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At least 703 records · Page 39

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Coupling a Lagrangian–Eulerian Spark-Ignition (LESI) model with LES combustion models for engine simulations

In the United States transportation sector, Light-Duty Vehicles (LDVs) are the largest energy consumers and CO 2 emitters. Electrification of LDVs is posed as a potential solution, but SI engines can still contribute to decarbonization. Car manufacturers have turned to unconventional engine operation to increase the efficiency of Spark-Ignition (SI) engines and reduce the carbon emissions of their fleets. Dilute, lean, and stratified-charge engine operation has the potential for engine efficiency improvements at the expense of increased cyclic variability and combustion instability. At such demanding engine conditions, the spark ignition event is key for flame initiation and propagation and for enhanced combustion stability. Reliable and accurate spark ignition models can help design ignition systems that reduce cyclic variability. Multiple computational spark-ignition models exist that perform well under conventional conditions, but the underlying physics needs to be expanded, for unconventional engine operation. In this paper, a hybrid Lagrangian–Eulerian Spark-Ignition (LESI) model is coupled with different turbulent flame propagation models for engine simulations. LESI relies on Lagrangian arc tracking and Eulerian energy deposition. The LESI model is coupled with the Well-Stirred Reactor (WSR), Thickened Flame Model (TFM), and g-equation model and used to simulate several cycles of a Direct-Injection Spark-Ignition (DISI) engine using a commercial Computational Fluid Dynamics (CFD) engine solver. The results showcase the successful coupling of LESI with the combustion models. Global engine metrics, such as pressure and Apparent Heat Release Rate (AHRR), for each simulation setup are compared to experimental engine results, for validation. In addition, results highlight the successful prediction of spark channel movement by comparing simulation images to experimental optical engine images. Finally, the successful coupling of LESI to combustion models, making it a usable model in the engine modeling community, is emphasized and future development details are discussed.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Genome Extraction from Shotgun Metagenome Sequence Data

Uncultivated Bacteria and Archaea comprise the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only recently become possible. To realize the hope of capturing Earth’s microbial genetic complement, technologies that accelerate recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAG genomes, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq, and others. While portions of such capabilities are individually available from other resources, the combination of the intuitive usability, data interoperability, and integration of tools in a freely available compute resource makes KBase a uniquely powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended, with additional MAG recovery and analysis tools, via the KBase SDK (Software Development Kit).

Chivian, Dylan↗

DOE OSTI2021

Moab Desert Crust - Sample 4E

Chivian, Dylan↗

DOE OSTI2026

DICOMs, Missiles, and Metadata: The U.S. Nuclear Weapons Program Leverages a Medical Standard

Digital Imagine and Communications in Medicine (DICOM) images, although most commonly used in medical settings, have been widely adopted by the United States Department of Energy (DOE) for capturing images of the internal components in a nuclear weapon. DICOMs, a lesser-known file format that combine nested metadata structures with complex image data-including multiple planes, frames, and high resolution-require the creation of access copies to support usability within the DOE. Used primarily for ensuring the safety, security, and reliability of the U.S. nuclear stockpile, the Los Alamos National Laboratory (LANL)’s DICOM images and corresponding image metadata must be accessible to scientists and researchers via our institutional centralized databases. This paper describes the author's creation of a Python script that converts DICOM images into accessible, archive-friendly TIFF files while preserving key image data and metadata.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2024

A nuclear power plant digital twin for developing robot navigation and interaction

As robot technologies are rapidly improving, an increasing number of new ideas on utilizing robots for automated operation and maintenance tasks in nuclear power plants (NPPs) are being studied. However, due to safety concerns, researchers hardly found opportunities to test their new robot solutions on physical NPPs. In that sense, an efficient and realistic simulation environment plays a vital role in the development of automation systems for an NPP. In this paper, we propose the design of a 3D digital twin system capable of simulating NPP in real-time. This system obtains the data from a full-scope NPP simulator to reproduce the operating conditions of the plant. In addition, a scenario of a team of robots performing inspection tasks like temperature and pressure measurements will highlight its usability. This system enables development of intelligent robot swarms to deploy for inspection and maintenance purposes. It will positively impact autonomous control and operations for many types of reactors by reducing uncertainty in autonomous control and providing the tools necessary for remote intervention.

Energy & Fuels↗

DOE OSTI2026

An Ab Initio Molecular Dynamics Study of Key Thermodynamic Input Parameters for Computer Simulation of U-6Nb Solidification

The key to metallic fuel development is the fabrication of uranium metal and alloys into fuel forms. U-Nb alloys are one of the best candidates for a metallic fuel alloy with high-temperature strength sufficient to support the core, acceptable nuclear properties, good fabricability, and compatibility with usable coolant media. Melt processing has been a key component of the metallic fuel cycle, and process models require thermophysical parameters at elevated temperatures, particularly above the melting temperatures, regarding which experimental data are scarce, for accurate simulations and process development. By means of ab initio density-functional theory (DFT) quantum molecular dynamics (QMD), we have calculated the main thermophysical parameters—the density, thermal expansion coefficient, specific heat, thermal conductivity, melting temperature, latent heat of fusion, and viscosity—used in the modeling of the U-6 wt.% Nb alloy casting. The melting temperature of the U-6 wt.% Nb alloy at ambient pressure is obtained by means of QMD simulations using the Z-method. The ambient volume change and latent heat of melting of U-6 wt.% Nb are also derived from QMD simulations in conjunction with analytical fitting for the energy and pressure. The thermal conductivity for the solid U-Nb alloy is calculated from the semi-classical Boltzmann transport equation combined with an estimate of the electron relaxation time obtained from DFT simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Strategies for Enhancing Battery Life Under Fast Charging: Insights from NMC-Based Cell Cycling

Fast charging improves the usability of consumer electronics and electric vehicles (EVs) by reducing range anxiety and downtime but accelerates battery degradation and raises safety concerns. Optimizing operational conditions during fast-charging is critical to mitigating aging and ensuring safety. This study evaluated multilayer Gr/NMC811 cells under various conditions, including depths of discharge (DODs of 68%, 84%, and 100%), upper charge cutoff voltages (4.1–4.2 V), and post-charge rest periods (2–30 min), using a 20 min fast charging protocol for up to 500 cycles (up to 150,000 miles of EV use assuming 3.3 mi/kWh vehicle level energy efficiency). Surprisingly, higher DODs under fast charging improved battery life and performance compared to lower DODs. Reducing the upper charge cut-off voltage helped mitigate degradation. A brief 2 min rest period after charging further reduced aging effects. The primary aging modes were loss of lithium inventory and cathode active material. Although minor lithium plating was observed within 500 cycles, it did not affect performance significantly. These findings suggest that, with optimized conditions, cells can sustain hundreds of fast charge cycles—equivalent to over 100,000 miles of EV use—without significant adverse effects on performance or longevity.

25 - ENERGY STORAGE↗

DOE OSTI2022

Postmortem and Antemortem Forensic Assessment of Pediatric Fracture Healing from Radiographs and Machine Learning Classification

A timeline of pediatric bone healing using fracture healing characteristics that can be assessed solely using radiographs would be practical for forensic casework, where the fracture event may precede death by days, months, or years. However, the dating of fractures from radiographs is difficult, imprecise, and lacks consensus, as only a few aspects of the healing process are visible on radiographs. Multiple studies in both the clinical and forensic literature have attempted to develop a usable scale to assess pediatric bone healing on radiographs using various healing characteristics. In contrast to the orthopedic definition, a fracture in forensic casework is only considered to be healed when the area around the fracture has been remodeled to the point that the fracture is difficult to detect on a radiograph or on the surface of the bone itself, a process that can take several years. We subjectively assessed visible characteristics of healing in radiograms of fractures occurring in 942 living children and adolescents. By dividing these assessments into learning and test (validation) sets, the accuracy of a newly proposed fracture healing scale was compared to a previous study. Two machine learning models were used to test predictions of the new scale. All three models produced similar estimates with substantial imprecision. Results corroborate the Malone model with an independent dataset and support the efficacy of using less complex models to estimate fracture age in children.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Unconventional Materials Processing Using Spark Plasma Sintering

Spark plasma sintering (SPS) has gained recognition in the last 20 years for its rapid densification of hard-to-sinter conventional and advanced materials, including metals, ceramics, polymers, and composites. Herein, we describe the unconventional usages of the SPS technique developed in the field. The potential of various new modifications in the SPS technique, from pressureless to the integration of a novel gas quenching system to extrusion, has led to SPS’ evolution into a completely new manufacturing tool. The SPS technique’s modifications have broadened its usability from merely a densification tool to the fabrication of complex-shaped components, advanced functional materials, functionally gradient materials, interconnected materials, and porous filter materials for real-life applications. The broader application achieved by modification of the SPS technique can provide an alternative to conventional powder metallurgy methods as a scalable manufacturing process. The future challenges and opportunities in this emerging research field have also been identified and presented.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Development and Implementation of Fault-Correction Algorithms in Fault Detection and Diagnostics Tools

A fault detection and diagnostics (FDD) tool is a type of energy management and information system that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Building operators on the leading edge of technology adoption use FDD tools to enable median whole-building portfolio savings of 8%. Although FDD tools can inform operators of operational faults, currently an action is always required to correct the faults to generate energy savings. A subset of faults, however, such as biased sensors, can be addressed automatically, eliminating the need for staff intervention. Automating this fault “correction” can significantly increase the savings generated by FDD tools and reduce the reliance on human intervention. Doing so is expected to advance the usability and technical and economic performance of FDD technologies. This paper presents the development of nine innovative fault auto-correction algorithms for Heating, Ventilation, and Air Conditioning pi(HVAC) systems. When the auto-correction routine is triggered, it overwrites control setpoints or other variables to implement the intended changes. It also discusses the implementation of the auto-correction algorithms in commercial FDD software products, the integration of these strategies with building automation systems and their preliminary testing.

field testing↗

DOE OSTI2021

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

With the increasing digitalization of processes throughout the lifecycle of buildings, data exchanged between stakeholders and between building systems has grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent, hindering the development of applications that can be reused across buildings and limiting the scalability of innovative solutions. Semantics refers to the description of the meaning of the data in a way that can be consistently understood by applications. Recently, several competing initiatives have been developing metadata schemas and ontologies to express this semantic information for different applications in the building domain. This paper systematically reviews these schemas and conducts an analysis of five of them to evaluate their applicability to three high-value use cases for building operations: energy audits, automated fault detection and diagnostics and optimal control. The survey finds 40 schemas published in the last 10 years but but their actual use in industry is difficult to estimate. Among the five selected ontologies, several gaps are highlighted in relation to the three use cases. Recommendations for the future include better harmonization of these initiatives, more centralized repositories and search engines for these schemas as well as better industry engagement to facilitate their adoption.

Smart Building, Sematic, Metadata, Ontology, Data ↗

DOE OSTI2022

Centralized and Decentralized Distributed Energy Resource Access Control Implementation Considerations.

A global transition to power grids with high penetrations of renewable energy generation is being driven in part by rapid installations of distributed energy resources (DER). New DER equipment includes standardized IEEE 1547-2018 communication interfaces and proprietary communications capabilities. Interoperable DER provides new monitoring and control capabilities. The existence of multiple entities with different roles and responsibilities within the DER ecosystem makes the Access Control (AC) mechanism necessary. In this paper, we introduce and compare two novel architectures, which provide a Role-Based Access Control (RBAC) service to the DER ecosystem’s entities. Selecting an appropriate RBAC technology is important for the RBAC administrator and users who request DER access authorization. The first architecture is centralized, based on the OpenLDAP, an open source implementation of the Lightweight Directory Access Protocol (LDAP). The second approach is decentralized, based on a private Ethereum blockchain test network, where the RBAC model is stored and efficiently retrieved via the utilization of a single Smart Contract. We have implemented two end-to-end Proofs-of-Concept (PoC), respectively, to offer the RBAC service to the DER entities as web applications. Finally, an evaluation of the two approaches is presented, highlighting the key speed, cost, usability, and security features.

42 ENGINEERING↗

DOE OSTI2024

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

This paper presents software advances to easily exploit computer architectures consisting of a multi-core CPU and CPU+GPU to accelerate diverse types of high-performance computing (HPC) applications using a single code implementation. The paper describes and demonstrates the performance of the open-source C++ matrix and array (MATAR) library that uniquely offers: (1) a straightforward syntax for programming productivity, (2) usable data structures for data-oriented programming (DOP) for performance, and (3) a simple interface to the open-source C++ Kokkos library for portability and memory management across CPUs and GPUs. The portability across architectures with a single code implementation is achieved by automatically switching between diverse fine-grained parallelism backends (e.g., CUDA, HIP, OpenMP, pthreads, etc.) at compile time. The MATAR library solves many longstanding challenges associated with easily writing software that can run in parallel on any computer architecture. This work benefits projects seeking to write new C++ codes while also addressing the challenges of quickly making existing Fortran codes performant and portable over modern computer architectures with minimal syntactical changes from Fortran to C++. We demonstrate the feasibility of readily writing new C++ codes and modernizing existing codes with MATAR to be performant, parallel, and portable across diverse computer architectures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Multipulse Optical-Rectification-Based THz Source for Accelerator Applications

THz sources offer the potential for higher frequencies and higher breakdown thresholds in accelerating structures in comparison with conventional RF sources. They also benefit from larger field strengths, field gradients, better beam synchronization and compactness. In this work, we first present the development of a 49μJ single-cycle THz source centered at 0.6 THz that provides fields over 30 MV/m. With further modifications, multicycle pulses were produced, narrowing the bandwidth of the source and potentially easing the coupling of THz radiation to relativistic electron beams and increasing the usability in other areas of research.

Lenz, Maximilian (ORCID:0009000579693042)↗

DOE OSTI2023

Recent Progress in Electrochemical Upgrading of Bio-Oil Model Compounds and Bio-Oils to Renewable Fuels and Platform Chemicals

Sustainable production of renewable carbon-based fuels and chemicals remains a necessary but immense challenge in the fight against climate change. Bio-oil derived from lignocellulosic biomass requires energy-intense upgrading to produce usable fuels or chemicals. Traditional upgrading methods such as hydrodeoxygenation (HDO) require high temperatures (200–400 °C) and 200 bar of external hydrogen. Electrochemical hydrogenation (ECH), on the other hand, operates at low temperatures (<80 °C), ambient pressure, and does not require an external hydrogen source. These environmental and economically favorable conditions make ECH a promising alternative to conventional thermochemical upgrading processes. ECH combines renewable electricity with biomass conversion and harnesses intermediately generated electricity to produce drop-in biofuels. This review aims to summarize recent studies on bio-oil upgrading using ECH focusing on the development of novel catalytic materials and factors impacting ECH efficiency and products. Here, electrode design, reaction temperature, applied overpotential, and electrolytes are analyzed for their impacts on overall ECH performance. We find that through careful reaction optimization and electrode design, ECH reactions can be tailored to be efficient and selective for the production of renewable fuels and chemicals. Preliminary economic and environmental assessments have shown that ECH can be viable alternative to convention upgrading technologies with the potential to reduce CO2 emissions by 3 times compared to thermochemical upgrading. While the field of electrochemical upgrading of bio-oil has additional challenges before commercialization, this review finds ECH a promising avenue to produce renewable carbon-based drop-in biofuels. Finally, based on the analyses presented in this review, directions for future research areas and optimization are suggested.

09 BIOMASS FUELS↗

DOE OSTI2023

Effect of Melt-Spinning Parameters on the Structure and Properties of Ni 55.5 Mn 18.8 Ga 24 Si 1.7 Heusler Alloy Ribbons

Ni–Mn-based Heusler alloys are known to demonstrate magnetic shape memory and giant magnetocaloric effect (MCE). These effects depend on the phases, crystallographic and magnetic phase transitions, and the crystallographic texture characteristics. These structural characteristics, in turn, are a function of the processing parameters. In the current work, Ni 55.5 Mn 18.8 Ga 24 Si 1.7 Heusler alloy was processed by melt-spinning under a helium atmosphere. This process results in a fine microstructure. The ribbon that was produced with a narrower nozzle width, faster wheel speed, and higher cast temperature, indicating a faster cooling rate, had double the magnetic entropy change close to room temperature. However, the other ribbon demonstrated a large entropy change over a broader temperature range, extending its usability. The effect of the melt-spinning process parameters on the developing microstructure, crystallographic structure and texture, transformation temperatures, and the magnetic entropy change were studied to explain the difference in magnetocaloric behavior.

36 MATERIALS SCIENCE↗