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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Earth System Grid Federation (ESGF) Compute Challenge

This Open Geospatial Consortium (OGC) Engineering Report (ER) describes the advancement of an Execution Management System (EMS) to support Web Processing Service (WPS) climate processes deployed on the Earth System Grid Federation (ESGF). The report introduces climate data, processes and applications into Common Workflow Language (CWL) workflows with the intent of advancing: application packaging, deployment and execution in clouds; interoperability of services in federated cyberinfrastructures; and geospatial workflows towards standardization. Work presented in this report is a direct continuation of the Earth Observation & Clouds (EOC) thread of Testbed-14. This report is expected to be of relevance to Testbed-15, both to the Earth Observation Process and Application Discovery (EOPAD) task and the Machine Learning task. This engineering report will describe: relevant work conducted in OGC Testbed-14; ESGF and its compute challenge; adaptations of existing climate processes into workflows; interoperability experiments with ESGF endpoints conforming to a common API.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An Agile/XP software development process for modernizing the accelerator control system at Fermilab

Fermilab is undergoing the most ambitious upgrade to its accelerator control system of the 21st century. As part of the ACORN project, hundreds of legacy control system applications written in C/C++ will be re-imagined and developed from the ground up. In addition, applications to support Fermilab’s new super-conducting linear accelerator are already under construction. To manage the development of modern controls applications, the Controls department has adopted an Agile software development process based on eXtreme Programming. In this paper we will describe our process and detail our experience applying it to the development of two case studies.

Diamond, John [Fermilab]↗
DOE OSTI2015

TU-F-CAMPUS-I-05: Semi-Automated, Open Source MRI Quality Assurance and Quality Control Program for Multi-Unit Institution

Purpose: Phantom measurements allow for the performance of magnetic resonance (MR) systems to be evaluated. Association of Physicists in Medicine (AAPM) Report No. 100 Acceptance Testing and Quality Assurance Procedures for MR Imaging Facilities, American College of Radiology (ACR) MR Accreditation Program MR phantom testing, and ACR MRI quality control (QC) program documents help to outline specific tests for establishing system performance baselines as well as system stability over time. Analyzing and processing tests from multiple systems can be time-consuming for medical physicists. Besides determining whether tests are within predetermined limits or criteria, monitoring longitudinal trends can also help prevent costly downtime of systems during clinical operation. In this work, a semi-automated QC program was developed to analyze and record measurements in a database that allowed for easy access to historical data. Methods: Image analysis was performed on 27 different MR systems of 1.5T and 3.0T field strengths from GE and Siemens manufacturers. Recommended measurements involved the ACR MRI Accreditation Phantom, spherical homogenous phantoms, and a phantom with an uniform hole pattern. Measurements assessed geometric accuracy and linearity, position accuracy, image uniformity, signal, noise, ghosting, transmit gain, center frequency, and magnetic field drift. The program was designed with open source tools, employing Linux, Apache, MySQL database and Python programming language for the front and backend. Results: Processing time for each image is <2 seconds. Figures are produced to show regions of interests (ROIs) for analysis. Historical data can be reviewed to compare previous year data and to inspect for trends. Conclusion: A MRI quality assurance and QC program is necessary for maintaining high quality, ACR MRI Accredited MR programs. A reviewable database of phantom measurements assists medical physicists with processing and monitoring of large datasets. Longitudinal data can reveal trends that although are within passing criteria indicate underlying system issues.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Characterizing the Oscillatory Properties of Bulk Electric Systems

This paper presents a process for characterizing the oscillatory dynamics of a large bulk power system. As a demonstration, the process is applied to the Western Interconnection of North America. Several complementary analysis approaches, both new and existing, are employed to provide a comprehensive understanding of the oscillatory properties of the system. Established modal analysis techniques based on ringdown and mode-meter algorithms are utilized. In addition, we derive and apply methods based on spectral correlation analysis to identify modal frequencies, distinguish between modes that are closely spaced in frequency, and determine locations at which the modes are observable. Critical interarea modes are identified and characterized using actual-system synchrophasor measurements taken over several years of operation in concert with industry-standard simulation models. This includes 145 hours of PMU data and two planning base cases.

42 ENGINEERING↗
DOE OSTI2015

Apparatus and method for converting biomass to feedstock for biofuel and biochemical manufacturing processes

The present invention includes improved systems and methods for producing biomass-derived feedstocks for biofuel and biochemical manufacturing processes. The systems and methods use components that are capable of transferring relatively high concentrations of solid biomass utilizing pressure variations between vessels, and allows for the recovery and recycling of heterogeneous catalyst materials.

09 BIOMASS FUELS↗
DOE OSTI2023

Signal Decomposition for Intrusion Detection in Reliability Assessment in Cyber Resilience (Summary Report)

The complexity of assuring cyber resilience for physical process interactions in connected systems such as energy grids increases dramatically as the coupling between processes becomes more direct and responsive. An example of this growing complexity is provided by Integrated Energy Systems (IES), in which various processes such as nuclear heat generation and commodity production are being directly coupled for increased responsiveness to highly variable signals such as market pricing or electricity demand. As such, the potential attack surface of the coupled processes is larger than the two processes independently. Securing these complex systems requires two-fold monitoring: cybersecure monitoring for potential malicious incursion, and physics monitoring for system tampering. Physics monitoring includes analyzing the behavior of the signals within the system for anomalous behavior. This analysis has been shown to be insufficient if approached by only data-driven machine learning and artificial intelligence (MLAI) techniques or only low-level model comparison. Previous efforts at Purdue University suggested combining high-fidelity models with MLAI algorithms as a basis for a software tool for detecting anomalies in physical processes. This work built on that suggestion, developing an advanced library for signal decomposition and analysis using both MLAI and high-fidelity physics algorithms for greatly improved anomaly detection, especially false data injection. This software can be used as part of a secure imbedded intelligence (SEI) system designed under Consequence-driven Cyber-informed Engineering (CCE) for complex coupled systems. This library established a foundation for online and posteriori analysis of digital signals for the purpose of detecting potential malicious tampering in digital signals representing physical processes. Demonstrations carried out throughout the development highlight the effective use of characterization algorithms to detect signal perturbations, particularly triangle attack-style perturbations, in three wide-ranging applications: seismic monitoring, nuclear thermal hydraulics system simulation, and custom manufacturing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Reactor Subsystem Simulation for Nuclear Hybrid Energy Systems

Nuclear Hybrid Energy Systems (NHES) could be a key part of the solution to achieving energy security, may provide reliable power availability even with increasing renewable energy penetration into the power grid, and may allow repurposing excess electricity in times of low demand. Incorporating a fission-based power source in a multi-output system (electricity and process heat) can offer significant advantages over carbon-based production sources, such as coal or natural gas, including reduction in atmospheric carbon emissions. In an integrated multi-output system, thermal energy from the nuclear reactor subsystem can be diverted to industrial applications in times of low electricity demand. High temperature, high quality heat from advanced reactor designs might be used for hydrogen production or synthetic fuel production (coal-to-liquid or natural gas-to-liquid processes). Low temperature heat from advanced reactor designs or the current and future fleet of light water reactors (LWRs) might be applied to desalination processes or be stored for later use in low temperature ammonia or hydrocarbon-based thermal cycles. The NHES research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation. Many computational tools and methods are available for modeling a nuclear reactor, power conversion systems and associated process applications. One method is to develop a single program capable of modeling the entire system. Another is to combine two or more existing computer programs, each modeling a portion of the system for which it is validated, where the programs exchange information to compute the solution. The former method requires a lengthy development and verification and validation process. The latter method leverages industry standard software to reduce development and funding requirements. Preliminary system models have been developed by Idaho National Laboratory researchers and are currently being enhanced to assess integrated system performance given multiple sources (e.g., nuclear + wind) and multiple applications (i.e., electricity + process heat). Initial efforts to integrate a Fortran-based simulation of a small modular reactor (SMR) with the balance of plant model have been completed in FY12. This initial effort takes advantage of an existing SMR model developed at North Carolina State University to provide initial integrated system simulation for a relatively low cost. The SMR subsystem simulation details are discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2011

Final Report Integrated DM1200 Melter Testing Using AZ-102 and C-106/AY-102 HLW Simulants: HLW Simulant Verification

The principal objectives of the DM1200 melter tests were to determine the effects of feed rheology, feed solid content, and bubbler configuration on glass production rate and off-gas system performance while processing the HLW AZ-101 and C-106/AY-102 feed compositions; characterize melter off-gas emissions; characterize the performance of the prototypical off-gas system components, as well as their integrated performance; characterize the feed, glass product, and off-gas effluents; and perform pre- and post test inspections of system components. The specific objectives (including test success criteria) of this testing, along with how each objective was met, are outlined in a table.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Molecular Dynamics Simulation of the Structure and Properties of CaO-SiO{sub 2}-CaF{sub 2} Slag Systems

As a fundamental slag system in metallurgical processes, the CaO-SiO{sub 2}-CaF{sub 2} system, its properties, and related microstructures are of critical importance. The effect of the binary basicity and addition of CaF{sub 2} on the structure and viscosity of CaO-SiO{sub 2}-CaF{sub 2} slag were investigated using molecular dynamics simulations and Fourier transform infrared spectrometry. The average bond lengths of Si-O, Ca-O, and O-O were 1.61, 2.31, and 2.61 Å, respectively, and the coordinate number of Si remained constant. O-Si-O maintained an angle of 109.2, which was considered to be unaffected by the basicity changes. With increasing basicity, the network connectivity degrees Q{sup 3} and Q{sup 4} decreased, and the microstructure of the melt was significantly simpler. The effect of CaF{sub 2} on the depolymerization of the network structure was not obvious, and CaF{sub 2} acted mainly as a diluent. The calculations showed that the viscosity decreased upon setting up a ratio of nonbridging oxygen over tetrahedrally coordinated atoms (NBO/T). A good linear relationship was confirmed between the viscosity of the molten slag and the NBO/T.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Crystallization and functionality of inorganic materials

In this article, we briefly summarized our recent work on the studies of crystallization and functionality of inorganic materials. On the basis of the chemical bonding theory of single crystal growth, we can quantitatively simulate Cu{sub 2}O crystallization processes in solution system. We also kinetically controlled Cu{sub 2}O crystallization process in the reduction solution route. Lithium ion battery and supercapacitor performances of some oxides such as Co{sub 3}O{sub 4} and MnO{sub 2} were shown to elucidate the important effect of crystallization on functionality of inorganic materials. This work encourages us to create novel functionalities through the study of crystallization of inorganic materials, which warrants more chances in the field of functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simulating a solar parabolic trough collector plant used for industrial process heat using an optimized operating scheme that utilizes flexible heat integration

This study focuses on the modeling and simulation of a novel design and operation of a solar industrial process heat (SIPH) plant that uses a parabolic trough collector system for generating process heat. The SIPH plant incorporates flexible heat integration (FHI) by having two options for heat sinks as well as a flexible collection temperature for the heat transfer fluid. Leveraging the degrees of freedom created by FHI allows an optimized operating scheme to be created which maximizes the solar heat delivered to the industrial processes. Yearly results for a 27 MW-t plant located in Salt Lake City, UT are simulated for a base case and a case utilizing optimized FHI. For the main process temperature case presented, FHI increases the total solar share by 13.0% and reduces the levelized cost of heat of the SIPH plant by 10.4% relative to the base case. Furthermore, three case study days are presented which highlight how FHI maximizes solar share, specifically during mornings, afternoons, and days with intermittent solar conditions. An environmental analysis is also performed showing that the SIPH plant can reduce harmful emissions by 15.4% for the base case and 17.4% for the FHI case compared to a plant that only utilizes a natural gas furnace for process heat. Overall, the work thoroughly explores an effective operating scheme for a SIPH plant, helping to make it more economical and environmentally beneficial.

14 SOLAR ENERGY↗
DOE OSTI2018

High-Level Simulation for Spiking Neuromorphic Computing Systems

Neuromorphic computing systems are alternatives to conventional microprocessors, often built from unconventional hardware. Designing and evaluating these systems requires multiple levels of simulation, from the device level to the circuit level to the system level. In this paper, we describe the system level simulator of a neuromorphic computing system based on memristors. We compare it to a circuit level simulator of the same system, both verifying its accuracy and demonstrating its performance improvement. We argue that system level simulation is an essential part of the design process of neuromorphic systems.

Skuda, Nicholas↗
DOE OSTI2021

Qubit Control System (QubiC) v1.0

We design a modular FPGA (field-programmable gate array) based system called QubiC to control and measure a superconducting quantum processing unit. The system includes room temperature electronics hardware, FPGA gateware, and engineering software.

Huang, Gang↗
DOE OSTI2023

State Energy Offices’ Engagement in Electric Distribution Planning to Meet State Policy Goals

NASEO and Berkeley Lab released a new publication on State Energy Offices’ Engagement in Electric Distribution Planning to Meet State Policy Goals. State and Territory Energy Offices develop plans, programs, policies, and projects that have a substantial impact on electric distribution systems. They also can participate in distribution system planning (DSP) processes to help ensure that utilities – consumer- and investor-owned – meet the state’s future energy needs. This paper recognizes the wide spectrum of roles that State Energy Offices can play in DSP processes, including planning for distributed energy resources and grid modernization. It highlights various examples of non-regulatory activities by State Energy Offices including planning, conducting studies, convening stakeholder processes, and implementing programs that inform and contribute to distribution system planning. It also provides examples of State Energy Offices’ engagement in proceedings before their respective public utility commissions. As State Energy Offices face myriad challenges associated with meeting state policy goals, preparing for anticipated rates of distributed energy resource deployment, addressing concerns regarding grid reliability and resilience, and recommending and making long-term investment decisions, the examples provided through this guide can serve as a resource in navigating those challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Power System Waveform Classification Using Time-Frequency and CNN

Many modern reclosers and circuit breakers have microprocessor relays that record waveforms of system events. In some cases, utilities may record a half-a-dozen event captures for every event. This is thousands of events per year. The industry needs faster, more automated, more conclusive, and easy-to-use systems that can process massive amounts of event recordings without extensive input/support from power system engineers. To address the need for a commercially viable solution that can classify waveform data, energies were directed to develop a universal neural network (NN) structure (deep learning algorithm) that works for a wide variety of system event types. The structure that showed the most promise was one that included the use of spectrograms. The technique has shown positive results in audio engineering, particularly with respect to speech recognition. A waveform signature could be treated as a spoken word like audio waveforms for specific things such as “YES” or “UP”. No two people produce the exact same waveform when speaking each of these words, but audio processing algorithms based on spectrograms and convolutional neural networks (CNN) can still distinguish the word regardless of the speaker. No two circuits produce the exact same waveform for a given event, but the NN can be trained to classify the event type regardless of the circuit or location on the circuit. A Power System Neural Network (PSNN) has been developed to use a CNN to classify events within waveform data for power systems. The waveform is converted to an array of values by way of spectrograms and interpreted as an image. This image is passed into the CNN. The test results on independent simulated test and validation datasets show greater than 99% accuracy. While the results thus far are based on simulated data, the performance of the PSNN is very promising and should work for a wide variety of power system conditions of interest. Ultimately, much of the custom code and tools used today and much of the manual effort expended today may be automated using this PSNN.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Return of the Lemnaceae: duckweed as a model plant system in the genomics and postgenomics era

Abstract The aquatic Lemnaceae family, commonly called duckweed, comprises some of the smallest and fastest growing angiosperms known on Earth. Their tiny size, rapid growth by clonal propagation, and facile uptake of labeled compounds from the media were attractive features that made them a well-known model for plant biology from 1950 to 1990. Interest in duckweed has steadily regained momentum over the past decade, driven in part by the growing need to identify alternative plants from traditional agricultural crops that can help tackle urgent societal challenges, such as climate change and rapid population expansion. Propelled by rapid advances in genomic technologies, recent studies with duckweed again highlight the potential of these small plants to enable discoveries in diverse fields from ecology to chronobiology. Building on established community resources, duckweed is reemerging as a platform to study plant processes at the systems level and to translate knowledge gained for field deployment to address some of society’s pressing needs. This review details the anatomy, development, physiology, and molecular characteristics of the Lemnaceae to introduce them to the broader plant research community. We highlight recent research enabled by Lemnaceae to demonstrate how these plants can be used for quantitative studies of complex processes and for revealing potentially novel strategies in plant defense and genome maintenance.

Biochemistry & Molecular Biology↗
DOE OSTI2012

Multi-core processing and scheduling performance in CMS

Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resulting in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.

Hernandez, J. M.↗