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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

TASK 3: PILOT PLANT GASIFIER TESTING

Aerojet Rocketdyne (AR) has developed an innovative gasifier concept incorporating advanced technologies in ultra-dense phase dry feed system, rapid mix injector, and advanced component cooling to significantly improve gasifier performance, life, and cost compared to commercially available state-of-the-art systems. Design, fabrication and initial testing of the pilot plant compact gasifier was completed in 2011 by a development team led by AR. Findings from this initial test program, as well as subsequent gasifier design and pilot plant testing by AR, identified a number of technical aspects to address prior to advancing into a demonstration-scale gasifier design. Key among these were an evaluation of gasifier ability to handle thermal environments with highly reactive coals; ability to handle high ash content, high ash fusion temperature coals with reliable slag discharge; and to develop an understanding of residual properties pertaining to gasification kinetics as carbon conversion approaches 99%. The gasifier did demonstrate the ability to withstand the thermal environments of highly reactive Powder River Basin coal, while achieving high carbon conversion in < 0.15 seconds residence time. Continuous operation with the high ash fusion temperature Xinyuan coal was demonstrated in long duration testing, validating suitability of outlet design as well as downstream slag discharge systems. Surface area and porosity data were obtained for the Xinyuan and Xinjing coals for carbon conversion ranging from 85% to 97%, and showed a pronounced downward trend in surface area per unit mass carbon as conversion increased. Injector faceplate measurements showed no incremental loss of material over the course of these experiments, validating the commercially traceable design approach and supportive of long injector life goals. Hybrid testing of PRB and natural gas was successfully completed over a wide range of natural gas feed content, providing test data to anchor predictions for commercial operation of hybrid coal/natural gas gasification plants.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Memory forensic analysis of a programmable logic controller in industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLCs) are used to automate physical processes such as nuclear plants and power grid stations, and are often subject to cyber attacks. As in conventional IT domain, the memory analysis of the PLCs can help answer important forensic questions about the attack, such as the presence of malicious firmware, injection of modified control logic (the program running on the PLC), and manipulation of I/O devices (e.g., sensors and actuators). Unlike conventional IT domain, PLCs have heterogeneous hardware architecture, proprietary firmware and control software, making it challenging to employ a unified framework for their memory forensics. For merely extracting artifacts of forensic importance, reverse-engineering the firmware is a tedious task, and the effort needs to be repeated for every PLC model. As a community, a step-wise approach to tackle this challenge is to analyze the memory of specific PLCs, and subsequently find a generic framework applicable to all PLCs. Our work is a step forward in this direction. By following a methodology that focuses on the functional layer of PLCs instead of reverse engineering the firmware, we analyze the digital forensic artifacts available in a common PLC, Allen-Bradley ControlLogix 1756-L61. Before diving into the memory dump, we analyze the PLC control software to create a list of important artifacts that are sure to exist in the PLC memory dump. The approach employs a setup where PLC control software RSLogix-5000 is connected to the PLC, and the memory dump can be obtained as and when needed. We create test cases that sequentially highlight each category of artifacts, followed by an examination of the resultant impact on memory. After attaining the listed artifacts, we employ conventional string and known data searches to extract interesting information present in this PLC's memory. The memory analysis profile, presented as a Python library and shared with the community, can help a forensic investigator to readily extract forensic artifacts from the same model's controller. The adopted approach may help researchers in creating memory profile of other PLCs, and ultimately formulating a generic PLC memory analysis framework.

Rais, Muhammad Haris↗
DOE OSTI2018

SULI Final Report

This project looks at alternative water sources, specifically in the field of desalination and selective ion removal through capacitive deionization (CDI). It project aims to both scale up the desalination capabilities of CDI cells as well as determine the selectivity of CDI for particular ions. My task is to design and build cells that have reproducible performance and characterize the materials for building these cells. The scientific methods I’ve learned through my work in CDI and the data mining and analysis tools I’ve become familiar with through CAES will be important catalysts in my future success in a graduate program. The purpose of this presentation is to give a standard of practice for my current method of building of capacitive deionization cells. Parts 1 and 2 will be discussed in which the electrodes are prepared, and the cell is built.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Analysis of the Frequency of Extreme Precipitation Events at Los Alamos National Laboratory

The Environmental Protection and Compliance (EPC) Storm Water Permitting and Compliance Program is currently updating its stormwater compliance standards for the Los Alamos National Laboratory (LANL) Engineering Standards Manual (2015) and is addressing the required current meteorological data needed for storm water applications. Information on the frequency of extreme precipitation events at LANL is needed. In response to this request, LANL Meteorology & Air Quality (MAQ) was tasked to estimate the frequency of extreme precipitation events. An earlier study by Foley (2012) which estimated extreme precipitation rates at LANL for a set of duration periods and average recurrence intervals (return periods) was evaluated. However, it was determined that this study would not be helpful since its technical support documentation was unavailable and the meteorological data and the methodology employed were not well understood. This led to the need to develop a new peer-reviewed methodology. This report documents the development of the new methodology and the application of a temporally representative precipitation dataset from February 1990 through December 2018, monitored at the official LANL meteorological station, Technical Area (TA)-6, to develop the frequency of extreme precipitation events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

UNESE Data Analysis - Disko Elm Gas Transport Characteristics (NA-22 Quarterly Report)

Two research papers describing gas transport studies in subsurface containment environments appropriate for underground nuclear explosions were revised and accepted for publication in the peer-reviewed journals, Nature – Scientific Reports and Journal of Geophysical Research. The Nature – Scientific Reports paper is a primary deliverable and describes the gas-transport experiment performed in P Tunnel (NNSS) and 1) subsequent analysis of field data as part of the UNESE program. The Journal of Geophysical Research paper describes an experiment, supported mainly by DARPA and led by researchers at Weston Geophysical and New Mexico Tech., with 2) analyses supported by this project to evaluate the ability of SF6 gas tracer to track xenon gas migration under conditions related to a previous UNESE experiment. Two new tasks consider 3) evaluation of detonation heating and multiphase flow on arrival of xenon at the surface and 4) the impact of surface or Langmuir adsorption of gases being transported through pores and along fractures.

58 GEOSCIENCES↗
DOE OSTI2022

Deployment Readiness Framework Subtask 1.1 (Literature Review)

Island and remote coastal communities face some of the most challenging environments for building, operating, and maintaining energy infrastructure, as well as the highest costs for electricity, fuels, and other essential energy sources. As sea-levels rise and storms become more intense and frequent, these communities and the energy infrastructure that supports coastal lives and livelihoods are also at increasing risk from natural hazards. To address these challenges, many coastal communities are envisioning energy solutions that will support the triple bottom line goals of the blue economy: economic growth, environmental sustainability, and social equity. Yet, island and remote coastal communities often face limited resources and capacity to tackle complex energy and coastal resilience issues. To support community-driven energy transitions in island and remote communities, and to better understand relationships between energy, community, and ecosystem resilience, the Department of Energy’s Water Power Technologies Office (WPTO) has initiated the development of a Deployment Readiness Framework (DRF). The objective of the work is to co-produce and test practical tools and approaches that assess the readiness of coastal communities for marine energy demonstration, deployment, and operation. The DRF aims to build on and support the Energy Transitions Initiative Partnership Program (ETIPP) and other community-oriented energy transition programs. This project is jointly led by Pacific Northwest National Laboratory (PNNL) and the National Renewable Energy Laboratory (NREL). The development of the DRF includes three main phases: 1) a learning phase involving stakeholder engagement and literature review to synthesize metrics of community readiness to advance through an energy transition and to understand the state of the research and practice of participatory science-policy processes in various sectors, 2) a design phase to define readiness approaches and tools that will be developed as part of the DRF, and 3) an implementation phase to create the applications and interfaces for WPTO and the national laboratories to interact with the DRF. All three phases include close collaboration with communities and end-users of the framework, first to identify gaps in the science and tools needed to achieve community-driven energy transition goals and second, to test and improve the framework iteratively. Through technical assistance programs like ETIPP and utilizing the completed DRF to understand the influencing factors which motivate or deter energy transitions, WPTO hopes to engage a number of near-term marine energy demonstration opportunities. Here we report on the results from the literature review (Subtask 1.1) to inform the stakeholder engagement (Subtask 1.2) and design phase (Task 2) of the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks

Machine learning algorithms are heavily relied on to understand the vast amounts of data from high-energy particle collisions at the CERN Large Hadron Collider (LHC). The data from such collision events can naturally be represented with graph structures. Therefore, deep geometric methods, such as graph neural networks (GNNs), have been leveraged for various data analysis tasks in high-energy physics. One typical task is jet tagging, where jets are viewed as point clouds with distinct features and edge connections between their constituent particles. The increasing size and complexity of the LHC particle datasets, as well as the computational models used for their analysis, have greatly motivated the development of alternative fast and efficient computational paradigms such as quantum computation. In addition, to enhance the validity and robustness of deep networks, we can leverage the fundamental symmetries present in the data through the use of invariant inputs and equivariant layers. In this paper, we provide a fair and comprehensive comparison of classical graph neural networks (GNNs) and equivariant graph neural networks (EGNNs) and their quantum counterparts: quantum graph neural networks (QGNNs) and equivariant quantum graph neural networks (EQGNN). The four architectures were benchmarked on a binary classification task to classify the parton-level particle initiating the jet. Based on their area under the curve (AUC) scores, the quantum networks were found to outperform the classical networks. However, seeing the computational advantage of quantum networks in practice may have to wait for the further development of quantum technology and its associated application programming interfaces (APIs).

Forestano, Roy T. (ORCID:0000000203552076)↗
DOE OSTI2022

Offshore Testing Facility – Small Scale Turbine Testing and Development Final Technical Report

In July 2010 funding for an award was made available under contract DE-EE0004200 which is the focus of this report. Under this funding, The U.S. Department of Energy’s (USDOE) designated Florida Atlantic University’s (FAU) state of Florida marine renewable energy focused Center of Excellence for Ocean Energy Technology as the Southeast National Marine Renewable Energy Center (SNMREC). The award was advertised in 2008, when the USDOE Wind and Water Program issued a funding opportunity announcement (DE-PS36-08GO98030) to establish university-led National Marine Renewable Energy Centers (NMRECs). Although FAU was selected for this opportunity, funding did not become available until 2010 at which time three of the original five years of performance remained and scope was adjusted accordingly. This award was divided into two phases. The first phase focused on marine energy turbine system enhancement and research while the second phase aimed to advance offshore capabilities and testing opportunities for small-scale demonstration turbines. The project’s objective was to increase the nation’s capabilities, knowledge, and competitiveness with respect to ocean current energy technology. This project successfully achieved these goals by advancing marine energy technology testing opportunities and capabilities. This report details these accomplishments by phase and task. Descriptions include any relevant results, challenges, achievements, and outcomes. Additional intellectual products and publications are listed in the Appendix where detailed technical explanations can be found. Further, because this award designated SNMREC as a USDOE center, it challenges FAU to continue providing value for the marine energy sector in the long term. The direct accomplishments of this project, though noteworthy, are also the seeds for a greater partnership between the USDOE and FAU. SNMREC, leveraging its designation as an NMREC under this award, will expand these contributions for decades to come as a coordinated sustainable program that can serve the marine energy sector’s needs as they arise.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Design-time performance modeling of compositional parallel programs

Performance models are powerful instruments for understanding the performance of parallel systems and uncovering their bottlenecks. Already during system design, performance models can help ponder alternative development options. However, creating a performance model – whether theoretically or empirically – for an entire application that does not exist yet is challenging. In this paper, we propose to generate performance models of full programs from performance models of their components using formal composition operators derived from parallel design patterns. As long as the design of the overall system follows such a pattern, its performance model can be predicted with reasonable accuracy without an actual implementation. In conclusion, we demonstrate our approach with design patterns of varying complexity, including pipeline, task pool, and eventually MapReduce, which is representative of a broad class of data-analytics applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Verification of Electromagnetic Physics Models for Parallel Computing Architectures in the GeantV Project

An intensive R&D and programming effort is required to accomplish new challenges posed by future experimental high-energy particle physics (HEP) programs. The GeantV project aims to narrow the gap between the performance of the existing HEP detector simulation software and the ideal performance achievable, exploiting latest advances in computing technology. The project has developed a particle detector simulation prototype capable of transporting in parallel particles in complex geometries exploiting instruction level microparallelism (SIMD and SIMT), task-level parallelism (multithreading) and high-level parallelism (MPI), leveraging both the multi-core and the many-core opportunities. We present preliminary verification results concerning the electromagnetic (EM) physics models developed for parallel computing architectures within the GeantV project. In order to exploit the potential of vectorization and accelerators and to make the physics model effectively parallelizable, advanced sampling techniques have been implemented and tested. In this paper we introduce a set of automated statistical tests in order to verify the vectorized models by checking their consistency with the corresponding Geant4 models and to validate them against experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Net Shape Fabricated Low Cost MHK Pass-Through the Hub Turbine Blades with Integrated Health Management Technology

The primary objective of this project is to develop a three-blade MHK rotor with low manufacturing and maintenance costs. The proposed program will design, fabricate and test a novel half-scale low cost, net shape fabricated single piece three-blade MHK rotor with integrated health management technology to demonstrate significant Capital Expenditures (CAPEX) and Operational Expenditures (OPEX) cost reductions due to the novel design and manufacturing process. The proposed project is divided into three major tasks: Task 1: Single Piece Three-blade Kinetic Hydropower System (KHPS) Rotor Full-Scale and Half-Scale Design; Task 2: Composite Manufacturing Trials and Half-Scale Prototype Rotor Fabrication; and Task 3: Material Characterization and Half-Scale Prototype Test and Evaluation. These three tasks include design and analysis of full-scale and half-scale three-blade rotor prototypes using computational fluid dynamics (CFD) and finite-element analysis (FEA), demonstration of a novel half-scale net shape fabrication process, determination of a fatigue threshold composite strain allowable, three-blade rotor mold design, manufacture of half-scale rotor clam shell mold, three-blade rotor test fixture design and fabrication, development of final manufacturing and test plans, manufacture of the half-scale net shape composite single blade and three-blade prototypes, and test and evaluation of the half-scale rotor.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Development of Enabling Technologies for a Pressurized Dry Feed Oxy-Coal Reactor

Researchers at Brigham Young University (3 faculty, 9 graduate students, and 35 undergraduate students) completed this 5-year research program with the main objective to build and test a 100 kWth pressurized dry-feed oxy-coal combustor (POC). This objective was achieved through the development and testing of a unique pressurized dry coal fluidization feed system that operates in conjunction with a pressurized oxycoal combustor. The project included a series of R&D tasks, including design, modeling, bench-scale testing, construction, safety reviews, and reactor testing which are detailed in this report. BYU researchers were supported in some modeling tasks by project partners Reaction Engineering International (REI) and CPFD Software.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2015

Prediction Models for Dynamic Demand Response

As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D 2 R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D 2 R, which we address in this paper. Our first contribution is the formal definition of D 2 R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D 2 R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D 2 R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D 2 R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D 2 R. Also, prediction models require just few days’ worth of data indicating that small amounts of historical training data can be used to make reliable predictions, simplifying the complexity of big data challenge associated with D 2 R.

Aman, Saima↗
DOE OSTI2016

Consensus Statement on Proton Therapy in Early-Stage and Locally Advanced Non–Small Cell Lung Cancer

Radiation dose escalation has been shown to improve local control and survival in patients with non–small cell lung cancer in some studies, but randomized data have not supported this premise, possibly owing to adverse effects. Because of the physical characteristics of the Bragg peak, proton therapy (PT) delivers minimal exit dose distal to the target volume, resulting in better sparing of normal tissues in comparison to photon-based radiation therapy. This is particularly important for lung cancer given the proximity of the lung, heart, esophagus, major airways, large blood vessels, and spinal cord. However, PT is associated with more uncertainty because of the finite range of the proton beam and motion for thoracic cancers. PT is more costly than traditional photon therapy but may reduce side effects and toxicity-related hospitalization, which has its own associated cost. The cost of PT is decreasing over time because of reduced prices for the building, machine, maintenance, and overhead, as well as newer, shorter treatment programs. PT is improving rapidly as more research is performed particularly with the implementation of 4-dimensional computed tomography–based motion management and intensity modulated PT. Given these controversies, there is much debate in the oncology community about which patients with lung cancer benefit significantly from PT. The Particle Therapy Co-operative Group (PTCOG) Thoracic Subcommittee task group intends to address the issues of PT indications, advantages and limitations, cost-effectiveness, technology improvement, clinical trials, and future research directions. This consensus report can be used to guide clinical practice and indications for PT, insurance approval, and clinical or translational research directions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Evolving Obs4MIPs to Support Phase 6 of the Coupled Model Intercomparison Project (CMIP6)

Over the past four years, an initiative known as Observations for Model Intercomparison Projects (Obs4MIPs) has successfully completed its pilot phase by adopting a set of technical protocols (dataset format, metadata standards, and documentation requirements) for dataset contributions, producing datasets that conform to these standards and archiving them for distribution on the Earth System Grid Federation (ESGF) alongside the fifth phase of the Coupled Model Intercomparison Project (CMIP5) model output. This pilot phase of Obs4MIPs, initiated by the National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL) and the Department of Energy’s (DOE) Program for Climate Model Diagnosis and Intercomparison (PCMDI) at Lawrence Livermore National Laboratory, supported CMIP5 and provided a path to improve the coordination between observational communities and major climate modeling intercomparison projects such as CMIP. Obs4MIPs is now being embraced by the international community, with the World Climate Research Programme (WCRP) Data Advisory Council (WDAC) empaneling a task team to provide guidance and governance for Obs4MIPs at an international level, in conjunction with the existing NASA Science Working Group that is more tightly focused on NASA satellite data products. Here, following the example of the first DOE–NASA Obs4MIPs meeting, and with an initial design of CMIP6 being published, a meeting of over 50 experts in both climate modeling and satellite data from the United States, Europe, Japan, and Australia convened at NASA headquarters in Washington, D.C., for the purpose of planning the evolution of Obs4MIPs and its connection to the CMIP6 experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

ORNL NCSP Training and Education Support for FY2023 [Slides]

This presentation goes over the ORNL NCSP training and education support for Fiscal Year (FY) 2023. It includes a look at approved training and education tasks set up for FY2023. This lecture also covers revisions and updates to proposals and the LA-12808 LA-12808 Nuclear Criticality Safety Guide.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

A simplified approach for creep damage and remaining life calculation for materials surveillance in advanced reactors

High temperature reactor materials will experience a combination of mechanical degradation caused by creep and fatigue and environmental degradation caused by neutron irradiation and, in some cases, exposure to corrosive coolants. A materials surveillance program is one option for ensuring the safe, reliable operation of key reactor components under these conditions. Such a program would monitor the degradation in key material properties over time, using this data to predict how changes in the material properties affect components performance. This could then be used to make plant operational decisions and support eventual plant license extensions. Past work de-scribes such a material surveillance program based on passively actuated mechanical test articles that impose creep-fatigue type loading on test materials driven only by changes in temperature, for example those experienced by components under standard operating cycles. This report focuses on two aspects of the proposed material surveillance program: how to design the test articles to mimic the mechanical response of the corresponding component and how to use ex-situ test data to deter-mine the amount of damaged experienced by the test article (and hence the corresponding compo-nent) in service. Specifically, this report derives and validated simplified methods for both tasks, replacing earlier, more complicated approaches based on simulating the test article response and finding the best specimen design or current damage via complex numerical optimization. The sim-plified methods for each task developed here can be implemented in spreadsheet software and are simple enough for practical use in future operating plants. This report derives the methods (one for sizing and two options for damage inference), verifies the simplified approaches versus more so-phisticated methods, and compares the results of applying the simplified methods to previous re-sults using the complex numerical optimization approach. The report also provides a worked sam-pled problem applying the simplified techniques to a realistic high temperature reactor component.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

On the adequacy of lightweight thread approaches for high-level parallel programming models

High-level parallel programming models (PMs) are becoming crucial in order to extract the computational power of current on-node multi-threaded parallelism. The most popular PMs, such as OpenMP or OmpSs, are directive-based: the complexity of the hardware is hidden by the underlying runtime system, improving coding productivity. The implementations of OpenMP usually rely on POSIX threads (pthreads), offering excellent performance for coarse-grained parallelism and a perfect match with the current hardware. OmpSs is a task oriented PM based on an ad hoc runtime solution called Nanos++; it is the precursor of the tasking parallelism in the OpenMP tasking specification. A recent trend in runtimes and applications points to leveraging massive on-node parallelism in conjunction with fine-grained and dynamic scheduling paradigms. In this paper we analyze the behavior of the OpenMP and OmpSs PMs on top of the recently emerged Generic Lightweight Threads (GLT) API. GLT exposses a common API for lightweight thread (LWT) libraries that offers the possibility of running the same application over different native LWT solutions. We describe the design details of those high-level PMs implemented on top of GLT and analyze different scenarios in order to assess where the use of LWTs may benefit application performance. Our work reveals those scenarios where LWTs overperform pthread-based solutions and compares the performance between an ad hoc solution and a generic implementation.

97 MATHEMATICS AND COMPUTING↗