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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Striped Data Analysis Framework

A columnar data representation is known to be an efficient way for data storage, specifically in cases when the analysis is often done based only on a small fragment of the available data structures. A data representation like Apache Parquet is a step forward from a columnar representation, which splits data horizontally to allow for easy parallelization of data analysis. Based on the general idea of columnar data storage, working on the [LDRD Project], we have developed a striped data representation, which, we believe, is better suited to the needs of High Energy Physics data analysis. A traditional columnar approach allows for efficient data analysis of complex structures. While keeping all the benefits of columnar data representations, the striped mechanism goes further by enabling easy parallelization of computations without requiring special hardware. We will present an implementation and some performance characteristics of such a data representation mechanism using a distributed no-SQL database or a local file system, unified under the same API and data representation model. The representation is efficient and at the same time simple so that it allows for a common data model and APIs for wide range of underlying storage mechanisms such as distributed no-SQL databases and local file systems. Striped storage adopts Numpy arrays as its basic data representation format, which makes it easy and efficient to use in Python applications. The Striped Data Server is a web service, which allows to hide the server implementation details from the end user, easily exposes data to WAN users, and allows to utilize well known and developed data caching solutions to further increase data access efficiency. We are considering the Striped Data Server as the core of an enterprise scale data analysis platform for High Energy Physics and similar areas of data processing. We have been testing this architecture with a 2TB dataset from a CMS dark matter search and plan to expand it to multiple 100 TB or even PB scale. We will present the striped format, Striped Data Server architecture and performance test results.

Gutsche, Oliver↗
DOE OSTI2021

Optical Spectroscopic Investigation of Hexavalent Actinide Ions in n-Dodecane Solutions of Tri-butyl Phosphate

The extraction of hexavalent actinides An(VI) by tri-butyl phosphate (TBP) was investigated by electronic absorption and vibrational spectroscopies. Through a series of spectral subtractions, vibrational spectra associated with TBP, TBP–HNO3 adducts, and An(VI)–TBP complexes could be isolated. Investigation of U(VI) extracts indicated spectral features consistent with the formation of the expected [UO2(NO3)2(TBP)2] complex, but spectral features of other species were clearly evident. Likewise, multiple species were evident in the electronic absorption and vibrational spectra of TBP phases generated by extraction of Pu(VI). Although definitive characterization of the additional species formed could not be achieved in this work, it is hypothesized that they contain 3:1 TBP-to-An(VI) stoichiometry.

Lumetta, Gregg J.↗
DOE OSTI2022

Enhanced Synchronization Stability of Grid-Forming Inverters With Passivity-Based Virtual Oscillator Control

In this article, a passivity-based virtual oscillator control strategy with enhanced synchronization stability for grid-forming inverters (GFMs) is proposed. By adopting the port-controlled Hamiltonian system theory for orbital stabilization problems, an energy pumping-and-damping block is proposed to render GFMs globally asymptotically stable with respect to the prespecified solutions of the power-flow equations from any initial condition. This allows for stable integrations of GFMs to any other globally asymptotically stable systems without their explicit knowledge, e.g., helping maintain synchronism with the bulk power system in a wide range of short-circuit-ratio conditions or under large disturbances and keeping synchronism among multiple GFMs in power systems. Herein, both simulations and experiments are presented to demonstrate the proposed control approach.

42 ENGINEERING↗
DOE OSTI2022

KokkACC: Enhancing Kokkos with OpenACC

Template metaprogramming is gaining popularity as a high-level solution for achieving performance portability on heterogeneous computing resources. Kokkos is a representative approach that offers programmers high-level abstractions for generic programming while most of the device-specific code generation and optimizations are delegated to the compiler through template specializations. For this, Kokkos provides a set of device-specific code specializations in multiple back ends, such as CUDA and HIP. Unlike CUDA or HIP, OpenACC is a high-level and directive-based programming model. This descriptive model allows developers to insert hints (pragmas) into their code that help the compiler to parallelize the code. The compiler is responsible for the transformation of the code, which is completely transparent to the programmer. This paper presents an OpenACC back end for Kokkos: KokkACC. As an alternative to Kokkos’s existing device-specific back ends, KokkACC is a multi-architecture back end providing a high-productivity programming environment enabled by OpenACC’s high-level and descriptive programming model. Moreover, we have observed competitive performance; in some cases, KokkACC is faster (up to 9×) than NVIDIA’s CUDA back end and much faster than OpenMP’s GPU offloading back end. This work also includes implementation details and a detailed performance study conducted with a set of mini-benchmarks (AXPY and DOT product) and three mini-apps (LULESH, miniFE and SNAP, a LAMMPS proxy mini-app).

Valero Lara, Pedro↗
DOE OSTI2022

Analyses of internal structures and defects in materials using physics-informed neural networks

Characterizing internal structures and defects in materials is a challenging task, often requiring solutions to inverse problems with unknown topology, geometry, material properties, and nonlinear deformation. Here, we present a general framework based on physics-informed neural networks for identifying unknown geometric and material parameters. By using a mesh-free method, we parameterize the geometry of the material using a differentiable and trainable method that can identify multiple structural features. We validate this approach for materials with internal voids/inclusions using constitutive models that encompass the spectrum of linear elasticity, hyperelasticity, and plasticity. We predict the size, shape, and location of the internal void/inclusion as well as the elastic modulus of the inclusion. Our general framework can be applied to other inverse problems in different applications that involve unknown material properties and highly deformable geometries, targeting material characterization, quality assurance, and structural design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Low-velocity repeated impact behaviors of Polymer Fiber Reinforced Plastics (PFRPs)

Modern fiber-reinforced composites have become ubiquitous across multiple industries due to their excellent weight-to-strength ratio. Typically glass or carbon fibers are widely used. While Glass or Carbon Fiber-Reinforced Plastics (GFPRs or CFPRs) have good stiffness, strength, and fatigue life, they are expensive and difficult to recycle. Researchers are exploring Polymer Fiber-Reinforced Plastics (PFRPs) as an alternative solution. PFRPs utilize polymer fibers and a polymer matrix. A wide range of materials options is available, including low-cost thermoplastics such as polyethylene or polypropylene. These thermoplastics are easy to handle and recyclable without special methods. Manufacturing parts using thermoplastics are well-established as well. However, their mechanical performances have not been extensively studied compared to GFRPs or CFRPs. This study examines the low-velocity impact resistance of PFRPs made of different thermoplastics. The low-velocity impacts are applied through a drop-weight tower. The experiment is divided into two cases: a single perforation impact and low-energy repeated impacts. Energy absorption and the number of impacts to failure are measured. The results are compared to traditional CFRPs which have a thermoset matrix. The PFRPs demonstrate energy absorption capabilities comparable to or greater than those of CFRPs with respect to specimen thickness and density. Additionally, the PFRPs show significantly higher impacts-to-failure than the CFRPs in low-energy repeated impact tests. This is particularly noteworthy considering that the PFRPs are much simpler and more economical to manufacture than CFRPs. To further

Ko, Seunghyun↗
DOE OSTI2020

Today's Energy Challenges, Tomorrow's Solutions: Integrated Energy Pathways: Modernizing Our Energy Systems

Integrated Energy Pathways Today's electric grid was built for century-old needs, not the needs of tomorrow's emerging system. As the cost of generating electricity falls, products and systems that previously operated on other types of fuels are becoming increasingly "electrified." Instead of a one-way flow of electricity to systems that operate independently from one another, we are seeing more bi-directional connectivity between the grid and multiple end points. Integrated Energy Systems require a fundamental rethinking of grid infrastructure and the path electricity takes from the source of generation to the end point of use. Inevitably, the way the grid is managed today won't be the way it is managed 10-15 years from now. NREL is pioneering the fundamental research needed to guide this transition through renewable energy fuels and low-carbon electricity generation. Working with industry partners, we can collaboratively develop a fresh approach to energy generation, security, resilience, and advanced mobility.

energy security↗
DOE OSTI2025

Differentiable lagrangian shock hydrodynamics with application to stable shock acceleration of density interfaces

We develop a gradient based optimization approach for the equations of compressible, Lagrangian hydrodynamics and demonstrate how it can be employed to automatically uncover strategies to control hydrodynamic instabilities arising from shock acceleration of density interfaces. Strategies for controlling the Richtmyer-Meshkov instability (RMI) are of great benefit for inertial confinement fusion (ICF) where shock interactions with many small imperfections in the density interface lead to instabilities which rapidly grow over time. These instabilities lead to mixing which, in the case of laser driven ICF, quenches the runaway fusion process ruining the potential for positive energy return. Here, we demonstrate that control of these instabilities can be achieved by optimization of initial conditions with ( > 100) parameters. Optimizing over a large parameter space like this is not possible with gradient-free optimization strategies. This requires computation of the gradient of the outputs of a numerical solution to the equations of Lagrangian hydrodynamics with respect to the inputs. We show that the efficient computation of these gradients is made possible via a judicious application of (i) adjoint methods, the exact formal representation of sensitivities involving partial differential equations, and (ii) automatic differentiation (AD), the algorithmic calculation of derivatives of functions. Careful regularization of multiple operators including artificial viscosity and timestep control is required. We perform design optimization of > 100 parameter energy field driving the Richtmyer Meshkov instability showing significant suppression while simultaneously enhancing the acceleration of the interface relative to a nominal baseline case.

Hydrophysics↗
DOE OSTI2023

A projection-based analytical Jacobian framework for chemical kinetics applications

A major challenge in simulating complex combustion systems with detailed chemical kinetic models is the cost of integrating the chemical source terms, often done using stiff ODE solvers that require frequent Jacobian evaluations. Using analytically derived Jacobian matrices instead of divided-difference-based numerical Jacobian approximations can significantly reduce the associated computational cost. However, ambiguities arise in the formulation of analytical Jacobians because the chemical state of the system, or state vector, can be expressed in multiple ways, involving variables that are typically not independent from one another. Here, in this work, the consequences of those ambiguities on practical calculations are characterized in detail, and a generalized, projection-based framework is proposed as a mitigation strategy. Performances are assessed in a series of test cases involving a variety of configurations and numerical solution approaches. Results show that with proper treatment, commonly used analytical Jacobian formulations can be considered as equivalent for practical purposes, thereby alleviating concerns that the state vector chosen to express the governing equations and corresponding analytical Jacobian may significantly impact the accuracy of the simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Multi-objective Decisions on Integrated Energy Systems Planning and Operation for Industrial Combined Heat and Power Supply

Unlike the power sector—which can transmit electricity over long distances via established grids—the industrial sector poses a unique challenge due to its geographically concentrated large-scale heat processes. Enhancing energy security in such industrial parks provides a dual benefit: reduced exposure to volatile fossil fuel prices and improved economic viability, largely driven by economies of scale in energy supply and distribution. This study presents a comprehensive technoeconomic analysis of a nuclear energy hub, employing a mechanism-focused approach to evaluate uncertainties in operational strategies and capacity optimization. Load profiles from three major energy intesive industries—chemical, refinery, and steelmaking—are examined, each presenting unique challenges and opportunities for nuclear energy integration. We adopt a multi-objective optimization framework, converting multiple objectives into a single objective function through the e-constraint method. The findings highlight clear trade-offs between system conditions and varying levels of energy independence. Overall, this analysis is granular enough to address industry-specific concerns yet sufficiently generalizable to provide actionable insights into the feasibility of nuclear-based clean heat solutions for the industrial sector.

25 - ENERGY STORAGE↗
DOE OSTI2022

ACORN Review: NPK fertilizer use in loblolly pine plantations: Who are we really feeding?

Optimizing loblolly pine (Pinus taeda L.) productivity using fertilizers and various site management practices has been a goal of foresters for decades. Nitrogen (N), phosphorus (P), and potassium (K) are the three most operationally applied fertilizers to loblolly pine silviculture and are of primary importance to their total productivity. Fertilizer recommendations for N, P, and K in loblolly pine are primarily made on abiotic factors such as site and soil characteristics, while the biological factors controlling nutrient uptake are typically overlooked in the production and optimization of these stands. Arguably the most important of these biological factors are the diverse ectomycorrhizal fungal (ECM) communities that colonize the fine roots of almost all loblolly pine trees. The mantle formed by ECM fungi on short-root tips presents a barrier for direct apoplastic uptake of N, P, and K from soil solution by pine roots. In well-colonized roots, the tree is dependent on symplastic fungal transport of N, P, and K foraged from the soil by the extraradical hyphal network. This raises the question: Who are we really feeding if the ECM fungi are the ones assimilating most of the tree's total nutritional requirements? Considering multiple species of ECM fungi can inhabit a single root system, many questions remain regarding the drivers of colonization, why some species are more efficient at taking up and exchanging nutrients with their hosts than others, and why certain fertilizers directly affect the morphology of ECM growth. The purposes of this review here are (1) to explore how the most commonly commercially applied macronutrients, N, P, and K, affect the relationship between loblolly pine and ECM communities, and (2) to propose future directions to investigate, preserve, and manipulate these interactions in pine plantations to optimize productivity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Improving the Quasi‐Biennial Oscillation via a Surrogate‐Accelerated Multi‐Objective Optimization

Accurate simulation of the quasi-biennial oscillation (QBO) is challenging due to uncertainties in representing convectively generated gravity waves. We develop an end-to-end uncertainty quantification workflow that calibrates these gravity wave processes in E3SM for a realistic QBO. Central to our approach is a domain knowledge-informed, compressed representation of high-dimensional spatio-temporal wind fields. By employing a parsimonious statistical model that learns the fundamental frequency from complex observations, we extract interpretable and physically meaningful quantities capturing key attributes. Building on this, we train a probabilistic surrogate model that approximates the fundamental characteristics of the QBO as functions of critical physics parameters governing gravity wave generation. Leveraging the Karhunen–Loève decomposition, our surrogate efficiently represents these characteristics as a set of orthogonal features, capturing cross-correlations among multiple physics quantities evaluated at different pressure levels and enabling rapid surrogate-based inference at a fraction of the computational cost of full-scale simulations. Finally, we analyze the inverse problem using a multi-objective approach. Our study reveals a tension between amplitude and period that constrains the QBO representation, precluding a single optimal solution. To navigate this, we quantify the bi-criteria trade-off and generate a set of Pareto optimal parameter values that balance the conflicting objectives. This integrated workflow improves the fidelity of QBO simulations and offers a versatile template for uncertainty quantification in complex geophysical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Novel Voltage Balancing Control With dv/dt Reduction for 10-kV SiC MOSFET-Based Medium Voltage Modular Multilevel Converter

Using high voltage (HV) silicon carbide (SiC) power semiconductors in a modular multilevel converter (MMC) is promising because it results in fewer submodules and lower switching loss compared to conventional Si based solutions. The nearest level pulsewidth modulation (NL-PWM) is commonly used in the MMC for medium voltage applications. However, with the NL-PWM and existing voltage balancing control, there are many submodules that switch their modes in a control cycle, resulting in a high dv/dt during the deadtime of the power semiconductor, which could be multiple times of the dv/dt of the single device. This poses great challenges on the noise immunity and insulation design in the MMC using HV SiC devices, which have very fast switching speed. A novel voltage balancing control, which ensures only two submodules switch their modes in a control cycle, is proposed in this article, limiting the maximum dv/dt to the dv/dt of a single power semiconductor and also maintaining the voltage balance performance. Furthermore, the proposed voltage balancing control is experimentally validated in a 10-kV SiC mosfet based MMC with four submodules per arm.

42 ENGINEERING↗
DOE OSTI2021

CB10412: Bulk CWA Destruction

The objective of this project was to eliminate and/or render bulk agent unusable by a threat entity via neutralization and/or polymerization of the bulk agent using minimal quantities of additives. We proposed the in situ neutralization and polymerization of bulk chemical agents (CAs) by performing reactions in the existing CA storage container via wet chemical approaches using minimal quantities of chemical based materials. This approach does not require sophisticated equipment, fuel to power generators, electricity to power equipment, or large quantities of decontaminating materials. By utilizing the CA storage container as the batch reactor, the amount of logistical resources can be significantly reduced. Fewer personnel are required since no sophisticated equipment needs to be set up, configured, or operated. Employing the CA storage container as the batch reactor enables the capability to add materials to multiple containers in a short period of time as opposed to processing one container at a time for typical batch reactor approaches. In scenarios where a quick response is required, the material can be added to all the CA containers and left to react on its own without intervention. Any attempt to filter the CA plus material solution will increase the rate of reaction due to increased agitation of the solution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Medial axis and local thickness computation using the Fast Sweeping Method

This report describes an efficient and robust voxel-based methodology for computing the medial axis, local thickness, and distance-to-skeleton of arbitrary three-dimensional geometries. It is assumed that the object can be represented by an exact or approximate signed distance function on a discrete grid. The gradient of such function is used to formulate a hyperbolic partial differential equation (PDE) that models the collapse of the position vector in space. By exploiting the causality property of the PDE, the Fast Sweeping Method is able to obtain the solution in a finite number of sweeps independent of the mesh resolution. The intersection of characteristic lines leads to the formation of shocks and a discrete bisector function is used to identify the medial axis. The same PDE approach is used to compute the local thickness inside the object and obtain the distance-to-skeleton field. Multiple examples are given in two and three dimensions along with a resolution study. The methodology has optimal complexity and yields subsecond computational times for geometries with over a million zones on a single core. The methodology is also capable of parallelization across shared and distributed memory architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Isolation of Histone from Sorghum Leaf Tissue for Top Down Mass Spectrometry Profiling of Potential Epigenetic Markers

Histones belong to a family of highly conserved proteins in eukaryotes. They pack DNA into nucleosomes as functional units of chromatin. Post-translational modifications (PTMs) of histones, which are highly dynamic and can be added or removed by enzymes, play critical roles in regulating gene expression. In plants, epigenetic factors including histone PTMs are related to their adaptive responses to the environment. Understanding the molecular mechanisms of epigenetic control can bring unprecedented opportunities for engineering solutions to increase the resilience of crops to climate change. Herein, we describe a protocol to isolate the nuclei and purify histones from sorghum leaf tissue. The extracted histones can be analyzed as their intact forms by top-down mass spectrometry (MS) coupled to online reversed-phase (RP) liquid chromatography (LC). Combinations and stoichiometry of multiple PTMs on the same histone proteoform can be readily identified. In addition, histone tail clipping can be detected using the top-down LC-MS workflow thus yielding the global PTM profile of core histones (H4, H2A, H2B, H3). By comparing the PTM profile among samples corresponding to different conditions (e.g. drought vs. control), potential epigenetic marks can be discovered as targets for further characterization using approaches such as chromatin immunoprecipitation – sequencing (ChIP-seq).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Cyber Threat Dictionary Using MITRE ATT&CK Matrix and NIST Cybersecurity Framework Mapping

Cyber-attack and defense frameworks offer numerous ways to protect systems and networks from threats. However, only a few of these numerous attack and defense frameworks provide countermeasures by linking multiple frameworks. Due to the lack of attack-defense mapped frameworks, a number of cyber security practitioners are often puzzled how to cope with cyber-attacks when it occurs. The objective of this paper is to present a tool called the “Cyber Threat Dictionary” to solve the problem . Cyber Threat Dictionary offers approaches and practical solutions to the threats by mapping MITRE ATT&CK Matrix to the NIST Cybersecurity Framework. By providing immediate solutions to cyber security practitioners, Cyber Threat Dictionary enables effective responses against cyber-attacks.

MITRE ATT&CK MATRIX, NIST Cybersecurity Framework,↗
DOE OSTI2022

High Temperature Optocoupler for 3D High Density Power Modules

The goal of this proposed research is to develop a reliable high-temperature optocouplers, which can operate at 250°C with at least ten-year lifetime, and replace isolation transforms as the galvanic isolation solution for the 3D integration of high density power modules. The electrification of future transportations (i.e., electric vehicles) will continuously drive the demand for high density power modules. Optocouplers (i.e., packaged light emitter and detector) as a promising candidate to replace bulky isolation transformers are highly desirable to facilitate the continuous scale-down of gate driver circuitry that will lead to 3D high density power modules and achieve disruptive performance in terms of thermal management, power density, power efficiency, reliability and operating environments. However, regular semiconductor optoelectronic materials and devices have significant difficulty functioning in the harsh environments designated for high density power module usage (such as operation at high temperatures). Ultimately, it is not the intrinsic properties of power devices that prevent their use at higher temperatures, but rather the low voltage electronics needed to drive them and the packaging that surrounds them. The typical operating temperature for optocouplers is only up to 100°C, due to the limitations of light emitting diode (LED) devices inside and packaging materials. A systematic characterization methodology will be developed to analyze the performance, lifetime and reliability of LED devices and distinguish multiple failure mechanisms at high temperatures. An original methodology of “design for reliability” will be developed to design the optoelectronic devices with high reliability and long lifetime at high temperatures. A new architecture of high temperature high reliable optocouplers will be developed, fabricated and demonstrated with continuous operating at 250°C. The development of efficient, reliable high density 3D power modules is the foundation for energy efficiency and energy reliability. Enabled with advanced 3D integration and packaging technologies, high density power module solutions can achieve much more superior performance over the conventional discrete solutions in terms of efficiency, thermal management and power density. The proposed concept of high temperature optocouplers as the galvanic isolation solution for high density power modules will bring together interdisciplinary research involving the wide bandgap materials, optoelectronics, high reliable device design, electronics packaging and power modules. A streamline of skilled personnel would be trained including graduate and undergraduate students, local engineers and scientists which are in great demand to both academia and optoelectronics industry. The proposed research topics, such as, solid state lighting and high temperature device reliability, are currently of major interest at the Department of Energy, in particular, Sandia National Laboratories. This project can enhance collaborations between the University of Arkansas (UA) and Sandia National Laboratories. The findings of the proposed research are expected to be integrated into high density 3-D power modules at the Engineering Research Center for Power Optimization for Electro-Thermal Systems (POETS).

42 ENGINEERING↗