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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 1,801 records · Page 100
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

The Separate Physics and Dynamics Experiment (SPADE) framework for determining resolution awareness: A case study of microphysics

The ability to use multi-resolution dynamical cores for weather and climate modeling is pushing the atmospheric community towards developing scale aware or, more specifically, resolution aware parameterizations that will function properly across a range of grid spacings. Determining the resolution dependence of specific model parameterizations is difficult due to strong resolution dependencies in many pieces of the model. This study presents the Separate Physics and Dynamics Experiment (SPADE) framework that can be used to isolate the resolution dependent behavior of specific parameterizations without conflating resolution dependencies from other portions of the model. To demonstrate the SPADE framework, the resolution dependence of the Morrison microphysics from the Weather Research and Forecasting model and the Morrison-Gettelman microphysics from the Community Atmosphere Model are compared for grid spacings spanning the cloud modeling gray zone. It is shown that the Morrison scheme has stronger resolution dependence than Morrison-Gettelman, and that the ability of Morrison-Gettelman to use partial cloud fractions is not the primary reason for this difference. This study also discusses how to frame the issue of resolution dependence, the meaning of which has often been assumed, but not clearly expressed in the atmospheric modeling community. It is proposed that parameterization resolution dependence can be expressed in terms of "resolution dependence of the first type," RA1, which implies that the parameterization behavior converges towards observations with increasing resolution, or as "resolution dependence of the second type," RA2, which requires that the parameterization reproduces the same behavior across a range of grid spacings when compared at a given coarser resolution. RA2 behavior is considered the ideal, but brings with it serious implications due to limitations of parameterizations to accurately estimate reality with coarse grid spacing. The type of resolution awareness developers should target in their development depends upon the particular modeler’s application.

Gustafson, William I.↗
DOE OSTI2018

Fibers with Hyper‐Crosslinked Functional Porous Frameworks

Abstract The incorporation of robust porous frameworks into polymer fibers with handleable morphologies and flexible chemical compositions exhibits significant advantages for device fabrication in a wide range of applications. However, the soft linear polymeric chains of the fibers make the generation of nanopores extremely challenging. Herein, a facile synthetic strategy based on a combination of functional monomer grafting and hyper‐crosslinking technology is developed for the porous engineering of polymeric fibers. In this methodology, the nanoporous framework originating from the hyper‐crosslinking of aromatic monomers is covalently grafted onto fibers, which is beneficial to retaining their unique fiber morphology and to preserving their excellent mechanical properties. Moreover, this promising protocol can be further extended to the porous functionalization of polymeric matrices with diverse morphologies for target‐specific applications.

Sheng, Yujie↗
DOE OSTI2025

A Poromechanical Framework for Internal Interactions Induced by Solid Inclusions

The framework of poromechanics is generalized to simulate the multiscale behavior of porous media subjected to internal loadings stemming from the growth of solid inclusions. This generalization is designed to enable the study of anisotropic internal stress generation from solid growth within the pores, while recovering isotropic fluid-induced loading as a particular case. For this purpose, a mathematical strategy to define constitutive tensors in a thermodynamically consistent form is proposed, thus offering new opportunities for determining the poromechanical properties of a porous solid through advanced experimentation or micromechanical models. The framework is specialized by means of established elastic solutions for single pore–matrix interaction, as well as through homogenization schemes considering the interaction among congruent pores. In particular, the second Eshelby solution and the Tanaka–Mori–Benveniste homogenization scheme are used to derive a microporoelastic model. At an elemental scale, the model is tested under mixed control conditions by replicating different scenarios of geomaterial testing. In addition, the model characteristics are outlined with reference to inelastic microscopic loadings replicating chemo-mechanical forcing, such as expansive crystal formation. Through a series of parametric analyses, it is shown that the microstructure of the pores significantly influences the properties of porous media. Most notably, it is shown that the effects of a solid forming within the pores depend in a highly nonlinear fashion on the constitutive characteristics of the inhomogeneities and can therefore not be readily quantified or predicted without models capturing the diverse multiscale interactions among pores, inhomogeneities, and matrix.

chemomechanics↗
DOE OSTI2022

An optimized ChIP-Seq framework for profiling histone modifications in Chromochloris zofingiensis

The eukaryotic green alga Chromochloris zofingiensis is a reference organism for studying carbon partitioning and a promising candidate for the production of biofuel precursors. Recent transcriptome profiling transformed our understanding of its biology and generally algal biology, but epigenetic regulation remains understudied and represents a fundamental gap in our understanding of algal gene expression. Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a powerful tool for the discovery of such mechanisms, by identifying genome-wide histone modification patterns and transcription factor-binding sites alike. Here, we established a ChIP-Seq framework for Chr. zofingiensis yielding over 20 million high-quality reads per sample. The most critical steps in a ChIP experiment were optimized, including DNA shearing to obtain an average DNA fragment size of 250 bp and assessment of the recommended formaldehyde concentration for optimal DNA-protein cross-linking. We used this ChIP-Seq framework to generate a genome-wide map of the H3K4me3 distribution pattern and to integrate these data with matching RNA-Seq data. In line with observations from other organisms, H3K4me3 marks predominantly transcription start sites of genes. Our H3K4me3 ChIP-Seq data will pave the way for improved genome structural annotation in the emerging reference alga Chr. zofingiensis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Mechanistic Models as Framework for Understanding Biomarker Disposition: Prediction of Creatinine‐Drug Interactions

Creatinine is widely used as a biomarker of glomerular filtration, and, hence, renal function. However, transporter‐mediated secretion also contributes to its renal clearance, albeit to a lesser degree. Inhibition of these transporters causes transient serum creatinine elevation, which can be mistaken as impaired renal function. The current study developed mechanistic models of creatinine kinetics within physiologically based framework accounting for multiple transporters involved in creatinine renal elimination, assuming either unidirectional or bidirectional‐OCT2 transport (driven by electrochemical gradient). Robustness of creatinine models was assessed by predicting creatinine‐drug interactions with 10 perpetrators; performance evaluation accounted for 5% intra‐individual variability in serum creatinine. Models showed comparable predictive performances of the maximum steady‐state effect regardless of OCT2 directionality assumptions. However, only the bidirectional‐OCT2 model successfully predicted the minimal effect of ranitidine. The dynamic nature of models provides clear advantage to static approaches and most advanced framework for evaluating interplay between multiple processes in creatinine renal disposition.

Scotcher, Daniel↗
DOE OSTI2026

A multi‐variable framework for selecting WRF physics configurations at convection‐permitting scales: An Amazon wet‐season case study

Tropical convection over rainforests modulates atmospheric circulation and the energy and hydrological cycles across multiple scales. However, the scarcity of observations still limits our understanding of these processes. Although numerical models are utilized to investigate atmospheric physical processes, their performance depends on the choice of parameterizations and grid resolution. Here, in this work, we introduce and apply a multi‐variable, multi‐physics framework to evaluate and rank the Advanced Research Weather Research and Forecasting (WRF–ARW) configurations at 1‐km resolution over the central Amazon during the wet season. A 48‐member ensemble combines three land‐surface models (LSMs), four planetary boundary layer (PBL), and four microphysics (MP) schemes. Model performance for seven convection‐related near‐surface and boundary‐layer variables is assessed using Taylor diagrams and the Taylor skill score (TSS), analysis of variance (ANOVA)‐based sensitivity metrics, and non‐parametric rank tests. We then construct a combined, weighted TSS to identify configurations that are comparatively robust across variables. Results showed that most configurations reproduce near‐surface temperature, sensible and latent heat fluxes, and boundary‐layer height reasonably well, whereas humidity and rainfall remain challenging. LSM choice has the strongest impact on the surface fluxes and a secondary influence on near‐surface temperature and humidity, PBL schemes dominate boundary‐layer height, and MP schemes exert the largest control on rainfall. No single configuration is optimal for all variables, but the combination of Noah (LSM), Yonsei University (PBL), and Morrison (MP) emerges as the most robust configuration for this case, with the WRF single‐moment six‐class scheme (WSM6) providing a competitive, computationally cheaper MP alternative. The framework is general and can be applied to other regions, seasons, and convective regimes.

Amazon rainforest↗
DOE OSTI2018

Enhancing Hydrogen Generation Through Nanoconfinement of Sensitizers and Catalysts in a Homogeneous Supramolecular Organic Framework

Enrichment of molecular photosensitizers and catalysts in a confined nanospace is conducive for photocatalytic reactions due to improved photoexcited electron transfer from photosensitizers to catalysts. Herein, the self-assembly of a highly stable 3D supramolecular organic framework from a rigid bipyridine-derived tetrahedral monomer and cucurbit[8]uril in water, and its efficient and simultaneous intake of both [Ru(bpy) 3 ] 2+ -based photosensitizers and various polyoxometalates, that can take place at very low loading, are reported. Finally, the enrichment substantially increases the apparent concentration of both photosensitizer and catalyst in the interior of the framework, which leads to a recyclable, homogeneous, visible light-driven photocatalytic system with 110-fold increase of the turnover number for the hydrogen evolution reaction.

08 HYDROGEN↗
DOE OSTI2019

Highly Ordered N-Doped Carbon Dots Photosensitizer on Metal–Organic Framework-Decorated ZnO Nanotubes for Improved Photoelectrochemical Water Splitting

In spite of having several advantages such as low cost, high chemical stability, and environmentally safe and benign synthetic as well as operational procedures, the full potential of carbon dots (CDs) are yet to be explored as photosensitizers due to the challenges associated with the fabrication of well-arrayed CDs with any other photocatalytic heterostructures. In the present study, a unique combination of Metal-organic frameworks (MOFs) decorated Zinc Oxide (ZnO) one-dimensional (1D) nanostructures as host and CDs as guest species have been explored on account of its potential applications in photoelectrochemical (PEC) water splitting performance. Our synthetic strategy to incorporate well-defined nitrogen-doped carbon dots (N-CDs) array onto zeolitic imidazolate framework-8 (ZIF-8) anchored on ZnO 1D nanostructures allows a facile unification of different components which subsequently plays a decisive role in improving the material’s PEC water splitting performance. Simple extension of such strategies is expected to offer significant advantages for the preparation of CDs-based heterostructures for photo(electro)catalytic and other related applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Framework Polymorphism and Modular Crystal Structures of Uranyl Vanadates of Divalent Cations: Synthesis and Characterization of M (UO 2 )(V 2 O 7 ) ( M = Ca, Sr) and Sr 3 (UO 2 )(V 2 O 7 ) 2

In this work, Uranyl vanadate compounds with divalent cations, M (UO 2 )(V 2 O 7 ) ( M = Ca, Sr) and Sr 3 (UO 2 )(V 2 O 7 ) 2 , were synthesized by flux crystal growth, and their crystal structures were solved using single-crystal X-ray diffraction data. Ca(UO 2 )V 2 O 7 and Sr(UO 2 )V 2 O 7 were synthesized from reactants with molar ratios M:U:V of 1:1:2 and identical heating conditions, and increasing the M:U:V ratio to 3:1:4 resulted in Sr 3 (UO 2 )(V 2 O 7 ) 2 . Crystallographic data for M(UO2)V2O7 compounds are: a = 7.1774(18) Å, b = 6.7753(17) Å, c = 8.308(2) Å; V = 404.01(18) Å 3 ; space group Pmn2 1 , Z = 2 for Ca; a = 13.4816(11) Å, b = 7.3218(6) Å, c = 8.4886(7) Å; V = 837.91(12) Å3; space group Pnma , Z = 4 for Sr. Compound Sr 3 (UO 2 )(V 2 O 7 ) 2 has a = 6.891(3) Å, b = 7.171(3) Å, c = 14.696(6) Å, α = 85.201(4)°, β = 78.003(4)°, γ = 89.188(4)°; V = 707.9(5) Å 3 ; space group P1, Z = 2. The framework structure of Sr(UO 2 )(V 2 O 7 ) is related to that of Pb(UO 2 )(V 2 O 7 ) reported previously, while that of Ca(UO 2 )(V 2 O 7 ) has a different topology. The topological polymorphism of the [(UO 2 )(V 2 O 7 )]-type framework may be due to the differing ionic radii of the guest M 2+ cations. Compound Sr 3 (UO 2 )(V 2 O 7 ) 2 has a modular structure based on two different types of electroneutral layers: [Sr(UO 2 )(V 2 O 7 )] and [Sr 2 (V 2 O 7 )]. This report calculated Structural complexities, and Raman spectra were collected and their peaks were assigned.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

A Cloud-Based Decision Support System Framework for Hydropower Biological Evaluation

Hydropower has become one of the most important energy sources: it accounts for more than 80% of the world’s renewable energy and about 16% of all the energy in the world. Significantly more hydropower capacity is planned to be developed. However, hydro-structures, including powered dams, may have adverse biological effects on fishes, especially on migrating fish. For instance, fish can be injured or even killed when they pass through turbines. This is why biological evaluations on hydro-structures are greatly needed to estimate fish injury and mortality rates. The Hydropower Biological Evaluation Toolset (HBET) is an integrated suite of science-based desktop tools designed to evaluate whether the hydraulic conditions of hydropower structures are fish friendly by analyzing collected data and providing estimated injury and mortality rates. Sensor Fish, a small, autonomous sensor package, is used by HBET to record data describing the conditions that live fish passing through a hydropower structure will face. In this paper, we incorporated cloud computing into HBET, and migrated it into a cloud-based decision support system framework for hydropower biological evaluation. This will make the evaluation systems more scalable and flexible; however, this also introduces a significant challenge: how to maintain the security while retaining scalability and flexibility. We discuss the technical methodologies and algorithms implemented in the proposed framework, and analyze the countermeasures implemented therein.

Decision Support System, Hydropower, Dam, Fish Inj↗
DOE OSTI2019

A Real-Time Big Data Control-Theoretical Framework for Cyber-Physical-Human Systems [Book Chapter]

It is known that cyber-physical-human systems naturally arise from interdependent infrastructure systems and smart connected communities. Such applications require ubiquitous information sensing and processing, intelligent machine-to-machine communication for a seamless coordination, as well as intelligent interactions between humans and machines. This chapter presents a control-theoretical framework to model heterogeneous physical dynamic systems, information and communication, as well as cooperative controls and/or distributed optimization of such interconnected systems. It is shown that efficient analytical and computational algorithms can be modularly designed and hierarchically implemented to operate and optimize cyber-physical-human systems, first to quantify individually the input–output relationship of nonlinear dynamic behaviors of every physical subsystem, then to coordinate locally both cyber-physical interactions of neighboring agents as well as physical-human interactions, and finally to dynamically model and optimize the overall networked system. The hierarchical structure makes the overall optimization and control problem scalable and solvable. Moreover, the three levels integrate individual designs and optimization, distributed cooperative optimization, and decision-making through real-time, data-driven, model-based learning and control. Specifically, one of the contributions of the chapter is to demonstrate how the combination of dissipativity theory and cooperative control serves as a natural framework and promising tools to analyze, optimize, and control such large-scale system. Application to digital grid is investigated as an illustrative example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

OpenGraphGym: A Parallel Reinforcement Learning Framework for Graph Optimization Problems

This paper presents an open-source, parallel AI environment (named OpenGraphGym) to facilitate the application of reinforcement learning (RL) algorithms to address combinatorial graph optimization problems. This environment incorporates a basic deep reinforcement learning method, and several graph embeddings to capture graph features, it also allows users to rapidly plug in and test new RL algorithms and graph embeddings for graph optimization problems. This new open-source RL framework is targeted at achieving both high performance and high quality of the computed graph solutions. This RL framework forms the foundation of several ongoing research directions, including 1) benchmark works on different RL algorithms and embedding methods for classic graph problems; 2) advanced parallel strategies for extreme-scale graph computations, as well as 3) performance evaluation on real-world graph solutions.

Zheng, Weijian↗
DOE OSTI2020

Software Framework for Federated Science Instruments

There is an unprecedented promise of enhanced capabilities for federations of leadership computing systems and experimental science facilities by leveraging software technologies for fast and efficient operations. These federations seek to unify different science instruments, both computing and experimental, to effectively support science users and operators to execute complex workflows. The FedScI project addresses the software challenges associated with the formation and operation of federated environments by leveraging recent advances in containerization of software and softwarization of hardware. We propose a software framework to streamline the federation usage by science users and it’s provisioning and operations by facility providers. A distinguishing element of our work is the support for improved interaction between experimental devices, such as beam-line instruments, and more traditional high-performance computing resources, including compute, network, storage systems. We present guiding principles for the software framework and highlight portions of a current prototype implementation. We describe our science use case involving neutron imaging beam-lines (SNAP/BL-3, Imaging/CG-1D) at the Spallation Neutron Source and High Flux Isotope Reactor facilities at Oak Ridge National Laboratory. Additionally, we detail plans for a more direct instrument interaction within a federated environment, which could enable more advanced workflows with feedback loops to shorten the time to science.

Naughton III, Thomas↗
DOE OSTI2021

Phoenix: A Scalable Streaming Hypergraph Analysis Framework

We present Phoenix, a scalable hypergraph analytics framework for data analytics and knowledge discovery that was implemented on the leadership class computing platforms at Oak Ridge National Laboratory (ORNL). Our software framework comprises a distributed implementation of a streaming server architecture which acts as a gateway for various hypergraph generators/external sources to connect. Phoenix has the capability to utilize diverse hypergraph generators, including HyGen, a very large-scale hypergraph generator developed by ORNL. Phoenix incorporates specific algorithms for efficient data representation by exploiting hidden structures of the hypergraphs. Our experimental results demonstrate Phoenix’s scalable and stable performance on massively parallel computing platforms. Phoenix’s superior performance is due to the merging of high-performance computing with data analytic.

Kurte, Kuldeep↗
DOE OSTI2025

An End-to-End Framework for Verifying and Validating Manufacturing Design Integrity

Cyber attacks on networked automated manufacturing systems can severely impact part quality. In fact, malicious modifications may be introduced at any point during the manufacturing lifecycle. Therefore, it is vital to verify and validate that manufactured parts conform to their designs. This chapter describes a formal, end-to-end framework that verifies and validates the design integrity of manufactured parts by considering all potential points of alteration during precision manufacturing processes. The framework prevents unauthorized changes to computer-aided designs, verifies the correctness of translations from CAD models to G-code, maintains the integrity of G-code transferred to manufacturing machines, verifies the runtime execution of G-code and part geometry, and considers the contexts of manufacturing machine operations and how manufactured parts could be altered.

Jablonski, Matthew [Cybersecurity Manufacturing In↗
DOE OSTI2019

The simplified likelihood framework

We discuss the simplified likelihood framework as a systematic approximation scheme for experimental likelihoods such as those originating from LHC experiments. We develop the simplified likelihood from the Central Limit Theorem keeping the next-to-leading term in the large N expansion to correctly account for asymmetries. Moreover, we present an efficient method to compute the parameters of the simplified likelihood from Monte Carlo simulations. The approach is validated using a realistic LHC-like analysis, and the limits of the approximation are explored. Finally, we discuss how the simplified likelihood data can be conveniently released in the HepData error source format and automatically built from it, making this framework a convenient tool to transmit realistic experimental likelihoods to the community.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

A conformal truncation framework for infinite-volume dynamics

Here, we present a new framework for studying conformal field theories deformed by one or more relevant operators. The original CFT is described in infinite volume using a basis of states with definite momentum, P , and conformal Casimir, C. The relevant deformation is then considered using lightcone quantization, with the resulting Hamiltonian expressed in terms of this CFT basis. Truncating to states with C ≤ C max , one can numerically find the resulting spectrum, as well as other dynamical quantities, such as spectral densities of operators. This method requires the introduction of an appropriate regulator, which can be chosen to preserve the conformal structure of the basis. We check this framework in three dimensions for various perturbative deformations of a free scalar CFT, and for the case of a free O(N) CFT deformed by a mass term and a non-perturbative quartic interaction at large- N . In all cases, the truncation scheme correctly reproduces known analytic results. As a result, we also discuss a general procedure for generating a basis of Casimir eigenstates for a free CFT in any number of dimensions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Dilaton EFT framework for lattice data

We develop an effective-field-theory (EFT) framework to analyze the spectra emerging from lattice simulations of a large class of confining gauge theories. Simulations of these theories, for which the light-fermion count is not far below the critical value for transition to infrared conformal behavior, have indicated the presence of a remarkably light singlet scalar particle. We incorporate this particle by including a scalar field in the EFT along with the Nambu-Goldstone bosons (NGB’s), and discuss the application of this EFT to lattice data. We highlight the feature that data on the NGB’s alone can tightly restrict the form of the scalar interactions. As an example, we apply the framework to lattice data for an SU(3) gauge theory with eight fermion flavors, concluding that the EFT can describe the data well.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

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