high accuracy. Despite high accuracy, the ML models were shown to perform poorly on roads in minority-populated areas. Our bias mitigation approach reduced minority-related bias by over 50%.
Fair Bagging Boosting Models [SWR-24-38]
Fair Bagging Boosting Models is a software implementation of a framework for building, measuring bias and correcting bias in 3 popular forest machine learning models: gradient boosted trees (GBT), random forest (RF), and XGBoost models, using the XGBoost library. The framework takes advantage of the flexibility in XGBoost library to represent gradient boosted tree and random forest models, as well as the ability to use custom loss function.
In Vitro Leakage Testing of Tissue Containment Bags When Subjected to Power Morcellation Forces
Not Available
Energy momentum tensor and the D term in the bag model
Not Available
Energy and Earth Systems Brown Bag Series:Corrosion in Energy Systems and Application to Spent Nuclear Fuel Dry Storage Canisters.
Abstract not provided.
Wide-Area, Rapid Vacuum Bag Leak Detection for Composite Wind Turbine Blade Fabrication
Explore the source record for details and available documents.
Gray matter volume drives the brain age gap in schizophrenia: a SHAP study
Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term β = 1.71 [0.53; 3.23]; p corr < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.
Effects of Microbial-Mineral Interactions on Organic Carbon Stabilization in a Ponderosa Pine Root Zone: A Micro-Scale Approach
Soil microbial communities affect the formation of micro-scale mineral-associated organic matter (MAOM) where complex processes, including adhesion, aggregate formation, microbial mineral weathering and soil organic matter stabilization occur in a narrow zone of large biogeochemical gradients. Here we designed a field study to examine carbon stabilization mechanisms by using in-growth mesh bags containing biotite that were placed in a ponderosa pine root zone for 6 months and compared to the surrounding bulk soil. We sought to determine the composition of the microbial community in the mesh bags compared to the surrounding soils, analyze the direct interactions between microbes and biotite, and finally identify the nature of the newly formed MAOM within the mesh-bags. Our results revealed that minerals in the mesh bags were colonized by a microbial community that produced organic matter in situ. The 16S rRNA gene sequencing and ITS2 region characterization showed phylogenetic similarity between the mesh bag and bulk soil archaea/bacteria and fungi microbiomes, with significant differences in alpha- and beta-diversity and species abundances. Organic matter pools in the mesh bags, analyzed by Fourier transform ion cyclotron resonance mass spectrometry, contained protein- (peptides) and lipid-like compounds while the bulk soil OM was comprised of lignin-like and carboxyl-rich alicyclic molecules. These results support that the newly formed biotite associated organic compounds have a microbial signature in the mesh bags. High-resolution electron microscopy documented strongly adhered organic compounds to biotite surfaces, formation of microaggregates, elemental uptake at the microbe (organic matter)-mineral interface, and distortion of biotite layers. Overall, this study shows the direct and indirect involvement of soil microbial communities from the root zone of ponderosa pine in the formation of MAOM, soil organic carbon stabilization, microaggregation, and mineral weathering at micro- and nano-scales.
Developing an Active Learning algorithm for learning Bayesian classifiers under the Multiple Instance Learning scenario
In the Multiple Instance Learning scenario, the training data consists of instances grouped into bags, and each bag is labelled with whether it is positive, i.e. contains at least one positive instance. First, Active Learning, in which additional labels can be iteratively requested, has the potential to allow more accurate classifiers to be learned with less labels. Active Learning has been applied to the Multiple Instance Learning under two settings: when bag labels of unlabelled bags can be requested, and when instance labels within bags known to be positive can be requested. Second, Bayesian Active learning methods have the potential to learn accurate classifiers with few labels, because they explicitly track the classifier uncertainty and can thus address its knowledge gaps. Yet, there does not exist any Bayesian Active Learning method for the Multiple Instance Learning Scenario. In this work, we develop the first such method. We develop a Bayesian classifier for the Multiple Instance Learning scenario, show how it can be efficiently used for Bayesian Active Learning, and perform experiments assessing its performance. While its performance exceeds that when no Active Learning is used, it is sometimes better, sometimes worse than the naive baseline of uncertainty sampling, depending on the situation. This suggests future work: building more customizable Bayesian Active Learning methods for the Multiple Instance Scenario, customizable to whether bag or instance label accuracy is targeted, and the labeling budget.
A Simple, Revolutionary Approach to Waste Packaging Utilizing Proven Technology - 20201
Historically, removing hazardous waste from gloveboxes involves the use of bags as the primary containment method. This method can prove tedious, repetitive, and time consuming to ensure the process follows all safeguards required to contain the waste and mitigate any breach of containment. Layers of bags, yards of tape, and multiple filters are added to the waste stream in order to transfer the hazardous waste from the glovebox safely into the drum package. Then, finally, it can be shipped and disposed of. The process to cut, tie, and tape each bag for disposal involves manual effort by multiple operators. Following Administrative Safety Controls, good operators are able to safely perform those tasks; but, since the bag is the only confinement layer, incidents can occur. Operators, in some cases, are also at close proximity to this waste which may increase the risk of radiation exposure. Once the waste is transferred out through these bags, it is nearly impossible to remove packaged waste that may contain higher dosage levels, thus increasing drum disposal costs incurred by the facility. Exceeding the allowable radiation levels, and drums not fully filled, both contribute significantly to excess disposal costs. Central Research Laboratories (CRL), based in Red Wing Minnesota, has developed the Waste Drum Transfer System (WDTS) building upon the proven technology and containment of the Rapid Transfer Port (RTP) as an alternate, more efficient method of waste transfer. This solution consists of an RTP Alpha port mounted inside a glovebox and Beta assembly unit composed of a drum liner fitted inside a standard 55 gallon drum. The use of the Beta drum liner bypasses the typical use of bags, sleeves or tape to provide leak tight containment. The process to connect and disconnect a drum from the glovebox is achieved by the self-docking and rotating system controls of the RTP Alpha, all done with only one operator standing in an upright ergonomic position. This system also allows for greater flexibility in available Beta connection options, expanding the overall functionality of the system. This system can be disconnected and reconnected multiple times to maximize volume containment. This will minimize drum disposal costs and reduce the overall volume of waste output by more efficiently filling the drums. Radiation levels inside each drum can be monitored and adjusted more efficiently by operators utilizing the reconnect option. Minimal As Low As Reasonably Achievable (ALARA) levels are also achievable with this system. This paper will show how highly efficient packaging and disposal of hazardous waste can be accomplished in a cost-effective manner utilizing the proven RTP technology. Maximized operator productivity and safety, as well as minimized radiation dose exposure, are all attainable through the system's engineered controls. (authors)
Effect of laminae count and manufacturing methods on mechanical properties of thin‐ply woven composites
Abstract Thin‐ply woven composites exhibit exceptional mechanical performance by delaying the onset of damage, making them suitable for high‐performance structural applications. This study outlines the impact of manufacturing techniques (vacuum bagging and hot pressing), ply count, and fiber waviness on the mechanical properties of aromatic thermosetting copolyester/carbon‐fiber (ATSP/CF) composites. The analysis encompasses several different ply counts, evaluating their effects on the in‐plane elastic modulus (0°–90°) and tensile strength. Results demonstrate that reducing the waviness (or crimp) ratio significantly enhances the in‐plane elastic modulus, with improvements up to 188%, highlighting the importance of fiber alignment. Vacuum bagging produced ply thicknesses from 128 to 58 μm for 1–36 plies, with in‐plane elastic moduli from 30.3 to 87.2 GPa, and 4‐ and 8‐ply samples showed approximately 40% higher stiffness than those made by hot pressing. ATSP resin with high thermal stability (up to 400°C) and recyclability was used. Furthermore, this study highlights the microstructural enhancements achieved through vacuum bagging, as revealed by scanning electron and optical microscopy, and micro‐computed tomography imaging. This paper provides insights into damage mitigation and achieving enhanced mechanical properties by controlling fiber waviness using vacuum bagging and higher ply count in thin‐ply ATSP/CF composites. Highlights Crimp ratio reduction enhances elastic in‐plane elastic modulus up to 188%. Vacuum bagging increases modulus over the hot pressing manufacturing method by 40%. Lowering thickness‐per‐ply increases failure strain from 0.8% to 1.2%. Explored the performance of a novel ATSP matrix with high recyclability and thermal stability.
Root carbon interation with soil minerals is dynamic, leaving a legacy of microbially derived residues
Minerals preserve the oldest most persistent soil carbon, and mineral characteristics appear to play a critical role in the formation of soil organic matter (SOM) associations. To test the hypothesis that carbon source and soil microorganisms also influence mineral-SOM associations, we incubated permeable minerals bags in soil microcosms with and without plants, in a 13CO2 labelling chamber. Mineral bags contained quartz, ferrihydrite, kaolinite, or native soil minerals isolated via density separation. Using 13C-NMR, FTICR-MS, and lipidomics, we traced plant-derived carbon onto minerals harvested from microcosms at three plant growth stages, characterizing total carbon, 13C enrichment, and SOM chemistry. While C accumulation was rapid and mineral-dependent, the accumulated amount was not significantly affected by the presence of plant roots. However, the rhizosphere did shape the chemistry of mineral-associated SOM. Minerals incubated in the rhizosphere were associated with a more diverse array of compounds with different C functional groups (carbonyl, aromatics, carbohydrates, lipids) than minerals incubated in a bulk soil control. These diverse rhizosphere-derived compounds may represent a “transient fraction” of mineral SOM, rapidly exchanging with mineral surfaces. Our results also suggest that many of the lipids which persist on minerals are microbially-derived with a large fraction of fungal lipids.