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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 433 records · Page 24

All sources NASA NTRS DOE OSTI

DOE OSTI2023

The Structure of Maltooctaose-Bound Escherichia coli Branching Enzyme Suggests a Mechanism for Donor Chain Specificity

Glycogen is the primary storage polysaccharide in bacteria and animals. It is a glucose polymer linked by α-1,4 glucose linkages and branched via α-1,6-linkages, with the latter reaction catalyzed by branching enzymes. Both the length and dispensation of these branches are critical in defining the structure, density, and relative bioavailability of the storage polysaccharide. Key to this is the specificity of branching enzymes because they define branch length. Herein, we report the crystal structure of the maltooctaose-bound branching enzyme from the enterobacteria E. coli. The structure identifies three new malto-oligosaccharide binding sites and confirms oligosaccharide binding in seven others, bringing the total number of oligosaccharide binding sites to twelve. In addition, the structure shows distinctly different binding in previously identified site I, with a substantially longer glucan chain ordered in the binding site. Using the donor oligosaccharide chain-bound Cyanothece branching enzyme structure as a guide, binding site I was identified as the likely binding surface for the extended donor chains that the E. coli branching enzyme is known to transfer. Furthermore, the structure suggests that analogous loops in branching enzymes from a diversity of organisms are responsible for branch chain length specificity. Together, these results suggest a possible mechanism for transfer chain specificity involving some of these surface binding sites.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Uncertainty Propagation within Chained Models for Machine Learning Reconstruction of Neutrino-LAr Interactions

Sequential or chained models are increasingly prevalent in machine learning for scientific applications, due to their flexibility and ease of development. Chained models are particularly useful when a task is separable into distinct steps with a hierarchy of meaningful intermediate representations. In reliability-critical tasks, it is important to quantify the confidence of model inferences. However, chained models pose an additional challenge for uncertainty quantification, especially when input uncertainties need to be propagated. In such cases, a fully uncertainty-aware chain of models is required, where each step accepts a probability distribution over the input space, and produces a probability distribution over the output space. In this work, we present a case study for adapting a single model within an existing chain, designed for reconstruction within neutrino-Argon interactions, developed for neutrino oscillation experiments such as MicroBooNE, ICARUS, and the future DUNE experiment. We test the performance of an input uncertainty-enabled model against an uncertainty-blinded model using a method for generating synthetic noise. By comparing these two, we assess the increase in inference quality achieved by exposing models to upstream uncertainty estimates.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1979

On geoid heights derived from GEOS 3 altimeter data along the Hawaiian-Emperor seamount chain

The geoid heights derived from preliminary GEOS 3 satellite radar altimeter data over the Hawaiian-Emperor seamount chain are examined. Two objectives are pursued: (1) to evaluate the contribution of the topography of the seamount chain and its compensation to the marine geoid; and (2) to determine whether geoid heights derived from GEOS 3 altimeter data can be used to provide information on isostasy at geological features such as the Hawaiian-Emperor seamount chain which formed as relatively young loads on the oceanic lithosphere. Short-wavelength geoid highs of 5-12 m over the crest of the seamount chain and geoid lows over flanking regions are observed. The geological undulations can be explained by a simple model in which the seamount-chain load is supported by a strong rigid lithospheric plate. The elastic thickness estimates agree with values based on surface ship gravity and bathymetry observations, and provide further support to the hypothesis that the elastic thickness acquired at a surface load depends on the temperature gradient of the lithosphere at the time of loading.

Watts, A. B.↗

NASA NTRS1985

Lagrangian observations of surface circulation at the Emperor Seamount chain

In a Kuroshio tracking experiment initiated in February 1977, two satellite-reporting buoys, drogued to 100-m depth, were released southeast of Kuyshu Island, Japan. These drifters crossed the Shatskiy Rise in the Kuroshio extension during May and October and then traversed the Emperor Seamount Chain. Although they reached the chain 117 days apart, their movements near the seamounts display remarkably similar patterns, demonstrating upstream meanders in the surface flow; cyclonic eddy activity immediately west of the chain; passage through the same gap associated with the Jingu and Nintoku seamounts; and a wavelike pattern present over the Hess Rise east of the chain. One drifter exhibited cyclonic eddy motion east of the chain in the lee of the Kinmei Seamount.

Vastano, A. C.↗

NASA NTRS1990

Molecular arrangements and conformations of liquid n-tridecane chains confined between two hard walls

Monte Carlo simulations based on united CH2 atoms linked with fixed bond lengths and angles, and continuously varying torsional angles subject to appropriate interaction energies, were used to study liquid n-tridecane chains confined between two parallel hard walls with 5 mm separation. The molecules located in the central region are noted to be in very close agreement with ideal unperturbed chains. Nearly all the chain units in the first segmental layer adjacent to the walls belong to two-dimensional chains, and exhibit considerable orientational correlations between neighboring segments of different chains.

Vacatello, Michele↗

NASA NTRS1991

Data-driven backward chaining

The C Language Integrated Production System (CLIPS) cannot effectively perform sound and complete logical inference in most real-world contexts. The problem facing CLIPS is its lack of goal generation. Without automatic goal generation and maintenance, forward chaining can only deduce all instances of a relationship. Backward chaining, which requires goal generation, allows deduction of only that subset of what is logically true which is also relevant to ongoing problem solving. Goal generation can be mimicked in simple cases using forward chaining. However, such mimicry requires manual coding of additional rules which can assert an inadequate goal representation for every condition in every rule that can have corresponding facts derived by backward chaining. In general, for N rules with an average of M conditions per rule the number of goal generation rules required is on the order of N*M. This is clearly intractable from a program maintenance perspective. We describe the support in Eclipse for backward chaining which it automatically asserts as it checks rule conditions. Important characteristics of this extension are that it does not assert goals which cannot match any rule conditions, that 2 equivalent goals are never asserted, and that goals persist as long as, but no longer than, they remain relevant.

Haley, Paul↗

NASA NTRS2003

Translocation of a Polymer Chain across a Nanopore: A Brownian Dynamics Simulation Study

We carried out Brownian dynamics simulation studies of the translocation of single polymer chains across a nanosized pore under the driving of an applied field (chemical potential gradient). The translocation process can be either dominated by the entropic barrier resulted from restricted motion of flexible polymer chains or by applied forces (or chemical gradient across the wall), we focused on the latter case in our studies. Calculation of radius of gyrations at the two opposite sides of the wall shows that the polymer chains are not in equilibrium during the translocation process. Despite this fact, our results show that the one-dimensional diffusion and the nucleation model provide an excellent description of the dependence of average translocation time on the chemical potential gradients, the polymer chain length and the solvent viscosity. In good agreement with experimental results and theoretical predictions, the translocation time distribution of our simple model shows strong non-Gaussian characteristics. It is observed that even for this simple tubelike pore geometry, more than one peak of translocation time distribution can be generated for proper pore diameter and applied field strengths. Both repulsive Weeks-Chandler-Anderson and attractive Lennard-Jones polymer-nanopore interaction were studied, attraction facilitates the translocation process by shortening the total translocation time and dramatically improve the capturing of polymer chain. The width of the translocation time distribution was found to decrease with increasing temperature, increasing field strength, and decreasing pore diameter.

Tian, Pu↗

NASA NTRS2010

Using SCOR as a Supply Chain Management Framework for Government Agency Contract Requirements

Enterprise Supply Chain Management consists of: Specifying suppliers to support inter-program and inter-agency efforts. Optimizing inventory levels and locations throughout the supply chain. Executing corrective actions to improve quality and lead time issues throughout the supply chain. Processing reported data to calculate and make visible supply chain performance (provide information for decisions and actions). Ensuring the right hardware and information is provided at the right time and in the right place. Monitoring the industrial base while developing, producing, operating and retiring a system. Seeing performance deep in the supply chain that could indicate issues affecting system availability and readiness.

Paxton, Joe↗

NASA NTRS2007

A Case Study Using Modeling and Simulation to Predict Logistics Supply Chain Issues

Optimization of critical supply chains to deliver thousands of parts, materials, sub-assemblies, and vehicle structures as needed is vital to the success of the Constellation Program. Thorough analysis needs to be performed on the integrated supply chain processes to plan, source, make, deliver, and return critical items efficiently. Process modeling provides simulation technology-based, predictive solutions for supply chain problems which enable decision makers to reduce costs, accelerate cycle time and improve business performance. For example, United Space Alliance, LLC utilized this approach in late 2006 to build simulation models that recreated shuttle orbiter thruster failures and predicted the potential impact of thruster removals on logistics spare assets. The main objective was the early identification of possible problems in providing thruster spares for the remainder of the Shuttle Flight Manifest. After extensive analysis the model results were used to quantify potential problems and led to improvement actions in the supply chain. Similarly the proper modeling and analysis of Constellation parts, materials, operations, and information flows will help ensure the efficiency of the critical logistics supply chains and the overall success of the program.

Tucker, David A.↗

NASA NTRSDate not supplied

Development of an End-to-End Demonstration Readout Chain for Athena-X-IFU

The X-IFU (X-ray Integral Field Unit) of the Athena (Advanced Telescope for High-ENergy Astrophysics) telescope, scheduled for launch in the early 2030's, will provide X-ray spectroscopy data with unprecedented spectral and spatial resolution. This will be achieved by a 3 kilo-pixel array of TES (transition-edge sensor) microcalorimeters. The complete detection chain is under development by a large international collaboration. The detector array will be provided by NASA Goddard Space Flight Center, the cold TDM (time domain multiplexing) electronics by NIST, the cold amplifier by VTT, the cold focal-plane assembly by SRON, the warm front-end electronics by APC, and the DRE (digital readout electronics) by IRAP. In order to perform an end-to-end demonstration of the X-IFU readout chain, a 50 mK test bench is being developed at IRAP in collaboration with CNES. The test bench is based on a two-stage ADR cryostat from Entropy GmbH and a 1024-pixel array from Goddard associated with its cold TDM readout from NIST. The setup will initially be validated using a warm electronic chain from NIST and Goddard. We will describe the complete system being installed in the cryostat and the first results obtained with these electronics. We will also review the status of the integration of the DRE prototype in the demonstration chain and the way forward in the integration and testing of the complete X-IFU readout chain.

S Beaumont↗

NASA NTRS2021

Computational Inference of Vibratory System with Incomplete Modal Information Using Parallel, Interactive and Adaptive Markov Chains

Inverse analysis of vibratory system is an important subject in fault identification, model updating, and robust design and control. It is challenging subject because 1) the problem is oftentimes underdetermined while the measurements are limited and/or incomplete; 2) many combinations of parameters may yield results that are similar with respect to actual response measurements; and 3) uncertainties inevitably exist. The aim of this research is to leverage upon computational intelligence through statistical inference to facilitate an enhanced, probabilistic framework using incomplete modal response measurement. This new framework is built upon efficient inverse identification through optimization, whereas Bayesian inference is employed to account for the effect of uncertainties. To overcome the computational cost barrier, we adopt Markov chain Monte Carlo (MCMC) to characterize the target function/distribution. Instead of using single Markov chain in conventional Bayesian approach, we develop a new sampling theory with multiple parallel, interactive and adaptive Markov chains and incorporate it into Bayesian inference. This can harness the collective power of these Markov chains to realize the concurrent search of multiple local optima. The number of required Markov chains and their respective initial model parameters are automatically determined via Monte Carlo simulation-based sample pre-screening followed by K-means clustering analysis. These enhancements can effectively address the aforementioned challenges in finite element inverse analysis. The validity of this framework is systematically demonstrated through case studies.

K Zhou↗

NASA NTRS2022

Development of an End-to-end Demonstration Readout Chain for Athena/X-IFU

The X-ray Integral Field Unit(X-IFU) of the Athena observatory, scheduled for launch in the mid2030's, will provide X-ray spectroscopy data with unprecedented spectral and spatial resolution. This will be achieved with a 2kilo-pixel array of transition-edge sensor (TES) microcalorimeters. The complete detection chain is under development by a large international collaboration. In order to perform an end-to-end demonstration of the X-IFU readout chain, a 50 mK test bench is being developed at IRAP in collaboration with CNES. The test bench uses a two-stage ADR cryostat from Entropy GmbH, a 1024-pixelarray, and will initially be operated using a warm electronics chain from NIST and NASA Goddard Space Flight Center. We describe the complete system being installed in the cryostat and the current results obtained with these electronics. We also review the status of the integration of the digital readout electronics (DRE)prototype into the demonstration chain and the plan for integrating and testing the complete X-IFU readout chain.

S Beaumont↗

DOE OSTI2022

Achieving American Leadership in the Hydrogen Supply Chain Factsheet

Hydrogen has been identified as a key energy option to enable full decarbonization of the energy system. A secure, resilient supply chain will be critical to achieving emissions reductions and capturing the economic opportunity inherent in the energy sector transition. Electrolyzers and fuel cells are two critical components of the hydrogen supply chain that today are largely nascent industries with limited data on supply chain needs and constraints. This fact sheet summarizes findings from an accompanying report that is one in a series of deep dive assessments of the energy industrial base called for in Executive Order 14017 on America’s supply chains. The report identifies key considerations for the development of water electrolyzer and fuel cell supply chains and materials, focusing on polymer electrolyte and solid oxide technologies, to meet future demand for hydrogen produced by electrolysis and achieve U.S. decarbonization goals.

Source record↗

DOE OSTI2022

Achieving American Leadership in the Solar Photovoltaics Supply Chain Factsheet

Developing U.S. photovoltaic (PV) manufacturing could mitigate global supply chain challenges and lead to tremendous benefits for the climate as well as for U.S. workers, employers, and the economy. The solar supply chain is global and reliant on products from China or companies with close ties to China. Significant growth in U.S. manufacturing across the supply chain is possible with incentives that offset the higher cost of manufacturing in the United States. Existing polysilicon production facilities are currently idle or supplying polysilicon to other industries. Expansion in the ingot and wafer sectors outside of China would create demand for existing U.S. polysilicon producers to run at high capacity. The United States can expand production of thin-film modules, which do not rely on obtaining materials from Chinese companies. The thin film supply chain is concentrated in Ohio. There is a cluster of solar module manufacturers in Alabama, Florida, and Georgia, which presents an opportunity to grow a competitive supply chain of module components in the region.

Source record↗

DOE OSTI2024

Organizational Influence on Supply Chain for Digital Energy Infrastructure: Business Models, and Policy Landscape

Significant investment is driving the essential modernization and digitization of U.S. energy infrastructure, but the United States faces a key challenge in this grid transformation: our renewable and clean energy supply chains have limited capacity to source necessary digital assets through U.S. or allied sources. Batteries and their associated power electronic interfaces are key components to delivering clean and more resilient energy delivery, providing much-needed fast ramping, emergency discharge, generation, and operations support to the electric grid. These services have grown to be invaluable over the past 10 years and will soon be an irreplaceable component of energy delivery. While there have been significant strides to move supply chains for raw and critical materials to U.S. and allied nations, the control and power electronic industry has lagged, in part because of lower cost margins. For example, the United States now has growing capacity to manufacture solar photovoltaic (PV) panels, but 90% of the inverters—which are essential to the conversion of DC to AC for grid connection and controls—are made in or source parts from the People’s Republic of China (PRC). While a global supply chain is beneficial for many economic and supply diversification reasons, presence of foreign entities of concern (FEOC) in a dominant role in this supply chain brings additional concerns for national security of infrastructure. The BESS relationship and new clean energy have features that warrant discussions and additional focus on impact for technology security, given their critical role. This review considers the impact and solutions for complex business and policy landscapes in clean energy supply chain, and the benefit trade-offs, focusing on the Battery Energy Storage System case study, and its complex organizational relationships across both the US, Allied countries and Foreign Entities of Concern. While many examples in this paper are presented on PRC focused manufacture, this could apply to any potentially adversarial relationship

25 - ENERGY STORAGE↗

DOE OSTI2021

A stochastic biomass blending problem in decentralized supply chains

Blending biomass materials of different physical or chemical properties provides an opportunity to adjust the quality of the feedstock to meet the specifications of the conversion platform. We propose a model which identifies the right mix of biomass to optimize the performance of the thermochemical conversion process at the mini-mum cost. This is a chance-constraint programming (CCP) model which takes into account the stochastic nature of biomass quality. The proposed CCP model ensures that process requirements, which are impacted by physical and chemical properties of biomass, are met most of the time. We consider two problem settings, a centralized and a decentralized supply chain. We propose a mixed-integer linear program to model the blending problem in the centralized setting and a bilevel program to model the blending problem in the decentralized setting. We use the sample average approximation method to approximate the chance constraints, and propose solution algorithms to solve this approximation. We develop a case study for South Carolina using data provided by the Billion Ton Study. Based on our results, the blends identified consist mainly of pine and softwood residues. The blends identified and the suppliers selected by both models are different. The cost of the centralized supply chain is 2%–6% lower. The implications of these results are twofold. First, these results could lead to improved collaborations in the supply chain. Second, these results provide an estimate of the approximation error from assuming centralized decision making in the supply chain.

09 BIOMASS FUELS↗

DOE OSTI2023

Spin dynamics of the generalized quantum spin compass chain

Here we calculate the dynamical spin structure factor of the generalized spin-1/2 compass spin chain using the density matrix renormalization group. The model, also known as the twisted Kitaev spin chain, was recently proposed to be relevant for the description of the spin chain compound CoNb 2 O 6 . It features bond-dependent interactions and interpolates between an Ising chain and a one-dimensional variant of Kitaev's honeycomb spin model. The structure factor, in turn, is found to interpolate from gapped and nondispersive in the Ising limit to gapless with nontrivial continua in the Kitaev limit. In particular, the component of the structure factor perpendicular to the Ising directions changes abruptly at the Kitaev point into a dispersionless continuum due to the emergence of an extensive ground-state degeneracy. We show this continuum is consistent with analytical Jordan-Wigner results. We also discuss implications for future inelastic scattering experiments and applications to materials, particularly CoNb 2 O 6 .

1-dimensional spin chains↗

DOE OSTI2023

Smartly Optimizing Crystallinity, Compatibility, and Morphology for Polymer Solar Cells by Small Molecule Acceptor with Unique 2D-EDOT Side Chain

A desired morphology is essential for achieving efficient polymer solar cells. Donors and acceptors with appropriate crystallization can lead to a suitable phase-separated morphology for effective photocurrent generation process. Inspired by the success of Y6 acceptors and the 2D side chain engineering on popular polymer donors and small molecule acceptors, the usage of unique 2D 3,4-ethylene dioxythiophene (EDOT) side chains on Y6 to regulate its crystallinity, compatibility, and thus the related blend morphology is explored. Here, in this study, two molecules of BTP-EDOT-4F and BTP-EDOT-4Cl with such unique 2D EDOT side chains are designed and synthesized. Due to the advantage of EDOT side chain, when these molecules are blended with PM6, the decent power conversion efficiencies (PCEs) of 16.78% and 15.87% are obtained. Furthermore, BTP-EDOT-4F is selected as the third component and added into PM6:L8-BO binary system to form ternary blends. The optimized crystallinity, compatibility, and morphology of such ternary blend are discovered in the presence of BTP-EDOT-4F, which enables efficient exciton dissociation and charge transport as well as decreased recombination, resulting in higher short circuit current density (J sc ) and fill factor. Finally, the outstanding PCE of 18.56% is achieved in ternary blends containing PM6, L8-BO, and BTP-EDOT-4F.

2D EDOT side chains↗