Search NASA⌕ Search

SEARCH · Search NASA

Results for “feature development”

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.

At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-T-527: Prior Knowledge Guided TomoTherapy Treatment Planning

Purpose: The quality and efficiency of radiotherapy treatment planning are highly planer dependent. Previously we have developed a statistical model to correlate anatomical features with dosimetry features of head and neck Tomotherapy treatment. The model enables us to predict the best achievable dosimetry for individual patient prior to treatment planning. The purpose of this work is to study if the prediction model can facilitate the treatment planning in both the efficiency and dosimetric quality. Methods: The anatomy-dosimetry correlation model was used to calculate the expected DVH for nine patients formerly treated. In Group A (3 patients), the model prediction agreed with the clinic plan; in Group B (3 patients), the model predicted lower larynx mean dose than the clinic plan; in Group C (3 patients), the model suggested the brainstem could be further spared. Guided by the prior knowledge, we re-planned all 9 cases. The number of interactions during the optimization process and dosimetric endpoints between the original clinical plan and model-guided re-plan were compared. Results: For Group A, the difference of target coverage and organs-at-risk sparing is insignificant (p>0.05) between the replan and the clinical plan. For Group B, the clinical plan larynx median dose is 49.4±4.7 Gy, while the prediction suggesting 40.0±6.2 Gy (p<0.05). The re-plan achieved 41.5±6.6 Gy, with similar dose on other structures as clinical plan. For Group C, the clinical plan brainstem maximum dose is 44.7±5.5 Gy. The model predicted lower value 32.2±3.8 Gy (p<0.05). The re-plans reduced brainstem maximum dose to 31.8±4.1 Gy without affecting the dosimetry of other structures. In the replanning of the 9 cases, the times operator interacted with TPS are reduced on average about 50% compared to the clinical plan. Conclusion: We have demonstrated that the prior expert knowledge embedded model improved the efficiency and quality of Tomotherapy treatment planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Synthesis and functionalization of electron-deficient perfluoroalkyl porphyrin building blocks for supermolecular systems

Synthetic strategies for electron-deficient meso-perfluoroalkylporphyrins bearing diverse functional groups are described. Scalable and efficient syntheses for 5-triisopropylsilylethynyl-10,15,20-tris(heptafluoropropyl)porphyrin and 5-triisopropylsilylethynyl-10,20-bis(heptafluoropropyl)porphyrin that equip meso-ethynyl functional groups via the bilane route have been established, along with a refined route to [5,15-bis(heptafluoropropyl)porphinato]zinc(II). meso-Position halogenation of [5,15-bis(heptafluoropropyl)porphinato]zinc(II) was achieved by selective meso-nitration and subsequent reduction, diazonium salt formation, and iodination reactions. Computational data describe the low energy excited states of these chromophores and the electronic structural factors that control reactivity of these meso-perfluoroalkyl substituted porphyrin complexes. meso-Functionalized [5-triisopropylsilylethynyl-10,20-bis(heptafluoropropyl)porphinato]zinc(II) and [5-iodo-10,20-bis(heptafluoropropyl)porphinato]zinc(II) building blocks lay the foundation for the construction of highly conjugated multiporphyrin arrays that feature electronic structural properties important for the development of n-type materials and high potential photooxidants.

Chemistry↗
DOE OSTI2017

The Hybrid Toolkit

The Hybrid Toolkit facilitates moving research algorithms into a production environment by creating useful abstractions that separate analytics developers from the intricacies of the production data formats, data flows, and result representations. The toolkit also assists developers with activities such as creating analysis feature vectors, converting between data structures, and creating data pipelines.

Davis IV, WarrenL↗
DOE OSTI2026

SPAROW: Stochastic Programming and Related Optimization Workflows

SAND2026-16703O SPAROW: Stochastic Programming and Related Optimization Workflows is a Python library tool that facilitates the development and solution of stochastic programming problems. It provides a user-friendly class structure for defining stochastic programs through scenario-based representations of uncertainties. SPAROW incorporates multiple optimization strategies, including integer programming with all scenarios, progressive hedging, Benders decomposition, and Snoglode, a novel technique developed by Carnegie Mellon University. It also features interfaces to external solvers and functions that are commonly used in analysis workflows, making it applicable to a wide range of scientific and engineering design challenges, particularly in power grid planning. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, William [Sandia National Lab. (SNL-NM), Albu↗
DOE OSTI2015

Structural basis for PECAM-1 homophilic binding

Platelet endothelial cell adhesion molecule-1 (PECAM-1) is a 130-kDa member of the immunoglobulin gene superfamily (IgSF) that is present on the surface of circulating platelets and leukocytes, and highly expressed at the junctions of confluent endothelial cell monolayers. PECAM-1–mediated homophilic interactions, known to be mediated by its 2 amino-terminal immunoglobulin homology domains, are essential for concentrating PECAM-1 at endothelial cell intercellular junctions, where it functions to facilitate diapedesis, maintain vascular integrity, and transmit survival signals into the cell. Given the importance of PECAM-1–mediated homophilic interactions in mediating each of these cell physiological events, and to reveal the nature and orientation of the PECAM-1–PECAM-1 homophilic-binding interface, we undertook studies aimed at determining the crystal structure of the PECAM-1 homophilic-binding domain, which is composed of amino-terminal immunoglobulin homology domains 1 and 2 (IgD1 and IgD2). The crystal structure revealed that both IgD1 and IgD2 exhibit a classical IgSF fold, having a β-sandwich topology formed by 2 sheets of antiparallel β strands stabilized by the hallmark disulfide bond between the B and F strands. Interestingly, despite previous assignment to the C2 class of immunoglobulin-like domains, the structure of IgD1 reveals that it actually belongs to the I2 set of IgSF folds. Both IgD1 and IgD2 participate importantly in the formation of the trans homophilic-binding interface, with a total buried interface area of >2300 Å 2 . These and other unique structural features of PECAM-1 allow for the development of an atomic-level model of the interactions that PECAM-1 forms during assembly of endothelial cell intercellular junctions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

HI-STORM Overpack and MPC-32 Thermal-Hydraulic Model with MOOSE Framework

Nuclear power is a significant source of electricity in the United States, but the average age of nuclear power plants is around 40 years old. The safe management of the spent nuclear fuel (SNF) is a key aspect of the back-end of the nuclear fuel cycle. Spent fuel dry storage systems are becoming a popular and effective solution in this area, given the absence of a final disposal system. The spent fuel cask system (dry cask method) provides a feasible solution to maintain spent fuel for 60 years before final disposal. Dry cask storage has many characteristics that make it attractive. It fulfills the safety requirements of the Nuclear Regulatory Commission (NRC) while providing modularity and flexibility to contractors. The HI-STORM overpack and MPC-32 canister are the main parts of the HI-STORM 100 dry cask storage system. These components remove heat from the system using natural circulation, requiring no human intervention. This is the characteristic that provides passive heat removal and low maintenance features in dry cask storage systems. To develop a thermal model for a dry cask storage system, the physics behind the system should be defined clearly. There are two natural circulation loops in the system; circulation of helium cools down the nuclear assemblies in the MPC, while circulation of air cools down the walls of the MPC. This work aims to develop a thermal model of the MPC-32 canister and HI-STORM overpack using the Multiphysics Object-Oriented Simulation Environment (MOOSE). MOOSE is an open-source framework developed by Idaho National Laboratory (INL) for multiscale, multiphysics simulations. In this study, we will investigate and demonstrate the thermal-hydraulics modeling capabilities of the MOOSE framework, including natural circulation, heat transfer, and porous flow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

The Biosurveillance Analytics Resource Directory (BARD): Facilitating the use of epidemiological models for infectious disease surveillance

Epidemiological modeling for infectious disease is important for disease management and its routine implementation needs to be facilitated through better description of models in an operational context. A standardized model characterization process that allows selection or making manual comparisons of available models and their results is currently lacking. A key need is a universal framework to facilitate model description and understanding of its features. Los Alamos National Laboratory (LANL) has developed a comprehensive framework that can be used to characterize an infectious disease model in an operational context. The framework was developed through a consensus among a panel of subject matter experts. In this paper, we describe the framework, its application to model characterization, and the development of the Biosurveillance Analytics Resource Directory (BARD; http://brd.bsvgateway.org/brd/), to facilitate the rapid selection of operational models for specific infectious/communicable diseases. We offer this framework and associated database to stakeholders of the infectious disease modeling field as a tool for standardizing model description and facilitating the use of epidemiological models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Inorganic and methane clathrates: Versatility of guest–host compounds for energy harvesting

ABSTRACT This review article evaluates the structure–property relations of inorganic clathrates and clathrate hydrates and their potential role in energy harvesting. There is potential cross-fertilization between the two research areas. Guest–host clathrate compounds exhibit unique structural and physical properties, which lead to their versatile roles in energy applications. Prominent classes of clathrate compounds are gas hydrates and inorganic clathrates. That said, there is limited cross-fertilization between the clathrate hydrate and inorganic clathrate communities, with researchers in the respective fields being less informed on the other field. Yet the structures and unique guest–host interactions in both these compounds are common important features of these clathrates. Common features and procedures can inspire and inform development between the compound classes, which may be important to the technological advancements for the different clathrate materials, e.g., structure characterization techniques and guest–host dynamics in which the “guest” tends to be imprisoned in the host structure, until external forces are applied. Conversely, the diversity in chemical compositions of these two classes of materials leads to the different applications from methane capture and storage to converting waste heat to electricity (thermoelectrics). This article highlights the structural and physical similarities and differences of inorganic and methane clathrates. The most promising state-of-the-art applications of the clathrates are highlighted for harvesting energy from methane (clathrate) hydrate deposits under the ocean and for inorganic clathrates as promising thermoelectric materials.

catalysis (heterogeneous)↗
DOE OSTI2015

TA-IV Sub-Area Plan: Overview & Summary

The Plan seeks to: Sustain programs and activities, and safeguard opportunities to grow mission through redevelopment and infill; Maintain existing land use designations; Construct a multi-modal corridor that connects TA-I, TA-II, and TA-IV; Implement minor adjustments to the site’s security boundaries; Implement an incremental development strategy that enhances the many positive features of the area; Replace temporary buildings with permanent (GPP-size) structures.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Initial High Temperature Inelastic Constitutive Model for Alloy 617

This report describes progress on a Alloy 617 inelastic constitutive model slated for inclusion in the ASME Boiler & Pressure Vessel Code in Code Case N-898 “Use of Alloy 617 (UNS N06617) for Class A Elevated Temperature Construction, Section III, Division 5” as part of an appendix on inelastic modeling. This appendix will provide a reference material model for A617 for use in conjunction with the ASME design by inelastic analysis criteria. This report focuses on the implementation and evaluation of an existing Alloy 617 model developed to represent the data collected at Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) as part of the Alloy 617 Code Case experimental campaign. While the model accurately captures the cyclic stress/strain behavior of Alloy 617, it fails to capture the long-term creep and lower temperature tensile data. In addition, the model form is complicated and has over 50 configurable parameters. As such, we recommend the development of a simplified model, incorporating key features of the ORNL model but reducing the model complexity.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Generic FEPs Catalogue and Salt Knowledge Archive

This report describes the development of a comprehensive catalogue of generic features, events, and processes (FEPs) that are potentially important for the post-closure performance of a repository for high-level radioactive waste (HLW) and spent nuclear fuel (SNF) in salt (halite) host rock. The FEPs and other supporting information have been entered into a “SaltFEP” Database. The generic salt repository FEPs include consideration of relevant FEPs from a number of U.S., Dutch, German, and international FEP lists and should be a suitable starting point for any repository program in salt host rock. The salt FEP catalogue and database employ a FEP classification matrix approach that is based on the concept that a FEP is typically a process or event acting upon or within a feature. The FEP matrix provides a two-dimensional structure consisting of a Features/Components axis that defines the “rows” and a Processes/Events axis that defines the “columns” of the matrix. The design of the FEP classification matrix is consistent with repository performance assessment – the Features/Components axis is organized vertically to generally correspond to the direction of potential radionuclide migration (from the waste to the biosphere) and the Processes/Events axis is designed to represent the common two-way couplings between thermal processes and other processes (such as thermal-mechanical or thermal-hydrologic processes). Related FEPs can be easily identified – related FEPs will typically be grouped in a single matrix cell or aligned along a common row (Feature/Component) or column (Process/Event). The online SaltFEP database can be downloaded from www.saltfep.org. It contains the FEP matrix, the FEPs, and the associated processes for each FEP. It provides a starting point to create and document site-specific individual FEPs. Furthermore, the FEP matrix is connected to the Salt Knowledge Archive (SKA), a database of about 20,000 references and documents representing the historical knowledge on radioactive disposal in salt. This work is the result of an ongoing collaboration between researchers in the U.S., the Netherlands, and Germany, and supports the NEA Salt Club Mandate. It builds upon prior work which is documented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Development of Efficient Process for Manufacturing of Thermoplastic Composites with Tailored Properties (CRADA 511)

This is a collaborative effort between Battelle Memorial Institute as manager and operator of Pacific Northwest National Laboratory (PNNL) and ESI North America Inc. (“ESI” or “Participant”) to apply computation and data analytics to the challenge of light weighting with a focus on the battery enclosures of electric vehicles (EVs). EVs use heavy batteries to increase range and power. A complex-shaped battery enclosure is required to meet a host of challenging performance requirements. The ability to virtually develop composite parts such as battery enclosure with tailored properties to meet required performance will be highly valuable to the automotive industry. However, efficient simulation of composite-manufacturing processes remains a challenging issue since simulation involves multiscale models in space and time, highly non-linear and anisotropic behavior, strongly coupled multi-physics, and complex geometries. This work will advance the state of the art by reducing the computational burden of composite optimization by using simulation data from a limited number of configurations off-line and then developing a reduced order model (ROM) using data analytics and machine learning (ML). Develop a data driven approach to link features of the material and manufacturing processes to the mechanical properties of thermoplastic composite parts.

42 ENGINEERING↗
DOE OSTI2022

Machine Learning for Correlated Intelligence. LDRD SAND Report

The Machine Learning for Correlated Intelligence Laboratory Directed Research & Development (LDRD) Project explored competing a variety of machine learning (ML) classification techniques against a known, open source dataset through the use of a rapid and automated algorithm research & development (RD) infrastructure. This approach relied heavily on creating an infrastructure in which to provide a pipeline for automatic target recognition (ATR) ML algorithm competition. Results are presented for nine ML classifiers against a primary dataset using the pipeline infrastructure developed for this project. New approaches to feature set extraction are presented and discussed as well.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Automatic Detection of Defects in High-Reliability Components

Disastrous consequences can result from defects in manufactured parts—particularly the high consequence parts developed at Sandia. Identifying flaws in as-built parts can be done with nondestructive means, such as X-ray Computed Tomography (CT). However, due to artifacts and complex imagery, the task of analyzing the CT images falls to humans. Human analysis is inherently unreproducible, unscalable, and can easily miss subtle flaws. We hypothesized that deep learning methods could improve defect identification, increase the number of parts that can effectively be analyzed, and do it in a reproducible manner. We pursued two methods: 1) generating a defect-free version of a scan and looking for differences (PandaNet), and 2) using pre-trained models to develop a statistical model of normality (Feature-based Anomaly Detection System: FADS). Both PandaNet and FADS provide good results, are scalable, and can identify anomalies in imagery. In particular, FADS enables zero-shot (training-free) identification of defects for minimal computational cost and expert time. It significantly outperforms prior approaches in computational cost while achieving comparable results. FADS’ core concept has also shown utility beyond anomaly detection by providing feature extraction for downstream tasks.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Small-Molecule Catalysis by Transition-Metal Isocyanide Monomers, Clusters and Materials

DOE Catalysis Science Award DE-SC0018243 focused on the development and mechanistic understanding of small-molecule-activation and catalysis by monomeric and multinuclear transition-metal complexes supported by encumbering m-terphenyl isocyanide ligands. An additional goal of this award was the development of solid-state network materials featuring low-valent metal centers and ditopic m-terphenyl isocyanide ligands into functional platforms for catalytic chemical transformations. The emphasis on m-terphenyl isocyanides stems from a sustained effort by our research team that has shown these ancillary ligands to be particularly adept at stabilizing electronically or coordinately unsaturated metal centers. These metal centers in turn have been shown to effect catalytic and/or stoichiometric chemical transformations of substrates relevant to high-priority energy science goals. In addition, the stabilizing environment provided by these encumbering ligands has in several instances aided the detailed mechanistic elucidation of substrate activation process and/or have enabled important electronic structure insights to be uncovered.

36 MATERIALS SCIENCE↗
DOE OSTI2023

AFC FY 2023 HFIR Irradiation Test Matrix – Supported by the Design of a Ring Specimen Irradiation Vehicle

The development and deployment of accident-tolerant cladding materials in light water nuclear reactors requires the collection of neutron-irradiated properties of these materials with specific consideration to the material properties orientation (i.e., tube geometry). To that end, a test plan to irradiate several cladding tube and ring specimens in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) was proposed, along with the development of a new capsule design that features ring specimens with a preexisting gauge section. This ring specimen geometry removes the need to machine a gauge section on the irradiated specimen and thus allows for direct application of a ring-pull test post-irradiation. The test matrix includes uncoated and chromium-coated Zircaloy-4 and advanced zirconium alloy cladding specimens, pre-characterized at ORNL. Plans are to irradiate the specimens at about 4 and 10 dpa—corresponding to two and five cycles at the HFIR centerline—with a target specimen gauge section temperature of 330°C.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

High-Efficiency Modular SiC-based Power-Converter for Flexible-CHP Systems with Stability-Enhanced Grid-Support Functions

This project seeks to develop a modular, scalable MV power converter featuring stability-enhanced grid-support functions for future grid-interface applications in flexible combined heat and power (F-CHP) cogeneration plants, being fully compliant with the IEEE Standard 1547, category B—for operation in local areas with high aggregated distributed energy resource (DER) penetration, and also with the IEEE standard for the specification of microgrid controllers, namely IEEE Std 2030.7, with the goal to enable F-CHP systems for both microgrid and standalone applications. Further, the proposed converter will use a modular circuit topology, the MMC, which is scalable both in voltage and current by interconnecting power-cell building blocks, thus flexibly suiting the needs of F-CHP systems in the 1–20 MWe range. Furthermore, the use of 10 kV SiC MOSFET devices will minimize the number of power-cells needed to operate in 2–13.8 kV MV distribution systems, but more importantly, they will render feasible a power conversion efficiency > 98 %, and a power density > 10 kW/l. This is highly relevant given that these are two key performance metrics that will further increase the value of F-CHP systems by shortening the time required to recover their investment costs.

14 SOLAR ENERGY↗
DOE OSTI2024

Evaluating the Nation's Pipeline Infrastructure with NETL's Advanced Infrastructure Integrity Model (AIIM)

This poster is a part of BIL-EDX4CCS Task 36: Advanced Infrastructure Integrity Modeling to Evaluate Existing Energy Infrastructure Reusability and Risk, the goal of which is to produce a smart tool that will assess existing energy infrastructure reusability and risk using the Advanced Infrastructure Integrity Model (AIIM). This model forecasts lifespan and potential risk using a multitude of factors such as incidents reports, structural characteristics, and the surrounding environment. The project aims to provide scientific insights for a better understanding of carbon storage (CS), potential to support CS stakeholder needs, national decarbonization, and mitigating climate change. AIIM will utilize an energy infrastructure database as its input, developed by acquiring publicly available data as well as NETL derived products. These resources include incidents, geohazards, and infrastructure variables. Soil data in the form of rasters and pipeline incident reports were processed and a script was developed to count the number of times features such as roads, railroads, and rivers intersected with pipeline segments which were then converted to points. Distance to oil and natural gas wells, petroleum ports, intermodal freight facilities, and geologic structures were also calculated. After data preparation and quality control was completed, the data was integrated into the pipeline points. Once models are complete, a smart tool will be created in the form of an online dashboard.

Malay, Caleb↗