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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.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Colloidal Three-Dimensional Covalent Organic Frameworks and Their Application as Porous Liquids

Developing solid porous materials into free-flowing liquids with permanent porosity is a promising strategy for overcoming certain limitations of conventional sorbent materials employed in gas storage and separation applications. The ability to control the pore size and chemical functionalities of organic frameworks gives these particular nanoporous materials distinct advantages over other small cage-like molecules or hollow particles that have been developed into porous liquids. Here, we describe the synthesis of a 3D imine-linked colloidal covalent organic framework (COF)-based porous liquid, designed for efficient size-exclusion of solvent, as well as for long-term stability. By tethering ionic liquids to the colloid surface, the colloids can be dried, purified, and resuspended in a variety of solvents without irreversible aggregation typically observed of COF colloids. Colloid size could be controlled between 50 and 400 nm, with surface areas as high as 800 m2/g. The 3D intertwining morphology of the colloids had pore sizes ranging from 5 to 14 Å, allowing them to efficiently sizeexclude bulky ionic liquids. The COF colloids were stable towards flocculation in an ionic liquid for > 1 year. Permanent porosity was confirmed with a combination of 19F NMR measurements and gas sorption techniques. CO2 and CH4 uptake in these porous liquids increased more than 10 and 20-fold, respectively, over non-porous, neat ionic liquid control samples. The work not only advances the state of COF-based colloid science but also represents a practical advance towards developing more robust, tunable framework-based porous liquid materials for a host of gas storage and separation applications.

Mow, Rachel E.↗
NASA NTRSDate not supplied

Application of Framework for Estimating Performance and Associated Uncertainty for Modified Aircraft Configurations Using NASA's X-57 Maxwell

A framework to estimate the performance and associated uncertainty of modified configurations of certified aircraft is applied to the X-57 Maxwell aircraft. In previous theoretical studies, the framework was shown to predict performance and uncertainty bounds accurately. The X-57 Maxwell is an experimental aircraft designed to demonstrate the benefits of distributed electric propulsion through a series of four incremental modifications to a Tecnam P2006T aircraft. The available models and data are first shown to be within the application domain of the framework. We then apply the framework to two X-57 Maxwell modifications. We compare the estimated performance and associated uncertainties against the airworthiness criteria. The results indicate that the framework is a promising tool for the certification by analysis workflow. We expect the framework to reduce and supplement the flight testing required to show compliance to airworthiness certification criteria for a modified configuration.

Uncertainty Quantification↗
NASA NTRSDate not supplied

Application of Framework for Estimating Performance and Associated Uncertainty for Modified Aircraft Configurations Using NASA's X-57 Maxwell

A framework to estimate the performance and associated uncertainty of modified configurations of certified aircraft is applied to the X-57 Maxwell aircraft. In previous theoretical studies, the framework was shown to predict performance and uncertainty bounds accurately. The X-57 Maxwell is an experimental aircraft designed to demonstrate the benefits of distributed electric propulsion through a series of four incremental modifications to a Tecnam P2006T aircraft. The available models and data are first shown to be within the application domain of the framework. We then apply the framework to two X-57 Maxwell modifications. We compare the estimated performance and associated uncertainties against the airworthiness criteria. The results indicate that the framework is a promising tool for the certification by analysis workflow. We expect the framework to reduce and supplement the flight testing required to show compliance to airworthiness certification criteria for a modified configuration.

Uncertainty Quantification↗
DOE OSTI2020

Refreshing Waste Tracking Software for the 2020's - 20059

The Waste Compliance and Tracking System (WCATS) is a software application designed to manage waste operations from cradle to grave. The system provides the support needed for characterization, generation, processing, and shipment of all waste generated or stored at Los Alamos National Laboratory (LANL). Waste is tracked with task records for containers in real-time via both desktop and mobile device applications. The software allows application administrators to configure sites with appropriate limits for Pu-239 equivalent Curies (PE-Ci), fissile gram equivalents (FGEs), volume limits, as well as custom limits for site-specific technical safety requirements (TSRs). WCATS was developed based on a need at Los Alamos National Laboratory for a modern, customizable waste tracking system that could support many different waste types. The application is built using Oracle{sup R} database and Oracle{sup R} ADF Swing application framework. The technologies and software frameworks selected for the system were finalized in 2006. Although Oracle{sup R} Database has proven to be robust, the user interface and application framework interface with the database have been deprecated and need to be replaced. The technologies selected for modernization follow the open-source model, which allows the WCATS team to more easily recruit developers, improve the speed of development, and ease the deployment and adoption of the system. The tools that support the re-engineering effort are Vue.js{sup R}, a JavaScript{sup R} framework, and Spring Boot{sup R}, an API (application programming interface) development tool written in Java{sup R}. An API allows for simplified communication from the database to the user interface of the application. In addition, legacy Crystal Reports{sup R} will be replaced with reports developed with the open source Pentaho{sup TM}f Report Designer community edition. Because the application uses HTML and JavaScript{sup R}, it builds upon tools that have been used for many years in web development. These tools have large community support and their proven track record will ensure that enhancements to WCATS can continue for years to come. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Evaluating precipitation distributions at regional scales: a benchmarking framework and application to CMIP5 and 6 models

Abstract. As the resolution of global Earth system models increases, regional-scale evaluations are becoming ever more important. This study presents a framework for quantifying precipitation distributions at regional scales and applies it to evaluate Coupled Model Intercomparison Project (CMIP) 5 and 6 models. We employ the Intergovernmental Panel on Climate Change (IPCC) sixth assessment report (AR6) climate reference regions over land and propose refinements to the oceanic regions based on the homogeneity of precipitation distribution characteristics. The homogeneous regions are identified as heavy-, moderate-, and light-precipitating areas by K-means clustering of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) version 6 final run product (IMERG) precipitation frequency and amount distributions. With the global domain partitioned into 62 regions, including 46 land and 16 ocean regions, we apply 10 established precipitation distribution metrics. The collection includes metrics focused on the maximum peak, lower 10th percentile, and upper 90th percentile in precipitation amount and frequency distributions; the similarity between observed and modeled frequency distributions; an unevenness measure based on cumulative amount; average total intensity on all days with precipitation; and number of precipitating days each year. We apply our framework to 25 CMIP5 and 41 CMIP6 models, as well as six observation-based products of daily precipitation. Our results indicate that many CMIP5 and 6 models substantially overestimate the observed light-precipitation amount and frequency, as well as the number of precipitating days, especially over midlatitude regions outside of some land regions in the Americas and Eurasia. Improvement from CMIP5 to 6 is shown in some regions, especially in midlatitude regions, but it is not evident globally, and over the tropics most metrics point toward degradation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Blockchain Applicability and Cybersecurity Frameworks (BAF)

The Blockchain Applicability and Cybersecurity Frameworks is the implementation of an earlier invention disclosure and Provisional Patent Application: S-146,805, Battelle IPID 31608-E. —BAF walks a user (or an interested party) through ~100 controls to determine various factors, including: 1. Does the application need a blockchain? 2. If the application needs a blockchain, does it need a private blockchain or permissionless/public blockchain? 3. What kind of consensus is most suitable for the application? The current version of BAF evaluates between four consensus mechanisms: proof-of-work, proof-of-stake, proof-of-burn, and proof-of-authority.

Gourisetti, Sri Nikhil Gupta↗
DOE OSTI2019

Behavioral modeling of on-demand mobility services: general framework and application to sustainable travel incentives

This paper presents a systematic way of understanding and modeling traveler behavior in response to on-demand mobility services. We explicitly consider the sequential and yet inter-connected decision-making stages specific to on-demand service usage. The framework includes a hybrid choice model for service subscription, and three logit mixture models with inter-consumer heterogeneity for the service access, menu product choice and opt-out choice. Different models are connected by feeding logsums. The proposed modeling framework is essential for accounting the impacts of real-time on-demand system's dynamics on traveler behaviors and capturing consumer heterogeneity, thus being greatly relevant for integrations in multi-modal dynamic simulators. The methodology is applied to a case study of an innovative personalized on-demand real-time system which incentivizes travelers to select more sustainable travel options. The data for model estimation is collected through a smartphone-based context-aware stated preference survey. Through model estimation, lower values of time are observed when the respondents opt to use the reward system. The perception of incentives and schedule delay by different population segments are quantified. These results are fundamental in setting the ground for different behavioral scenarios of such a new on-demand system. Here, the proposed methodology is flexible to be applied to model other on-demand mobility services such as ride-hailing services and the emerging mobility as a service.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Development of multi-objective core optimization framework and application to sodium-cooled fast test reactors

The optimization of a Sodium-cooled Fast Reactor (SFR) core is a challenging process, due to the large number of design parameters, the nonlinearities among inputs and outputs, and the complicated correlation among output parameters. This study attempts to develop a generalized framework for the SFR core optimization by coupling the sensitivity analysis, advanced optimization algorithm, and optionally the surrogate modeling. The framework is built based on the fast reactor modeling capability of the Argonne Reactor Computation (ARC) suite and the sensitivity analysis and optimization modules embedded in the DAKOTA code, both have been integrated within the NEAMS Workbench. The genetic algorithm is selected as the optimization method for its robustness, while the option of surrogate modeling is also explored to alleviate the computational burden caused by employing the ARC direct core physics simulation and thus enhance the efficiency of the optimization. Finally, the normalized deviations of performance parameters of the near-optimal solution from those of the ideal core are calculated and used as criteria to down select the final core design. The developed framework is applied to the Advanced Burner Test Reactor (ABTR) core, and optimal solutions are determined by balancing various objectives simultaneously, including peak fast flux, core volume, power, reactivity swing, plutonium mass feed, while at the same time satisfying the predefined constraints due to safety or economics considerations. The optimal ABTR core design obtained using the direct physical simulation and surrogated model are compared and discussed. It is found that using the accurately constructed surrogate models can significantly reduce the required computational time while maintaining satisfactory accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Advanced Health Information Technology Analytic Framework and Application to Hazard Detection

Health Information Technology (HIT) aims to improve healthcare outcomes by organizing and analyzing various health-related data. With data accumulating at a staggering rate, the importance of real-time analytics has been increasing dramatically, shifting the focus of informatics from batch processing to streaming analytics. HIT is also facing unprecedented challenges in adapting to this new requirement and leveraging advanced IT technologies. This paper introduces a HIT data and compute platform that supports multi-granularity real-time analytics from heterogeneous data sources. The paper first identifies functional requirements and proposes a framework that satisfies the requirements using state-of-the-art big data technologies including Apache Kafka, Spark Structured Streaming Engine, and Delta Lake. To demonstrate its capability to support data analytics in multiple time granularities analytics, a statistical process control-based hazard detection algorithm has been implemented on top of the framework to detect unexpected hazards from order cancellation data of the Department of US Veterans Affairs (VA) in near real-time.

Kumar, Mohit↗
DOE OSTI2018

Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels

Activity-travel choices of individuals are influenced by spatial dependency effects. As individuals interact and exchange information with, or observe the behaviors of, those in close proximity of themselves, they are likely to shape their behavioral choices accordingly. For this reason, econometric choice models that account for spatial dependency effects have been developed and applied in a number of fields, including transportation. However, spatial dependence models to date have largely defined the strength of association across behavioral units based on spatial or geographic proximity. In the current context of social media platforms and ubiquitous internet and mobile connectivity, the strength of associations among individuals is no longer solely dependent on spatial proximity. Rather, the strength of associations among individuals may be based on shared attitudes and preferences as well. In other words, behavioral choice models may benefit from defining dependency effects based on attitudinal constructs in addition to geographical constructs. In this paper, frequency of usage of car-sharing and ride-hailing services is modeled using a generalized heterogeneous data model (GHDM) framework that incorporates multi-dimensional dependencies among decision-makers. The model system is estimated on the 2014-2015 Puget Sound Regional Travel Study survey sample, with proximity in latent attitudinal constructs defined by a number of personality trait variables. Model estimation results show that social dependency effects arising from similarities in attitudes and preferences are significant in explaining shared mobility service usage. Ignoring such effects may lead to erroneous estimates of the adoption and usage of future transportation technologies and mobility services.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Parallel general purpose multiobjective optimization framework with application to electron beam dynamics

Particle accelerators are invaluable tools for research in the basic and applied sciences, such as materials science, chemistry, the biosciences, particle physics, nuclear physics and medicine. The design, commissioning, and operation of accelerator facilities is a nontrivial task, due to the large number of control parameters and the complex interplay of several conflicting design goals. The Argonne Wakefield Accelerator facility has some unique challenges resulting from its purpose to carry out advanced accelerator R&D. Individual experiments often have challenging beam requirements, and the physical configuration of the beam lines is often changed to accommodate the variety of supported experiments. The need for rapid deployment of different operational settings further complicates the optimization work that must be done for multiple constraints and challenging operational regimes. One example of this is an independently staged two-beam acceleration experiment which requires the construction of an additional beam line (this is now in progress). The high charge drive beam, well into the space charge regime, must be threaded through small aperture (17.6 mm) decelerating structures. In addition, the bunch length must be sufficiently short to maximize power generation in the decelerator. We propose to tackle this problem by means of multiobjective optimization algorithms which also facilitate a parallel deployment. In order to compute solutions in a meaningful time frame, a fast and scalable software framework is required. In this paper, we present a general-purpose framework for simulation-based multiobjective optimization methods that allows the automatic investigation of optimal sets of machine parameters. Using evolutionary algorithms as the optimizer and opal as the forward solver, validation experiments and results of multiobjective optimization problems in the domain of beam dynamics are presented. Optimized solutions for the new high charge drive beam line found by the framework were used to finish the design of a two beam acceleration experiment. The selected solution along with the associated beam parameters is presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

The LISE package: solvers for static and time-dependent superfluid local density approximation equations in three dimensions

Nuclear implementation of the density functional theory (DFT) is at present the only microscopic framework applicable to the whole nuclear landscape. The extension of DFT to superfluid systems in the spirit of the Kohn-Sham approach, the superfluid local density approximation (SLDA) and its extension to time-dependent situations, time-dependent superfluid local density ap- proximation (TDSLDA), have been extensively used to describe various static and dynamical problems in nuclear physics, neutron star crust, and cold atom systems. In this paper, we present the codes that solve the static and time-dependent SLDA equations in three-dimensional coordinate space without any symmetry restriction. These codes are fully parallelized with the message passing interface (MPI) library and take advantage of graphic processing units (GPU) for accelerating execution. The dynamic codes have checkpoint/restart capabilities and for initial conditions one can use any generalized Slater determinant type of wave function. The code can describe a large number of physical problems: nuclear fission, collisions of heavy ions, the interaction of quantized vor- tices with nuclei in the nuclear star crust, excitation of superfluid fermion systems by time dependent external fields, quantum shock waves, domain wall generation and propagation, the dynamics of the Anderson-Bogoliubov-Higgs mode, dynamics of fragmented condensates, vortex rings dynamics, generation and dynamics of quantized vortices, their crossing and recombinations and the incipient phases of quantum turbulence.

Jin, Shi↗
DOE OSTI2020

A general metriplectic framework with application to dissipative extended magnetohydrodynamics

General equations for conservative yet dissipative (entropy producing) extended magnetohydrodynamics are derived from two-fluid theory. Keeping all terms generates unusual cross-effects, such as thermophoresis and a current viscosity that mixes with the usual velocity viscosity. While the Poisson bracket of the ideal version of this model has already been discovered, we determine its metriplectic counterpart that describes the dissipation. This is done using a new and general thermodynamic point of view to derive dissipative brackets, a means of derivation that is natural for understanding and creating dissipative dynamics without appealing to underlying kinetic theory orderings. Finally, the formalism is used to study dissipation in the Lagrangian variable picture where, in the context of extended magnetohydrodynamics, non-local dissipative brackets naturally emerge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Deuteron-induced nucleon transfer reactions within an ab initio framework: First application to p -shell nuclei

Low-energy transfer reactions in which a proton is stripped from a deuteron projectile and dropped into a target play a crucial role in the formation of nuclei in both primordial and stellar nucleosynthesis, as well as in the study of exotic nuclei using radioactive beam facilities and inverse kinematics. Here, ab initio approaches have been successfully applied to describe the 3 H(d,n) 4 He and 3 He(d,p) 4 He fusion processes. An ab initio treatment of transfer reactions would also be desirable for heavier targets. In this work, we extend the ab initio description of (d,p) reactions to processes with light p-shell nuclei. As a first application, we study the elastic scattering of deuterium on 7 Li and the 7 Li(d,p) 8 Li transfer reaction based on a two-body Hamiltonian. We use the no-core shell model to compute the wave functions of the nuclei involved in the reaction, and describe the dynamics between targets and projectiles with the help of microscopic-cluster states in the spirit of the resonating group method. The shapes of the excitation functions for deuterons impinging on 7 Li are qualitatively reproduced up to the deuteron breakup energy. The interplay between d– 7 Li and p– 8 Li particle-decay channels determines some features of the 9 Be spectrum above the d+ 7 Li threshold. Our prediction for the parity of the 17.298 MeV resonance is at odds with the experimental assignment. Deuteron stripping reactions with p-shell targets can now be computed ab initio , but calculations are very demanding. Finally, a quantitative description of the 7 Li(d,p) 8 Li reaction will require further work to include the effect of three-nucleon forces and additional decay channels and to improve the convergence rate of our calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗