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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

SLAC microresonator RF(SMuRF) electronics: A tone-tracking readout system for superconducting microwave resonator arrays

Here, we describe the newest generation of the SLAC Microresonator RF (SMuRF) electronics, a warm digital control and readout system for microwave-frequency resonator-based cryogenic detector and multiplexer systems, such as microwave superconducting quantum interference device multiplexers (μmux) or microwave kinetic inductance detectors. Ultra-sensitive measurements in particle physics and astronomy increasingly rely on large arrays of cryogenic sensors, which in turn necessitate highly multiplexed readout and accompanying room-temperature electronics. Microwave-frequency resonators are a popular tool for cryogenic multiplexing, with the potential to multiplex thousands of detector channels on one readout line. The SMuRF system provides the capability for reading out up to 3328 channels across a 4–8 GHz bandwidth. Notably, the SMuRF system is unique in its implementation of a closed-loop tone-tracking algorithm that minimizes RF power transmitted to the cold amplifier, substantially relaxing system linearity requirements and effective noise from intermodulation products. Here, we present a description of the hardware, firmware, and software systems of the SMuRF electronics, comparing achieved performance with science-driven design requirements. In particular, we focus on the case of large-channel-count, low-bandwidth applications, but the system has been easily reconfigured for high-bandwidth applications. The system described here has been successfully deployed in lab settings and field sites around the world and is baselined for use on upcoming large-scale observatories.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Automated Generation of Integrated Digital and Spiking Neuromorphic Machine Learning Accelerators

The growing numbers of application areas for artificial intelligence (AI) methods have led to an explosion of domain-specific accelerators that could support every new machine learning (ML) algorithm advancement, clearly highlighting the need for a capability to quickly and automatically transition from algorithm definition to hardware implementation and explore design space along a variety of SWaP (size, weight and Power). The software defined architectures (SODA) synthesizer implements a compiler-based modular infrastructure for the end-to-end generation of machine learning accelerators from high-level frameworks to hardware description language. At the same time, neuromorphic computing, by mimicking how the brain operates, promises to perform artificial intelligence tasks at efficiencies orders of magnitude higher than the current conventional tensor-processing based accelerators, as demonstrated by a variety of specialized designs leveraging Spiking Neural Networks (SNNs). Nevertheless, the mapping of an artificial neural network (ANN) to solutions supporting SNNs is still a non-trivial and very device-specific task, and completely lack the possibility to design hybrid systems that integrate conventional and spiking neural models. In this paper we discuss the support for such an integrated generation leveraging the SODA Synthesizer framework and its modular structure. In particular, we present a new MLIR dialect (part of the SODA frontend) that allows expressing spiking neural network features (e.g., available resources, spiking sequences, analog signal reading, etc.) and illustrate how it enables mapping to Spiking Neurons and deployment to the related specialized hardware (which, in the digital domain, could be generated through the other existing layers of the SODA Synthesizer). We then discuss the opportunities for even deeper integration afforded by the hardware compilation infrastructure, providing a path towards the generation of complex heterogeneous artificial intelligence systems.

Curzel, Serena↗
DOE OSTI2023

Emergent symmetries in atomic nuclei: Probing nuclear dynamics and physics beyond the standard model

Dominant shapes naturally emerge in atomic nuclei from first principles, thereby establishing the shape-preserving symplectic Sp(3, \mathbb{R} ℝ ) symmetry as remarkably ubiquitous and almost perfect symmetry in nuclei. We discuss the critical role of this emergent symmetry in enabling machine-learning descriptions of heavy nuclei, ab initio modeling of \alpha α clustering and collectivity, as well as tests of beyond-the-standard-model physics. In addition, the Sp(3, \mathbb{R} ℝ ) and SU(3) symmetries provide relevant degrees of freedom that underpin the ab initio symmetry-adapted no-core shell model with the remarkable capability of reaching nuclei and reaction fragments beyond the lightest and close-to-spherical species.

Launey, Kristina D.↗
DOE OSTI2020

Research Roadmap on Grid-Forming Inverters

This research roadmap is intended to fill the knowledge gap by providing a system view of grid-forming inverter-based resource controls and their impact on grid stability, which we believe is central to meeting some of the challenges to operating the future North American electric power system. This includes the roles and requirements of grid-forming inverter-based resources—including solar photovoltaics, wind generators, and energy storage. For this roadmap, we focus on a specific family of grid-forming inverter control approaches that do not rely on an external voltage source (i.e., no phase-locked loop) and that can share load without explicit communications. Although the roadmap is focused narrowly on system challenges for grid-forming controls and power system stability, including interactions with protection, we hope it serves as a foundational element for future system-of-systems roadmapping needed in a broader grid modernization effort with increasing deployments of inverter-based resources. The roadmap first introduces formal definitions for the grid stability topics and then describes the differences between grid-forming and traditional grid-following control approaches for inverter-based resources. The core of the roadmap consists of a review of current research and an outline of research needs related to five grid-forming inverter topics: frequency control, voltage control, system protection, fault ride-through and voltage recovery, and modeling and simulation. The review both delineates contemporary advances and highlights open research questions that must be addressed to enable the widespread adoption of inverter-based resources across the grid. Feedback from industry on these research questions is incorporated, including discussions during the Workshop on Grid-forming Inverters for Low-inertia Power Systems. The workshop included industry presentations and discussion of ongoing research, technology gaps, and piloting needs. This roadmap concludes by offering a multiyear perspective on the gradual field validation of grid-forming inverters. This perspective recognizes that the scale and scope of the types of power systems that inverters will be called on to provide grid-forming services will and should begin modestly. Specifically, this roadmap recognizes that inverter controls today are predominantly grid-following and that future power systems will involve a mix of inverter-based resources with both grid-following and grid-forming control capabilities. Growth over time will depend on how well grid-forming inverters perform and what advantages they bring as penetration levels (instantaneous and average) of inverter-based resources increases. This recognition, in turn, establishes a natural sequence of priorities for the research questions that must be addressed. Following this multiyear perspective, the roadmap offers short descriptions of two specific near-term research priorities: the review of regulatory and technical standards and the development of advanced modeling techniques. These priorities are foundational. We recommend immediate pursuit of them in parallel with and in direct support of the research outlined by our multiyear perspective.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

C2QA - Bosonic Qiskit

The practical benefits of hybrid quantum information processing hardware that contains continuous-variable objects (bosonic modes such as mechanical or electromagnetic oscillators) in addition to traditional (discrete-variable) qubits have recently been demonstrated by experiments with bosonic codes that reach the break-even point for quantum error correction [1]–[5] and by efficient Gaussian boson sampling simulation of the Franck-Condon spectra of triatomic molecules [6] that is well beyond the capabilities of current qubit-only hardware. The goal of this Co-design Center for Quantum Advantage (C2QA) project is to develop an instruction set architecture (ISA) for hybrid qubit/bosonic mode systems that contains an inventory of the fundamental operations and measurements that are possible in such hardware. The corresponding abstract machine model (AMM) would also contain a description of the appropriate error models associated with the gates, measurements and time evolution of the hardware. This information has been implemented as an extension of IBM Qiskit. IBM Qiskit is an open-source software development toolkit (SDK) for simulating the quantum state of a quantum circuit and for running the same circuits on prototype hardware within the IBM Quantum Experience. We introduce the Bosonic Qiskit software to enable the simulation of hybrid qubit/bosonic systems using the existing Qiskit software development kit [7]. This implementation can be used for simulating new hybrid systems, verifying proposed physical systems, and modeling systems larger than can currently be constructed. We also cover tutorials and example use cases included within the software to study JaynesCummings models, bosonic Hubbard models, plotting Wigner functions and animations, and calculating maximum likelihood estimations using Wigner functions.

quantum, boson, Qiskit↗
DOE OSTI2021

Description and Demonstration of the Coupled Community Earth System Model v2 – Community Ice Sheet Model v2 (CESM2‐CISM2)

Abstract Earth system/ice‐sheet coupling is an area of recent, major Earth System Model (ESM) development. This work occurs at the intersection of glaciology and climate science and is motivated by a need for robust projections of sea‐level rise. The Community Ice Sheet Model version 2 (CISM2) is the newest component model of the Community Earth System Model version 2 (CESM2). This study describes the coupling and novel capabilities of the model, including: (1) an advanced energy‐balance‐based surface mass balance calculation in the land component with downscaling via elevation classes; (2) a closed freshwater budget from ice sheet to the ocean from surface runoff, basal melting, and ice discharge; (3) dynamic land surface types; and (4) dynamic atmospheric topography. The Earth system/ice‐sheet coupling is demonstrated in a simulation with an evolving Greenland Ice Sheet (GrIS) under an idealized high CO 2 scenario. The model simulates a large expansion of ablation areas (where surface ablation exceeds snow accumulation) and a large increase in surface runoff. This results in an elevated freshwater flux to the ocean, as well as thinning of the ice sheet and area retreat. These GrIS changes result in reduced Greenland surface albedo, changes in the sign and magnitude of sensible and latent heat fluxes, and modified surface roughness and overall ice sheet topography. Representation of these couplings between climate and ice sheets is key for the simulation of ice and climate interactions.

Muntjewerf, Laura↗
DOE OSTI2025

Methodologies and strategies for detecting fiber orientation in polymeric fiber-reinforced composites

In this review paper different methods and techniques for representing fiber orientation in advanced polymer matrix composites are presented. A description of the effect of fiber orientation on processing, fabrication and mechanical properties of a composite material is presented. The paper discusses the mathematical modeling and modeling techniques for fiber structure representation in polymeric composites, with an emphasis on fiber orientation in a composite part. The paper is divided into two sections; namely—destructive techniques and non-destructive techniques. The capabilities and limitations of each technique with respect to fiber orientation detection and measurements are discussed.

composites↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-NC3 NC_Clearcut#3

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-NC3 NC_Clearcut#3. This is the FLUXNET version of the carbon flux data for the site US-NC3 NC_Clearcut#3 produced by applying the standard ONEFlux (1F) software. Site Description - The North Carolina Clearcut site #3 was set up to complement NC2, and continue in place of NC1. The previous rotation of loblolly pine was harvested in the spring of 2012, the site was prepared and replanted with 2-yr old seedlings in the winter of 2012/2013. Measurements were terminated in 2021 due to trees outgrowing the tower and infrastructure capability.

Noormets, Asko↗
DOE OSTI2023

Modeling The DLOFC Accident Scenario of HTR-PM Equilibrium Core Using NEAMS Tools

High-Temperature Gas-cooled Reactors (HTGRs) have excellent characteristics in terms of safety and high thermal efficiency, and they are gaining a large interest from the industry as a candidate of Gen-IV reactors for a wide range of applications. The High Temperature gas-cooled Reactor Pebble-bed Module project (HTR-PM) is one of these designs and where helium gas is used to cool the pebble-bed region that consists of spherical fuel elements moderated with graphite. The HTR-PM design is based on the combined experience from the German pebble-bed reactor program from the 1960s through the 1990s and the HTR-10 experience in China during the 2000s. Idaho National Laboratory has a long experience in modeling of HTGRs working in developing neutronics and thermal hydraulics tools for the proper modeling of these reactors. The neutronics code Griffin has the capability to model pebble depletion . While the thermal hydraulics code Pronghorn was developed mainly to model the pebble bed reactors with the porous media assumption. In this work, an equilibrium core Multiphysics model was developed for the HTR-PM reactor to analyze the depressurized loss of forced cooling accident scenario (DLOFC). This paper is organized as follows: First, a brief description of the reactor and model specifications are provided. Then, the developed Multiphysics model is discussed. Finally, verification results of the steady-state equilibrium core and DLOFC accident are presented followed by a summary of the conclusions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Pyomo.GDP: an ecosystem for logic based modeling and optimization development

We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—and describe how new developments in Pyomo.GDP for Generalized Disjunctive Programming (GDP) advance this vision. We describe a new logical expression system implementation for Pyomo.GDP allowing for a more intuitive description of logical propositions. The logical expression system supports automated reformulation of these logical constraints to linear constraints. We also describe two new logic-based global optimization solver implementations built on Pyomo.GDP that exploit logical structure to avoid “zero-flow” numerical difficulties that arise in nonlinear network design problems when nodes or streams disappear. These new solvers also demonstrate the capability to link to external libraries for expanded functionality within an integrated implementation. We present these new solvers in the context of a flexible array of solution paths available to GDP models. Finally, we present results on a new library of GDP models demonstrating the value of multiple solution approaches.

42 ENGINEERING↗
DOE OSTI2025

ThinCurr: An open-source 3D thin-wall eddy current modeling code for the analysis of large-scale systems of conducting structures

In this paper we present a new thin-wall eddy current modeling code, ThinCurr, for studying inductively-coupled currents in 3D conducting structures -- with primary application focused on the interaction between currents flowing in coils, plasma, and conducting structures of magnetically-confined plasma devices. The code utilizes a boundary finite element method on an unstructured, triangular grid to accurately capture device structures. The new code, part of the broader Open FUSION Toolkit, is open-source and designed for ease of use without sacrificing capability and speed through a combination of Python, Fortran, and C/C++ components. Scalability to large models is enabled through use of hierarchical off-diagonal low-rank compression of the inductance matrix, which is otherwise dense. Ease of handling large models of complicated geometry is further supported by automatic determination of supplemental elements through a greedy homology approach. Here, a detailed description of the numerical methods of the code and verification of the implementation of those methods using cross-code comparisons against the VALEN code and Ansys commercial analysis software is shown.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

KETCHUP: Parameterizing of large-scale kinetic models using multiple datasets with different reference states

Large-scale kinetic models provide the computational means to dynamically link metabolic reaction fluxes to metabolite concentrations and enzyme levels while also conforming to substrate level regulation. However, the development of broadly applicable frameworks for efficiently and robustly parameterizing models remains a challenge. Challenges arise due to both the heterogeneity, paucity, and difficulty in obtaining flux and/or concentration data but also due to the computational difficulties of the underlying parameter identification problem. Both the computational demands for parameterization, degeneracy of obtained parameter solutions and interpretability of results has so far limited widespread adoption of large-scale kinetic models despite their potential. Herein, we introduce the Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the (non)steady-state fluxes and concentrations in wild-type and perturbed metabolic networks. KETCHUP is benchmarked against previously parameterized large-scale kinetic models demonstrating an at least an order of magnitude faster convergence than the tool K-FIT while at the same time attaining better data fits. Finally, this versatile toolbox accepts different kinetic descriptions, metabolic fluxes, enzyme levels and metabolite concentrations, under either steady-state or instationary conditions to enable robust kinetic model construction and parameterization. KETCHUP supports the SBML format and can be accessed at https://github.com/maranasgroup/KETCHUP.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Large-Scale, GPU-Enhanced DFTB Approaches for Probing Multi-Component Alloys

The major goals of the project are to develop and apply GPU-enhanced density functional theory tight binding (DFTB) calculations for efficient simulations of structural materials of alloy systems. The figure below depicts the GPU algorithmic developments on the left that will be carried out, and the solid-state structures on the right are representative of the complex alloys that can be computed with the GPU-enhanced DFTB approach. The methodology and tools developed in this project encompass accurate intermolecular potentials and GPU enhancements to the density functional tight binding (DFTB) approach for high-throughput ab initio molecular dynamics calculations of multi-component alloys at elevated temperatures. While classical molecular dynamics can handle hundreds of thousands of atoms, it cannot provide a first-principles based description of large, multi-component alloys at the predictive quantum level. At the other extreme, conventional Kohn-Sham DFT methods can probe the true quantum nature of chemical systems; however, these methods cannot tackle the large sizes relevant to these multi-component systems. The DFTB-based ab initio molecular dynamics approach (coupled with our in-house GPU capabilities for enhanced speed) used in this project provides a viable approach for probing these large systems at a quantum level of detail that is significantly faster than current first-principle methods Collectively, the capabilities developed in this project directly respond to DOE HBCU-OMI, AOI 2-1 initiatives by (1) enabling accurate and efficient predictions and (2) bringing a fundamental understanding of structural interactions in these complex systems at elevated temperatures.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Towards physics-informed explainable machine learning and causal models for materials research

From emergent material descriptions to estimation of properties stemming from structures to optimization of process parameters for achieving best performance – all key facets of materials science and related fields have experienced tremendous growth with the introduction of data-driven models. This gradual progression goes at par with developments of machine learning workflows, from purely data-driven shallow models to those that are well-capable in encoding more complex graphs, symbolic representations, invariances, and positional embeddings. Furthermore, this perspective aims at summarizing strategic aspects of such transitions while providing insights into the requirements of bringing in explainable, interpretable predictive models, and causal learning to aid in materials design and discovery. Although the focus remains on a variety of functional materials by providing a handful of case studies, the applications of such integrated methodologies are universal to facilitate fundamental understandings of materials physics while enabling autonomous experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding the Impact of Hydrogen Activation by SrCe 0.8 Zr 0.2 O 3-δ Perovskite Membrane Material on Direct Non-Oxidative Methane Conversion

Direct non-oxidative methane conversion (DNMC) converts methane (CH 4 ) in one step to olefin and aromatic hydrocarbons and hydrogen (H 2 ) co-product. Membrane reactors comprising methane activation catalysts and H 2 -permeable membranes can enhance methane conversion by in situ H 2 removal via Le Chatelier's principle. Rigorous description of H 2 kinetic effects on both membrane and catalyst materials in the membrane reactor, however, has been rarely studied. In this work, we report the impact of hydrogen activation by hydrogen-permeable SrCe 0.8 Zr 0.2 O 3-δ (SCZO) perovskite oxide material on DNMC over an iron/silica catalyst. The SCZO oxide has mixed ionic and electronic conductivity and is capable of H 2 activation into protons and electrons for H 2 permeation. In the fixed-bed reactor packed with a mixture of SCZO oxide and iron/silica catalyst, stable and high methane conversion and low coke selectivity in DNMC was achieved by co-feeding of H 2 in methane stream. The characterizations show that SCZO activates H 2 to favor “soft coke” formation on the catalyst. The SCZO could absorb H 2 in situ to lower its local concentration to mitigate the reverse reaction of DNMC in the tested conditions. The co-existence of H 2 co-feed, SCZO oxide, and DNMC catalyst in the present study mimics the conditions of DNMC in the H 2 -permeable SCZO membrane reactor. The findings in this work offer the mechanistic understanding of and guidance for the design of H 2 -permeable membrane reactors for DNMC and other alkane dehydrogenation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Importance of appropriate genome information for the design of mating type primers in black and yellow morel populations

Abstract Morels are highly prized edible fungi where sexual reproduction is essential for fruiting-body production. As a result, a comprehensive understanding of their sexual reproduction is of great interest. Central to this is the identification of the reproductive strategies used by morels. Sexual reproduction in fungi is controlled by mating-type ( MAT ) genes and morels are thought to be mainly heterothallic with two idiomorphs, MAT1-1 and MAT1-2. Genomic sequencing of black (Elata clade) and yellow (Esculenta clade) morel species has led to the development of PCR primers designed to amplify genes from the two idiomorphs for rapid genotyping of isolates from these two clades. To evaluate the design and theoretical performance of these primers we performed a thorough bioinformatic investigation, including the detection of the MAT region in publicly available Morchella genomes and in-silico PCR analyses. All examined genomes, including those used for primer design, appeared to be heterothallic. This indicates an inherent fault in the original primer design which utilized a single Morchella genome, as the use of two genomes with complementary mating types would be required to design accurate primers for both idiomorphs. Furthermore, potential off-targets were identified for some of the previously published primer sets, but verification was challenging due to lack of adequate genomic information and detailed methodologies for primer design. Examinations of the black morel specific primer pairs (MAT11L/R and MAT22L/R) indicated the MAT22 primers would correctly target and amplify the MAT1-2 idiomorph, but the MAT11 primers appear to be capable of amplifying incorrect off-targets within the genome. The yellow morel primer pairs (EMAT1-1 L/R and EMAT1-2 L/R) appear to have reporting errors, as the published primer sequences are dissimilar with reported amplicon sequences and the EMAT1-2 primers appear to amplify the RNA polymerase II subunit ( RPB2 ) gene. The lack of the reference genome used in primer design and descriptive methodology made it challenging to fully assess the apparent issues with the primers for this clade. In conclusion, additional work is still required for the generation of reliable primers to investigate mating types in morels and to assess their performance on different clades and across multiple geographical regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

MELCOR Code Change History (Revision 14959 to 18019)

This document summarily provides brief descriptions of the MELCOR code enhancement made between code revision number 14959and 18019. Revision 14959 represents the previous official code release; therefore, the modeling features described within this document are provided to assist users that update to the newest official MELCOR code release, 18019. Along with the newly updated MELCOR Users Guide and Reference Manual, users are aware and able to assess the new capabilities for their modeling and analysis applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗