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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Performance of the rigorous renormalization group for first-order phase transitions and topological phases

Expanding and improving the repertoire of numerical methods for studying quantum lattice models is an ongoing focus in many-body physics. While the density matrix renormalization group (DMRG) has been established as a practically useful algorithm for finding the ground state in one-dimensional systems, a provably efficient and accurate algorithm remained elusive until the introduction of the rigorous renormalization group (RRG) by Landau [Nat. Phys. 11, 566 (2015)1745-247310.1038/nphys3345]. In this paper, we study the accuracy and performance of a numerical implementation of RRG at first-order phase transitions and in symmetry-protected topological phases. Our study is motivated by the question of when RRG might provide a useful complement to the more established DMRG technique. In particular, despite its general utility, DMRG can give unreliable results near first-order phase transitions and in topological phases, since its local update procedure can fail to adequately explore (near-)degenerate manifolds. Furthermore, the rigorous theoretical underpinnings of RRG, meanwhile, suggest that it should not suffer from the same difficulties. We show this optimism is justified, and that RRG indeed determines well-ordered, accurate energies even when DMRG does not. Moreover, our performance analysis indicates that in certain circumstances seeding DMRG with states determined by coarse runs of RRG may provide an advantage over simply performing DMRG.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Developing Technology Performance Level Assessments for Early-Stage Wave Energy Converter Technologies

The advantage of using Technology Performance Level (TPL) in conjunction with Technology Readiness Level (TRL) assessments in guiding technology development trajectories to successful outcomes in less time, at less overall cost, and with less encountered risk has been well articulated in the literature. In partnership with industry and international collaborators, a TPL assessment methodology for grid-connected applications has been developed through the application of the systems engineering approach. Metrics under seven different categories have been developed, weighted based on their relative relevance, and combined to yield a composite score. The methodology has been implemented in a spreadsheet tool plus a web application specifically aimed at assessing early stage (TRL 1-3) concepts. The target use cases are (a) technology developers improving their design, to find fatal flaws early, to get feedback on current design, to identify areas of improvement that will yield the highest return on investment, (b) reviewers assessing technologies in competitions or for making funding decisions, (c) investor or project developer doing due diligence, (d) policy makers landscaping the technology domain for formulating R&D strategy. The methodology and the tools are undergoing continuous improvement based on the experience and lessons learnt from applying it to internal and external marine energy technology development projects. The methodology is also being adapted for assessing WECs servicing markets outside the continental grid - broadly categorized as Powering the Blue Economy (PBE) applications. Such applications have vastly different functional requirements entailing a modification of the methodology to account for their higher risk tolerance, reduced price sensitivities, lower power needs, different permitting protocols, etc. This paper presents the latest status of the TPL assessment methodology and tools, describes its adaptation to select PBE markets, and explores its extension to other domains where it could provide a comprehensive and holistic measure of a nascent or disruptive technology's technoeconomic performance potential.

metrics↗
DOE OSTI2021

Developing Technology Performance Level Assessments for Early-Stage Wave Energy Converter Technologies: Preprint

The advantage of using Technology Performance Level (TPL) in conjunction with Technology Readiness Level (TRL) assessments in guiding technology development trajectories to successful outcomes in less time, at less overall cost, and with less encountered risk has been well articulated in the literature. In partnership with industry and international collaborators, a TPL assessment methodology for grid-connected applications has been developed through the application of the systems engineering approach. Metrics under seven different categories have been developed, weighted based on their relative relevance, and combined to yield a composite score. The methodology has been implemented in a spreadsheet tool plus a web application specifically aimed at assessing early stage (TRL 1-3) concepts. The target use cases are (a) technology developers improving their design, to find fatal flaws early, to get feedback on current design, to identify areas of improvement that will yield the highest return on investment, (b) reviewers assessing technologies in competitions or for making funding decisions, (c) investor or project developer doing due diligence, (d) policy makers landscaping the technology domain for formulating R&D strategy. The methodology and the tools are undergoing continuous improvement based on the experience and lessons learnt from applying it to internal and external marine energy technology development projects. The methodology is also being adapted for assessing WECs servicing markets outside the continental grid - broadly categorized as Powering the Blue Economy (PBE) applications. Such applications have vastly different functional requirements entailing a modification of the methodology to account for their higher risk tolerance, reduced price sensitivities, lower power needs, different permitting protocols, etc. This paper presents the latest status of the TPL assessment methodology and tools, describes its adaptation to select PBE markets, and explores its extension to other domains where it could provide a comprehensive and holistic measure of a nascent or disruptive technology's technoeconomic performance potential.

metrics↗
DOE OSTI2020

OpenACC Profiling Support for Clang and LLVM using Clacc and TAU

Since its launch in 2010, OpenACC has evolved into one of the most widely used portable programming models for accelerators on HPC systems today. Clacc is a project funded by the US Exascale Computing Project (ECP) to bring OpenACC support for C and C++ to the popular Clang and LLVM compiler infrastructure. In this paper, we describe Clacc's support for the OpenACC Profiling Interface, a critical component of the OpenACC specification that standardizes an interface that profiling tools and libraries can depend upon across OpenACC implementations. As part of Clacc's general strategy to build OpenACC support upon OpenMP, we describe how Clacc builds OpenACC Profiling Interface support upon an extended version of OMPT. We then describe how a major profiling and tracing toolkit within ECP, the TAU Performance System, takes advantage of this support. We also describe TAU's selective instrumentation support for OpenACC. Finally, using Clacc and TAU, we present example visualizations for several SPEC ACCEL OpenACC benchmarks running on an IBM AC922 node, and we show that the associated performance overhead is negligible.

Coti, Camille↗
DOE OSTI2024

Challenges in Tracking Waste Reduction Performance Improvement in Manufacturing Plants

The recently released Circularity Gap Report 2023 by Circle Economy Foundation found that the circularity score for the global economy is declining. This indicates that material extraction from virgin sources is climbing over earlier years. As per data released by US Geological Survey, material use in the US economy has increased exponentially with the expanding US economy over last century. EPA tracked municipal solid waste from 1960 to 2018 and found that 50% of the waste is destined for landfills. EPA estimates that US industry is responsible for 2.7 billion ton of solid non-hazardous waste annually in our mostly linear economy model. The circular economy framework aims at decoupling economic value generation from virgin materials extraction from nature. The linear model of material extraction and disposal at end of life is highly unsustainable. Manufacturing companies have realized this and in their commitments to sustainability are adopting ambitious waste reduction targets. Through Better Plants program US Department of Energy has established Waste Reduction Network where it is offering technical assistance to partners to achieve these ambitious waste reduction goals. Basic requirements of establishing a target include identifying a baseline, quantifying waste performance, and measuring progress over time. One problem faced by industry is the unstandardized metrics to quantify waste performance that may not be well suited to demonstrate progress. In this paper, we research methods traditionally used to measure waste performance and highlight advantages, gaps and limitations of each method. Suitability of the methods applicable to different manufacturing circumstances are also examined. Finally, we present a case study of a large manufacturer that faced inconsistencies in their tracked measurement metric. A solution was proposed to alter the methodology to enable more accurate waste performance tracking against a baseline.

Chaudhari, Subodh↗
DOE OSTI2025

Challenges in Tracking Waste Reduction Performance Improvement in Manufacturing Plants

The recently released Circularity Gap Report 2023 by the Circle Economy Foundation states that the circularity score for the global economy is declining. The US Environmental Protection Agency (EPA) tracked municipal solid waste from 1960 to 2018 and found that 50% of the waste was destined for landfills. EPA estimates that US industry is responsible for 2.7 Gt of solid nonhazardous waste annually in the US mostly linear economy model. The circular economy framework aims to decouple economic value generation from the extraction of virgin materials from nature. The linear model of material extraction and disposal at the end of life is highly unsustainable. Manufacturing companies are adopting ambitious waste reduction targets to achieve sustainability. Through the Better Plants program, US DOE has established the Waste Reduction Network, which offers technical assistance to partners to achieve their ambitious waste reduction goals. Basic requirements of establishing a target include identifying a baseline, quantifying waste performance, and measuring progress over time. One problem faced by industry is unstandardized metrics for quantifying waste performance that may not be well suited to demonstrate progress. This paper studies traditional methods used to measure waste performance and highlights advantages, disadvantages, and limitations of each method. It also examines the suitability of applying the methods in different manufacturing circumstances. Finally, the paper presents a case study of a large manufacturer that faced inconsistencies in its tracked measurement metric. A solution was proposed and implemented to alter the methodology to enable more accurate waste performance tracking against a baseline.

circular economy↗
DOE OSTI2023

Mixed-Precision S/DGEMM Using the TF32 and TF64 Frameworks on Low-Precision AI Tensor Cores

Using NVIDIA graphics processing units (GPUs) equipped with Tensor Cores has enabled the significant acceleration of general matrix multiplication (GEMM) for applications in machine learning (ML) and artificial intelligence (AI) and in high-performance computing (HPC) generally. The use of such power-efficient, specialized accelerators can provide a performance increase between 8 × and 20 ×, albeit with a loss in precision. However, a high level of precision is required in many large scientific and HPC applications, and computing in single or double precision is still necessary for many of these applications to maintain accuracy. Fortunately, mixed-precision methods can be employed to maintain a higher level of numerical precision while also taking advantage of the performance increases from computing with lower-precision AI cores. With this in mind, we extend the state of the art by using NVIDIA’s new TF32 framework. This new framework not only burdens some constraints of the previous frameworks, such as costly 32 16-bit castings but also provides an equivalent precision and performance by using a much simpler approach. We also propose a new framework called TF64 that attempts double-precision arithmetic with low-precision Tensor Cores. Although this framework does not exist yet, we validated the correctness of this idea and achieved an equivalent of 64-bit precision on 32-bit hardware.

Valero Lara, Pedro↗
DOE OSTI2023

Physics‐Informed Machine Learning for Inverse Design of Optical Metamaterials

Optical metamaterials manipulate light through various confinement and scattering processes, offering unique advantages like high performance, small form factor and easy integration with semiconductor devices. However, designing metasurfaces with suitable optical responses for complex metamaterial systems remains challenging due to the exponentially growing computation cost and the ill‐posed nature of inverse problems. To expedite the computation for the inverse design of metasurfaces, a physics‐informed deep learning (DL) framework is used. A tandem DL architecture with physics‐based learning is used to select designs that are scientifically consistent, have low error in design prediction, and accurate reconstruction of optical responses. The authors focus on the inverse design of a representative plasmonic device and consider the prediction of design for the optical response of a single wavelength incident or a spectrum of wavelength in the visible light range. The physics‐based constraint is derived from solving the electromagnetic wave equations for a simplified homogenized model. The model converges with an accuracy up to 97% for inverse design prediction with the optical response for the visible light spectrum as input, and up to 96% for optical response of single wavelength of light as input, with optical response reconstruction accuracy of 99%.

Sarkar, Sulagna↗
DOE OSTI2024

Insight of Synthesis of Single Crystal Ni-Rich LiNi 1-x-y Co x Mn y O 2 Cathodes

Single-crystal Ni-rich LiNi 1-x-y Co x Mn y O 2 (NCM) cathodes have garnered widespread attention in the lithium-ion battery community due to their unique advantages in mechanical performance and their ability to minimize interfacial electrochemical side reactions. The synthesis of single-crystal materials with monodisperse and appropriate size, minimal lattice defects, and highly ordered structures is the key for high-performance batteries. However, achieving this goal poses challenges due to the lack of in-depth understanding regarding specific experimental parameters and the solid reaction mechanism during the synthesis process. Further, in this review, the aim is to provide an in-depth analysis of the critical process parameters involved in the synthesis and their impact on crystal morphology, structure, and electrochemical performance. Consequently, the first section focuses on the effect of the precursor morphology, lithium salt, atmosphere, and sintering procedure. In the second section, the study delves into an in-depth discussion of the solid reaction and crystal growth mechanism. Lastly, it is concluded by highlighting the prospects and challenges associated with the synthesis and application of single-crystal Ni-rich NCM cathodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Single-step conversion of ethanol into n-butene-rich olefins over metal catalysts supported on ZrO 2 -SiO 2 mixed oxides

With airlines committed to drastically reduce their carbon footprint by 2050, producing jet fuel from renewable ethanol is of particular interest. Here we reported on an Ag/ZrO 2 /SBA-16 catalyst that is very effective for directly converting ethanol into to n-butene-rich olefins jet fuel precursors (i.e., 88% at full conversion). Here, we report on a Cu/ZrO 2 /SBA-16 catalyst that presents remarkable olefins selectivity (i.e., 89% at 96% conversion) and enhanced stability as compared to Ag/ZrO2/SBA-16 catalyst. Under severe operating conditions a conversion loss < 10% was observed with the Cu/ZrO 2 /SBA-16 catalyst as compared to a 50% loss of conversion with the Ag/ZrO 2 /SBA-16 catalyst. Combined experimental and computational tools revealed that replacing Ag with Cu shifts the reaction pathway of crotonaldehyde hydrogenation from 1,3-butadiene (i.e., coke precursor) production to butyraldehyde formation. Experiments conducted with 4%Cu/4%ZrO 2 supported on SBA-16, dealuminated zeolite Beta, and aluminum silicate revealed the performance and stability advantage of the SBA-16-supported catalyst.

09 BIOMASS FUELS↗
DOE OSTI2023

CSPlib: A performance portable parallel software toolkit for analyzing complex kinetic mechanisms

Computational singular perturbation (CSP) is a method to analyze dynamical systems. It targets the decoupling of fast and slow dynamics using an alternate linear expansion of the right-hand side of the governing equations based on eigenanalysis of the associated Jacobian matrix. This representation facilitates diagnostic analysis, detection and control of stiffness, and the development of simplified models. For this work, we have implemented CSP in a C++ open-source library CSPlib using the Kokkos parallel programming model to address portability across diverse heterogeneous computing platforms, i.e., multi/many-core CPUs and GPUs. We describe the CSPlib implementation and present its computational performance across different computing platforms using several test problems. Specifically, we test the CSPlib performance for a constant pressure ignition reactor model on different architectures, including IBM Power 9, Intel Xeon Skylake, and NVIDIA V100 GPU. The size of the chemical kinetic mechanism is varied in these tests. As expected, the Jacobian matrix evaluation, the eigensolution of the Jacobian matrix, and matrix inversion are the most expensive computational tasks. When considering the higher throughput characteristic of GPUs, GPUs performs better for small matrices with higher occupancy rate. CPUs gain more advantages from the higher performance of well-tuned and optimized linear algebra libraries such as OpenBLAS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Additive manufacturing of LiCoO 2 electrodes via vat photopolymerization for lithium ion batteries

Additive manufacturing has the potential to revolutionize the fabrication of lithium-ion batteries for a diversity of applications including in portable, biomedical, aerospace, and the transportation fields. Standard commercial batteries consist of stacked layers of various components (current collectors, cathode, anode, separator and electrolyte) in a two-dimensional manner. By leveraging the latest advances in additive manufacturing and computer-aided design, an improved geometric and electrochemical configuration of these batteries can maximize energy efficiency while allowing design optimization to reduce dead space for a given application. In this work, a composite UV photosensitive resin was prepared and used as feedstock in a vat photopolymerization system. The resin was loaded with LiCoO 2 acting as electrochemically active material for the cathode of a lithium-ion battery, and was further improved with the addition of conductivity-enhancing carbonaceous additives. Challenges to additive manufacturing arise from the opacity and high viscosity of the composite nature of these electrochemically-active resins, which cause light refraction during selective UV curing. Subsequently, items were printed and subjected to a thermal post-processing step to obtain an adequate compromise between electrochemical performance and mechanical integrity. Both sintered and green state 3D printed cathodes were assembled into half-cell lithium-ion batteries using lithium metal as a reference and counter electrode. Electrochemical cycling of these batteries yielded satisfactory results approaching commercial LiCoO 2 cathodes’ performance, with the potential advantages of additive manufacturing – high surface area anode–cathode configurations for power performance as well as shape conformability.

25 ENERGY STORAGE↗
DOE OSTI2020

Design of target irradiation and diagnostic chamber to study ps-laser generated plasma as a source of singly charged ions for external injection into an electron beam ion source

High repetition-rate (~10 kHz) ps-lasers are becoming available on the market with reasonable cost and may offer several advantages compared to ns-lasers by generating nearly continuous beams of singly charged ions appropriate for the “slow” injection mode into the Electron Beam Ion Source (EBIS). To evaluate these advantages, we will perform studies of a ps-laser generated plasma using a laser with a pulse duration of 8 ps and energy up to 5 mJ per pulse. A vacuum chamber equipped with a 3D target positioner, a focusing lens, and a Faraday Cup has been designed and built for this study. Lens-to-target distance variations have been measured using a laser tracker over the whole range of horizontal and vertical translation for all five targets we will use. The variations were found to be within ±150 µm. This level of “target flatness” should be acceptable for our experimental conditions. Ion currents and ion pulse durations of various elements (from Al to Ta) will be measured for different target irradiation conditions (focal spot size and laser pulse energy). The results obtained will allow us to specify all parameters and geometry of a laser ion source based on a ps-laser to provide external ion injection into the relativistic heavy ion collider EBIS

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

A Weakly-Supervised, Multitask Deep Learning Framework for Shadow Mitigation in Remote Sensing Imagery

We propose a weakly-supervised, multitask framework for training a convolutional neural network to solve the problem of cloud shadow mitigation given only cloud and shadow masks as labels. The network minimizes the Wasserstein distance between shadows and their proximal sunlit neighborhoods, generating a supervisory signal directly from within the input image. We extract further utility from the shadow mask through multitask learning by introducing an auxiliary task of shadow segmentation. Our approach is advantageous since it performs mitigation in an end-to-end framework which requires only a shadowed image for inference. We apply this process to the Landsat 8 OLI SPARCS validation data set and demonstrate plausible results.

Couwenhoven, Scott↗
DOE OSTI2023

Upscaling of asymmetric hollow fiber‐supported thin film membranes for oxygen separation from air: Proof of concept

Abstract Hollow fiber membranes demonstrate various advantages for high performance oxygen separation. However, the small diameters of hollow fibers and the brittleness of ceramics limit their mechanical strength, imposing great difficulties on stack and module development. Gas‐tight sealing is another challenge for upscaling of hollow fiber membrane technology. Low temperature sealant materials of epoxy resin or silicon are typically used for hollow fiber stacks, requiring that the sealing portions be located out of hot zone. Consequently, only partial length of hollow fibers participates in oxygen permeation. In this study, upscaling of our recently developed asymmetric hollow fiber‐supported thin film membranes is conducted, where individual hollow fibers are assembled in parallel to form a stack. A reliable gas‐tight sealing is obtained by combining ceramic paste with conductive adhesive ink cohesively. Comprehensive oxygen permeation test is conducted with the sealing portions being in hot zone and compared with a single hollow fiber membrane. Fundamental mechanism is discussed to understand the performances and their differences. An accelerated long‐term test (∼320 h, 16 thermal cycles) demonstrates excellent stability and robustness of the stack and sealing. The characterization of post‐test samples further confirms excellent stability and robustness of the phases and microstructures of the stack.

36 MATERIALS SCIENCE↗
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 OSTI2023

Coal-based Bricks & Blocks (CBBs): Process Development to Prototype Fabrication Coupled with Techno-Economic Analysis and Market Survey

Coal-based bricks and blocks (CBBs) were formulated using anthracite and thermoplastic binder. Lab scale test composites were formed by hot-press molding and commercial extrusion for test articles and for a full-scale prototype. Formulations and test matrices followed a systematic experimental design to examine the effects of and interactions among three primary independent variables: a) thermoplastic type, b) weight fractions of binder relative to the total anthracite weight, and c) relative proportions of large versus small (milled) anthracite size fractions. Technical performance metrics include compressive strength, modulus, porosity/permeability and density. These DoE studies establish composition-property relations and identify the best combination for any desired property of interest – in particular, strength. Based on CBB composition and fabrication process, validated against technical performance metrics, a techno-economic analysis was constructed which incorporated a process flow model, engineering design (with scaling), and calculated capital plus operating costs. Based on measured property metrics and estimated process economics and a projected price by TEA (techno-economic analysis), building and construction target markets were identified by a market survey assessment. With known cost, price, performance metrics and competitive advantages for CBBs matched with commercial applications/uses, a technical gap analysis was performed to identify further development required for scale-up and commercialization.

01 COAL, LIGNITE, AND PEAT↗