Search NASA⌕ Search

SEARCH · Search NASA

Results for “flexible packaging”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

GNET2: an R package for constructing gene regulatory networks from transcriptomic data

Abstract Motivation The Gene Network Estimation Tool (GNET) is designed to build gene regulatory networks (GRNs) from transcriptomic gene expression data with a probabilistic graphical model. The data preprocessing, model construction and visualization modules of the original GNET software were developed on different programming platforms, which were inconvenient for users to deploy and use. Results Here, we present GNET2, an improved implementation of GNET as an integrated R package. GNET2 provides more flexibility for parameter initialization and regulatory module construction based on the core iterative modeling process of the original algorithm. The data exchange interface of GNET2 is handled within an R session automatically. Given the growing demand for regulatory network reconstruction from transcriptomic data, GNET2 offers a convenient option for GRN inference on large datasets. Availability and implementation The source code of GNET2 is available at https://github.com/jianlin-cheng/GNET2. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Codebase release r0.3 for SmoQyDQMC.jl

We introduce the SmoQyDQMC.jl package, a Julia implementation of the determinant quantum Monte Carlo algorithm. SmoQyDQMC.jl supports generalized tight-binding Hamiltonians with on-site Hubbard and generalized electron-phonon ( e e -ph) interactions, including non-linear e e -ph coupling and anharmonic lattice potentials. Our implementation uses hybrid Monte Carlo methods with exact forces for sampling the phonon fields, enabling efficient simulation of low-energy phonon branches, including acoustic phonons. The SmoQyDQMC.jl package also uses a flexible scripting interface, allowing users to adapt it to different workflows and interface with other software packages in the Julia ecosystem. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDQMC.jl or installed using the Julia package manager. The online documentation, including examples, can be obtained from our document page at https://smoqysuite.github.io/SmoQyDQMC.jl/stable/.

Cohen-Stead, Benjamin (ORCID:0000000279156280)↗
DOE OSTI2020

Designing Flexibility into the Authorized Radioactive Contents of the 9982 Shipping Package

The 9982 radioactive material shipping package, or the 9982, differs from the others by allowing a multitude of radionuclides instead of a single defined set. While allowing flexibility, this requires more justification on why these contents would be worthwhile and why they would not cause various safety hazards when shipped together. The latter was covered through mass limit calculations, and the potential uses for the package are shown through comparison with historical shipments. Here, the mass limits were already calculated[1] and used to show three example shipments are suitable for the 9982 as well. Plutonium stored in 3013 containers[2], training sources shipped in 9977 packages[3], and americium standards shipped in 9978 packages[4] were all analyzed. The mass of each radionuclide and the corresponding mass limit were used to first determine if the listed content could be shipped. If so, the maximum allowed mass of such contents is also calculated in order to see if the 200-gram fissile limit for the 9982 would be violated if additional material was packed. The sum-of-the-fractions method produces contents that do not violate the mass limits or exceed the 200-gram fissile limit. These sets also serve as realistic examples of what may be shipped in the 9982. Well-founded example contents will help the approval of the package by showing its compatibility with previously shipped material. Unfounded hypothetical contents would not show the usefulness of having a wide variety of allowed radionuclides. More contents may be developed in order to incorporate other radionuclides that were not present in these three examples. The light elements will also need to be evaluated due to their exclusion currently preventing some materials from being allowed in the 9982.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Transporting Non-Compliant TRU Wastes in the OPTIMUS{sup TM} Packages - 20493

The OPTIMUS{sup TM} product line of packages was developed with the purpose of providing a versatile and modular packaging option for shipping problematic wastes and fissile material contents. The product line includes a high-activity design in the OPTIMUS-H and a low activity design in the OPTIMUS-L. The two variants utilize a singular containment vessel design, that is enclosed in different protective components that offer different levels of shielding along with thermal and impact protection. The thick shielding provided by the OPTIMUS-H packaging allows for higher activity contents than the OPTIMUS-L to be transported. But the lightweight design of the OPTIMUS-L packaging allows for more packages to be transported in a single shipment. The containment vessel design shared between the two packages provides leak-tight containment of all radioactive contents along with the capabilities to easily leak test and the option to inert and backfill the contents, as necessary, prior to each shipment of the package. Together the OPTIMUS package designs offer significant flexibility and are capable of handling a wide variety of waste materials and other radioactive contents. One of the primary contents covered in the initial design effort for these packages is TRU waste contents beyond the standard waste materials that are compliant with the WIPP Waste Acceptance Criteria. More specifically, the initial content of interest is TRU Waste drums containing sealed containers with potentially flammable gases. While there are multiple other packaging options available for transporting standard WIPP compliant TRU wastes, the goal of the OPTIMUS packages is to offer a superior option for transporting both standard TRU wastes as well as the more problematic non-compliant wastes, among other contents. The non-compliant TRU waste contents explicitly included for the OPTIMUS packages are standard aerosol cans and DOT 3E lecture bottles. However, the methods applied for the package containment can be easily adjusted to cover other sealed container types with potentially flammable gases. The primary challenges with including these items are both the obvious issue of potential for flammable gases (e.g. aerosol propellants) in the package, but also the uncertainty in the exact state of the contents. Because these desired contents are waste materials, the characterization of the materials present in the waste may include some uncertainties. For example, though it may be known that there are one or more aerosol cans in a TRU waste drum, it may not be known if this can is full, spent, or anywhere in between. Also there may be equal uncertainty in the contents of the aerosol can, specifically in the potentially flammable propellant remaining in the can. To include these types of non-compliant items as acceptable contents for the package, the methods utilized in the safety analyses of the OPTIMUS packages must consider all of the uncertainties in the characterization of the waste. The methods utilized cover a range of concerns with transporting contents of this nature including pressure buildup, gas generation, and gaseous combustion for demonstrating the containment of the package. The ability to transport these problematic contents in the OPTIMUS packages gives TRU waste generating sites the option to relocate these drums to an offsite location where the non-compliant items can be properly managed through removal or destruction. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

An R Shiny graphical user interface for analyzing, visualizing, and interpreting high precision mass spectrometric data

There is currently a lack of software that meets the needs for the analysis of raw data produced by modern isotope ratio mass spectrometers for both R&D and routine use at SRNL and other US national labs • Needs to accommodate multiple isotope systems, instruments, and manufacturers • Include modern statistical methods and handling/visualization of uncertainty • Flexible software with transparent (no “black box”) and reproducible methods • This project is inspired by existing discipline-specific data analysis software (e.g., Tripoli1 , ET_Redux2 , IsoplotR3) used in the geochemical community • Our goal is to build an open source data analysis software package that focuses on flexibility, transparency, and reproducibility

Labone, Elizabeth↗
DOE OSTI2025

An R shiny graphical user interface for highprecision mass spectrometric data analysis

• There is currently a lack of software that meets the needs for the analysis of raw data produced by modern isotope ratio mass spectrometers for both R&D and routine use at SRNL and other US national labs • Needs to accommodate multiple isotope systems, instruments, and manufacturers • Include modern statistical methods and handling/visualization of uncertainty • Flexible software with transparent (no “black box”) and reproducible methods • This project is inspired by existing discipline-specific data analysis software (e.g., Tripoli1 , ET_Redux2, IsoplotR3) used in the geochemical community • Our goal is to build an open source data analysis software package that focuses on flexibility, transparency, and reproducibility

LABONE, ELIZABETH↗
DOE OSTI2026

Field testing and validation of a low-cost MPC for demand flexibility for grid-interactive K-12 schools

K-12 school buildings account for the highest energy consumption within the public sector. Implementing advanced HVAC controls in grid-interactive K-12 schools could bring substantial economic advantages and grid flexibility. Our previous study demonstrated that a low-cost model predictive control (MPC) solution, which coordinates multiple packaged units, can enable demand flexibility without major hardware upgrades. However, a significant gap remains between academic pilots and market-ready scalable solutions. This paper extends the previous single-site pilot to a multi-site demonstration involving three school campuses (95 total units) through a commercial technology transfer process. Addressing the challenge of verifying performance with sparse field data, we present a new statistical approach using Bayesian methods to estimate the MPC’s effect on peak demand. Unlike traditional methods, this approach robustly quantifies uncertainty in non-normal, limited datasets. The results confirm the solution’s replicability, achieving a 21.6–38.9% reduction in HVAC peak demand (10.8–22.1% at the site-level) with > 98% probability across diverse locations. Finally, we document critical barriers to scaling software-as-a-service (SaaS) solutions–such as API instability and diverse legacy systems–and offer practical strategies to accelerate the commercial adoption of grid-interactive efficient buildings.

Ham, Sang Woo↗
DOE OSTI2020

DLHub: Simplifying publication, discovery, and use of machine learning models in science

Machine Learning (ML) has become a critical tool enabling new methods of analysis and driving deeper understanding of phenomena across scientific disciplines. There is a growing need for "learning systems" to support various phases in the ML lifecycle. While others have focused on supporting model development, training, and inference, few have focused on the unique challenges inherent in science, such as the need to publish and share models and to serve them on a range of available computing resources. In this paper, we present the Data and Learning Hub for science (DLHub), a learning system designed to support these use cases. Specifically, DLHub enables publication of models, with descriptive metadata, persistent identifiers, and flexible access control. It packages arbitrary models into portable servable containers, and enables low-latency, distributed serving of these models on heterogeneous compute resources. In this work, we show that DLHub supports low-latency model inference comparable to other model serving systems including TensorFlow Serving, SageMaker, and Clipper, and improved performance, by up to 95%, with batching and memoization enabled. We also show that DLHub can scale to concurrently serve models on 500 containers. Finally, we describe five case studies that highlight the use of DLHub for scientific applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

rlmolecule: A library for general-purpose material and molecular optimization using AlphaZero-style reinforcement learning

This library includes in-progress code for the optimization of materials and molecules using reinforcement learning. This project seeks to develop a generalized machine learning approach for optimizing targeted, and often complex, functional properties over the space of possible material structures, allowing faster identification of promising candidates. Electronic and transport properties of materials are determined by their molecular structure (for molecules) or their crystal structure (for in-organic crystalline materials). The atomic composition, bonding, and 3-D-spatial arrangement in these systems therefore represent a vast, discontinuous search space for optimal candidates. This library implements AlphaZero style reinforcement learning applied to two worked examples: the optimization of stable organic radicals for redox flow batteries, and the determination of stable electrolyte species for solid state batteries. The current code contains proof-of-concept results run on the Eagle HPC system, while the completed package will be a flexible tool for material optimization across of number of energy-relevant fields, which leverages cloud compute resources for the majority of the computational heavy lifting.

Biagioni, David↗
DOE OSTI2026

kessel

Kessel is a tool to create and drive continuous integration (CI) and developer workflows through a unified interface across multiple code projects and environments. It serves as a driver and integration layer for build systems and package managers, providing a flexible library of reusable components to build and execute complex workflows consistently.

Berger, Richard [@lanl]↗
DOE OSTI2023

Fast and versatile sequence-independent protein docking for nanomaterials design using RPXDock

Computationally designed multi-subunit assemblies have shown considerable promise for a variety of applications, including a new generation of potent vaccines. One of the major routes to such materials is rigid body sequence-independent docking of cyclic oligomers into architectures with point group or lattice symmetries. Current methods for docking and designing such assemblies are tailored to specific classes of symmetry and are difficult to modify for novel applications. Here we describe RPXDock, a fast, flexible, and modular software package for sequence-independent rigid-body protein docking across a wide range of symmetric architectures that is easily customizable for further development. RPXDock uses an efficient hierarchical search and a residue-pair transform ( RPX ) scoring method to rapidly search through multidimensional docking space. We describe the structure of the software, provide practical guidelines for its use, and describe the available functionalities including a variety of score functions and filtering tools that can be used to guide and refine docking results towards desired configurations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

popclass: A Python Package for Classifying Microlensing Events

popclass is a Python package that provides a flexible, probabilistic framework for classifying the lens of a gravitational microlensing event. Gravitational microlensing occurs when a massive foreground object (e.g., a star, white dwarf or black hole) passes in front of and lenses the light from a distant background source. This causes an apparent brightening, and shift in position, of the background source. In most cases, characteristics of the microlensing signal do not contain enough information to definitively identify the lens type. Different lens types lie in different but overlapping regions of the characteristics of the microlensing signal. For example, black holes tend to be more massive than stars and therefore cause microlensing signals that are longer. Current Galactic simulations enable us to predict where different lens types lie in the observational space and can therefore be used to classify events (e.g., Lam et al., 2020). popclass allows the user to match the characteristics of a microlensing signal with a simulation of the Galaxy to calculate lens type probabilities for the event (see Figure 1). Constraints on any microlensing signal properties and any Galactic model can be used. popclass comes with an interface to ArviZ (Kumar et al., 2019) and PyMultiNest (Buchner et al., 2014) for microlensing signal constraints, as well as pre-loaded Galactic models, plotting functionality, and methods to quantify the classification uncertainty. The probabilistic framework for popclass was developed in Perkins et al. (2024), used in Fardeen et al. (2024) and has been applied to classifying events in Kaczmarek et al. (2025).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Robust galactomannan/graphene oxide film with ultra-flexible, gas barrier and self-clean properties

Here, this study examines a facile technology to manufacture food packaging alternatives with superior mechanical, ultra-flexible, gas barrier and self-cleaning properties, based on green and benign starting materials. A novel galactomannan (GM) was isolated from the Sesbania cannabina seeds, which was used as a matrix for the fabrication of GM-based films. Inspired by the brick-and-mortar structure of natural nacre, a facile method was adopted to fabricate an artificial nacre based on the self-assembly of GM and borate crosslinked graphene oxide (GO). These GM/GO composites are ultra-flexible, which can be folded into various shapes. The tensile strength reached 135.54 MPa which is 2.40 times that of the pure GM film. In addition, after coating with the poly(dimethylsiloxane) (PDMS), these films became hydrophobic (WCA around 120°) with self-cleaning properties. Our study further revealed that the oxygen and water vapor permeabilities were improved with the introduction of GO and PDMS coating.

36 MATERIALS SCIENCE↗
DOE OSTI2023

PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis

Abstract. This paper describes the new open-source framework PyFLEXTRKR (Python FLEXible object TRacKeR), a flexible atmospheric feature tracking software package with specific capabilities to track convective clouds from a variety of observations and model simulations. This software can track any atmospheric 2D objects and handle merging and splitting explicitly. The package has a collection of multi-object identification algorithms, scalable parallelization options, and has been optimized for large datasets including global high-resolution data. We demonstrate applications of PyFLEXTRKR on tracking individual deep convective cells and mesoscale convective systems from observations and model simulations ranging from large-eddy resolving (∼100s m) to mesoscale (∼10s km) resolutions. Visualization, post-processing, and statistical analysis tools are included in the package. New Lagrangian analyses of convective clouds produced by PyFLEXTRKR applicable to a wide range of datasets and scales facilitate advanced model evaluation and development efforts as well as scientific discovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

rmap: An R package to plot and compare tabular data on customizable maps across scenarios and time

`rmap` is an R package that allows users to easily plot tabular data (CSV or R data frames) on maps without any Geographic Information Systems (GIS) knowledge. Maps produced by `rmap` are `ggplot` objects and thus capitalize on the flexibility and advancements of the `ggplot2` package and all elements of each map are thus fully customizable. Additionally `rmap` automatically detects and produces comparison maps if the data has multiple scenarios or time periods as well as animations for time series data. Advanced users can load their own shapefiles if desired. `rmap` comes with a range of pre-built color palettes but users can also provide any `R` color palette or create their own as needed. Four different legend types are available to highlight different kinds of data distributions. The input spatial data can be both gridded or polygon data. `rmap` is desgined in particular for comparing spatial data across scenarios and time periods and comes preloaded with standard country, state, and basin maps as well as custom maps compatible with the Global Change Analysis Model (GCAM) spatial boundaries. `rmap` has a growing number of users and its products have been used in multiple multisector dynamics publications as well as a required dependency in other R packages such as `rfasst` and `metis`. `rmap's` automatic processing of tabular data using pre-built map selection, difference map calculations, faceting, and animations offers unique functionality which makes it a powerful and yet simple tool for users looking to explore multi-sector, multi-scenario data across space and time.

58 GEOSCIENCES↗
DOE OSTI2025

IDAES GTEP 0.1 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Generation and Transmission Expansion Planning (GTEP) package provides a Pyomo-based implementation of a modular, flexible, Generalized Disjunctive Programming (GDP) formulation for power infrastructure planning problems. This package is designed with the following goals in mind: - Abstract GTEP modeling away from any particular case study or fixed modeling assumptions (e.g., technologies, temporal resolution, spatial resolution, policy implications, etc.) - Admit flexible decision sets and heterogeneous parameterization - Allow high-level modeling options to be understood easily, chosen modularly, and changed rapidly

AS↗
DOE OSTI2024

ZMPY3D: accelerating protein structure volume analysis through vectorized 3D Zernike moments and Python-based GPU integration

Abstract Motivation Volumetric 3D object analyses are being applied in research fields such as structural bioinformatics, biophysics, and structural biology, with potential integration of artificial intelligence/machine learning (AI/ML) techniques. One such method, 3D Zernike moments, has proven valuable in analyzing protein structures (e.g., protein fold classification, protein–protein interaction analysis, and molecular dynamics simulations). Their compactness and efficiency make them amenable to large-scale analyses. Established methods for deriving 3D Zernike moments, however, can be inefficient, particularly when higher order terms are required, hindering broader applications. As the volume of experimental and computationally-predicted protein structure information continues to increase, structural biology has become a “big data” science requiring more efficient analysis tools. Results This application note presents a Python-based software package, ZMPY3D, to accelerate computation of 3D Zernike moments by vectorizing the mathematical formulae and using graphical processing units (GPUs). The package offers popular GPU-supported libraries such as CuPy and TensorFlow together with NumPy implementations, aiming to improve computational efficiency, adaptability, and flexibility in future algorithm development. The ZMPY3D package can be installed via PyPI, and the source code is available from GitHub. Volumetric-based protein 3D structural similarity scores and transform matrix of superposition functionalities have both been implemented, creating a powerful computational tool that will allow the research community to amalgamate 3D Zernike moments with existing AI/ML tools, to advance research and education in protein structure bioinformatics. Availability and implementation ZMPY3D, implemented in Python, is available on GitHub (https://github.com/tawssie/ZMPY3D) and PyPI, released under the GPL License.

Lai, Jhih-Siang (ORCID:0000000156775890)↗
DOE OSTI2020

Guest Editorial: Special Issue on InterPACK 2019 - Part 1

This is a collection of papers drawn from the 2019 ASME InterPACK Conference. The content spans the areas of heterogeneous integration, servers, flexible and wearable electronics, photonics, power electronics, energy storage, and autonomous and electric vehicles.

47 OTHER INSTRUMENTATION↗