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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Model-Based Approaches to Generate Knowledge from Data in a Plant Reliability Context

One challenge that nuclear power plant system engineers are facing is continuous generation of an extremely large amount of equipment reliability (ER) data. These data elements come in textual (e.g., condition reports) and numeric (e.g., generated by monitoring systems) forms. They provide system engineers with valuable insights and information by discovering anomalous behaviors or degradation trends, identifying possible causes behind such behaviors and trends, and predicting their direct consequences. This paper directly targets the knowledge generation from ER data by putting “data into context.” We employ model-based system engineering (MBSE) of systems and assets to represent and capture their architecture and functional (i.e., cause-effect) relations. ER data elements are processed by first identifying which of the developed MBSE elements they are referring to. This task is harder for textual data since the information contained in issue or maintenance reports needs to be “understood” by a computational tool. We called this process “knowledge extraction” since our methods extract knowledge from textual data. Last, once numeric and textual ER data elements have been processed and “understood,” we discover possible cause-effect relations among them. This is performed by observing whether a logical connection through the MBSE models exists, and if there is a temporal relationship among them. The logic and temporal are the two main ingredients to perform “machine reasoning” from ER data.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Nonlinear Signal Processing for Removing Microphonic Noise from Nuclear Spectrometer Measurements: Sparse Linear Modeling via L1 Norm Regularization [Slides]

The focus of this initial work is to apply recent breakthroughs in sparse linear modeling and nonlinear signal processing to the problem of removing microphonic noise from nuclear spectrum measurements. The resolution of nuclear spectrum measurements is commonly degraded by microphonic noise caused by the vibration of supporting equipment (i.e. cryocoolers) as well as motion of the detector itself in mobile applications. Current signal processing techniques cannot remove microphonic noise without modifying the desired characteristics of the spikes induced by nuclear detection events. The LANL Engineering Institute has been working with NEN‐1 to remedy this problem. Initial work focused on developing active control systems to cancel the vibrations experienced by nuclear detectors. As work on progressed along these lines the team realized that a more robust, lower‐energy, lower‐cost solution to the microphonic noise problem could be realized using recent breakthroughs in nonlinear signal processing. Over the course of the last decade significant advances have been made in the field of sparse linear modeling using L1 norm minimization to find linear representations of sparse signals. The problem of removing microphonic noise from nuclear detection measurements appears to be well suited to the L1 minimization approach because these measurements tend to be inherently sparse in two different domains. The nuclear detections are sparse in a spike domain, and the microphonic noise is sparse in the Fourier basis. L1 minimization allows us to decompose the measurements into these two domains. The result is that we can potentially separate the spikes from the microphonic noise. Initial investigations into this technique look very promising. In this work microphonic noise is induced in an HE‐3 detector by a wrench impact. A pulser is used to generate uniform, synthetic, nuclear events and is fed into the detector front end electronics. Nearly all the microphonic noise is separated from the spike measurements. The histograms in Figure 2 illustrate that spectrum widening caused by noise is significantly reduced. The goal of future work to further develop this technique to account for variations in spike characteristics, as well as to use adaptive signal processing and modern Graphical Processing Unit (GPU) technology to speed up the signal decompositions.

42 ENGINEERING↗
DOE OSTI2021

Recent Advances in Machine Learning for Fiber Optic Sensor Applications

Over the last three decades, fiber optic sensors (FOS) have gained a lot of attention for their wide range of monitoring applications across many industries, including aerospace, defense, security, civil engineering, and energy. FOS technologies hold great promise to form the backbone for next‐generation intelligent sensing platforms that offer long‐distance, high‐accuracy, distributed measurement capabilities and multiparametric monitoring with resilience to harsh environmental conditions. The major limitations posed by FOS are 1) cross‐sensitivity, 2) enormous volume and large data generation, 3) low data processing speed, 4) degradation of signal‐to‐noise ratio over the fiber length, and 5) overall cost of sensor and interrogator systems. These challenges can be overcome by building advanced data analytics engines enabled by recent breakthroughs in machine learning (ML) and artificial intelligence (AI). This article presents a comprehensive review of recent studies that integrate ML and AI algorithms with FOS technologies. This review also highlights several FOS technology development directions that promise a significant impact on widespread use for several industrial applications, with an emphasis on energy systems monitoring. A perspective on future directions for further research development is also provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

A Prototyping Environment for Research on Human-Machine Interfaces in Process Control: Use of Microsoft WPF for Microworld and Distributed Control System Development

Operators of critical processes, such as nuclear power production, must contend with highly complex systems, procedures, and regulations. Developing human-machine interfaces (HMIs) that better support operators is a high priority for ensuring the safe and reliable operation of critical processes. Human factors engineering (HFE) provides a rich and mature set of tools for evaluating the performance of HMIs, but the set of tools for developing and designing HMIs is still in its infancy. Here we propose that Microsoft Windows Presentation Foundation (WPF) is well suited for many roles in the research and development of HMIs for process control.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Quantum-Carnot engine for particle confined to 2D symmetric potential well

Carnot model of heat engine is the most efficient cycle consisting of isothermal and adiabatic processes which are reversible. Although ideal gas usually used as a working fluid in the Carnot engine, Bender used quantum particle confined in 1D potential well as a working fluid. In this paper, by following Bender we generalize the situation to 2D symmetric potential well. The efficiency is express as the ratio of the initial length of the system to the final length of the compressed system. The result then is shown that for the same ratio, 2D potential well is more efficient than 1D potential well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Environmental cleanup of the East Tennessee Technology Park - Year three - A status report - 15522

On August 1, 2011, URS - CH2M Oak Ridge LLC (UCOR) began its five-year, $1.4 billion cleanup of the East Tennessee Technology Park (ETTP), the former Oak Ridge Gaseous Diffusion Plant, located on the U.S. Department of Energy's (DOE) Oak Ridge Reservation (Reservation) in Tennessee. Under the contract, the base period scope of work to be completed by 2016 includes demolition of both the K-25 and K-31 gaseous diffusion buildings and all demolition waste dispositioned, initiation of demolition on the remaining K-27 gaseous diffusion building, safe storage of transuranic (TRU) waste for eventual transfer to the Transuranic Waste Processing Center, previously designated -No-Path-To-Disposition Waste- dispositioned to the extent possible, and completion of design and engineering of a mercury treatment system to be installed at the Y-12 National Security Complex (Y-12). UCOR will have also managed DOE Oak Ridge Office of Environmental Management (OREM)-owned facilities at ETTP, Oak Ridge National Laboratory (ORNL), and Y-12 in a safe and cost-effective manner. Since assuming responsibilities as the ETTP and Oak Ridge Reservation cleanup contractor, UCOR has completed its life-cycle Performance Measurement Baseline; received its Earned Value Management System (EVMS) certification; completed the deactivation and demolition (D and D) of the 44-acre K-25 gaseous diffusion building; removed and disposed of a contaminated underground storage tank (Tank W-1A) at ORNL; dispositioned mercury-contaminated storage tanks at Y-12; completed closure of the Toxic Substances Control Act Incinerator; disposed of more than 158,000 cubic yards of cleanup waste while managing the on-site Environmental Management Waste Management Facility (EMWMF); and conducted operations, surveillance, and maintenance activities at 180 DOE EM facilities at ETTP, ORNL, and Y-12 in a safe and cost-effective manner. In 2014, UCOR completed the removal and disposal of all of the K-25 demolition debris; completed the removal of asbestos-laden transite siding on the K-31 gaseous diffusion building and began demolition of that 17-acre building; advanced the characterization and deactivation of the K-27 gaseous diffusion building, readying the building for the start of demolition in 2015; advanced the design and engineering of a Mercury Treatment Facility to be located at Y-12; continued the cost-effective and safe disposition of all cleanup wastes; and readied ETTP for Voluntary Protection Program Star Status Assessment in 2015. Project performance as of December 31, 2014, continued to be excellent: - Cost Performance Index - 1.12 - Schedule Performance Index - 1.02 At the same time, since safety is the foundation of all cleanup work, UCOR's safety record goes hand-in-hand with its excellent project performance. Through calendar year 2014, UCOR's recordable injury rate was 1.04 occurrences per 200,000 work hours, and the lost workday case rate was 0.52. This performance continues to be due, in large part, to the people and processes URS and CH2M HILL, the parent companies of UCOR, brought to the project. Key enablers included: - Selected and deployed experienced staff in key leadership positions throughout the organization, continually re-energizing the organization with new leaders - Implemented previously successful safety programs and initiatives from other DOE sites, such as DOE's Voluntary Protection Program - Brought fresh thinking and innovation to tackling tough project issues, such as the deactivation of the Technetium-99-contaminated areas of K-27, applying lessons learned from the D and D of K-25; and implementing a -waste factory- approach to cleanup - Maintained continuing alignment between UCOR's contract with DOE and its Performance Measurement Baseline - rapidly addressing contract changes when they arose - Maintained a readiness both from a process as well as experienced personnel perspective to support DOE OREM in performing other significant Oak Ridge Reservation cleanup activities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

An experimental system for high temperature X-ray diffraction studies with in situ mechanical loading

An experimental system with in situ thermomechanical loading has been developed to enable high energy synchrotron x-ray diffraction studies of crystalline materials. The system applies and maintains loads of up to 2250 N in uniaxial tension or compression at a frequency of up to 100 Hz. The furnace heats the specimen uniformly up to a maximum temperature of 1200 Degree-Sign C in a variety of atmospheres (oxidizing, inert, reducing) that, combined with in situ mechanical loading, can be used to mimic processing and operating conditions of engineering components. The loaded specimen is reoriented with respect to the incident beam of x-rays using two rotational axes to increase the number of crystal orientations interrogated. The system was used at the Cornell High Energy Synchrotron Source to conduct experiments on single crystal silicon and polycrystalline Low Solvus High Refractory nickel-based superalloy. The data from these experiments provide new insights into how stresses evolve at the crystal scale during thermomechanical loading and complement the development of high-fidelity material models.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Low-temperature Stirling Engine for Geothermal Electricity Generation

Up to 2700 terawatt-hours per year of geothermal electricity generation capacity has been shown to be available within North America, typically with wells drilled into geologically active regions of the earth's crust where this energy is concentrated (Huttrer, 2001). Of this potential, about half is considered to have temperatures high enough for conventional (steam-based) power production, while the other half requires unconventional power conversion approaches, such as organic Rankine cycle systems or Stirling engines. If captured and converted effectively, geothermal power generation could replace up to 100GW of fossil fuel electric power generation, leading to a significant reduction of US power sector emissions. In addition, with the rapid growth of hydro-fracking in oil and gas production, there are smaller-scale distributed power generation opportunities in heated liquids that are co-produced with the main products. Since 2006, Cool Energy, Inc. (CEI) has designed, fabricated and tested four generations of low-temperature (100°C to 300°C) Stirling engine power conversion equipment. The electric power output of these engines has been demonstrated at over 2kWe and over 16% thermal conversion efficiency for an input temperature of 215°C and a rejection temperature of 15°C. Initial pilot units have been shipped to development partners for further testing and validation, and significantly larger engines (20+ kWe) have been shown to be feasible and conceptually designed. Originally intended for waste heat recovery (WHR) applications, these engines are easily adaptable to geothermal heat sources, as the heat supply temperatures are similar. Both the current and the 20+ kWe designs use novel approaches of self-lubricating, low-wear-rate bearing surfaces, non-metallic regenerators, and high-effectiveness heat exchangers. By extending CEI's current 3 kWe SolarHeart® Engine into the tens of kWe range, many additional applications are possible, as one 20 kWe design produces nearly seven times the power output of the 3 kWe unit but at only 2.5 times the estimated fabrication cost. Phase I of the proposed SBIR program will therefore study the feasibility of generating electricity with one or more 20 kWe or larger Stirling engines, powered by geothermal heat produced by current and possibly some forward-looking borehole extraction methods, and from producing oil and gas wells. The feasibility study will include full analysis of the thermodynamic and heat transfer processes within the engine (necessary to produce optimum theoretical designs and performance maps), the cost of pumping the geothermal heat recovery fluid, and how the system tradeoffs impact the overall system economics. The goal is a geothermal system design that could be demonstrated during a Phase II follow-on program at a field test site.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

IDC Re-Engineering Phase 2 Iteration E2 Use Case Realizations

This architecturally significant use case describes how the System acquires meteorological data to build atmospheric models used in automatic and interactive processing of infrasound data. The System requests the latest available high-resolution global meteorological data from external data centers and puts it into the correct formats for generation of infrasound propagation models. The system moves the meteorological data from Data Acquisition Partition to the Data Processing Partition and stores the meteorological data. The System builds a new atmospheric model based on the meteorological data. This use case is architecturally significant because it describes acquiring meteorological data from various sources and creating dynamic atmospheric transmission model to support the prediction of infrasonic signal detection

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

Engineering Spin-Orbit Interaction in Silicon

There has been much interest in leveraging the topological order of materials for quantum information processing. Among the various solid-state systems, one-dimensional topological superconductors made out of strongly spin-orbit-coupled nanowires have been shown to be the most promising material platform. In this project, we investigated the feasibility of turning silicon, which is a non-topological semiconductor and has weak spin-orbit coupling, into a one-dimensional topological superconductor. Our theoretical analysis showed that it is indeed possible to create a sizable effective spin-orbit gap in the energy spectrum of a ballistic one-dimensional electron channel in silicon with the help of nano-magnet arrays. Experimentally, we developed magnetic materials needed for fabricating such nano-magnets, characterized the magnetic behavior at low temperatures, and successfully demonstrated the required magnetization configuration for opening the spin-orbit gap. Our results pave the way toward a practical topological quantum computing platform using silicon, one of the most technologically mature electronic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2016

IDC Re-Engineering Phase 2 Iteration E2 Use Case Realizations

This architecturally significant use case describes how the System acquires meteorological data to build atmospheric models used in automatic and interactive processing of infrasound data. The System requests the latest available high-resolution global meteorological data from external data centers and puts it into the correct formats for generation of infrasound propagation models. The system moves the meteorological data from Data Acquisition Partition to the Data Processing Partition and stores the meteorological data. The System builds a new atmospheric model based on the meteorological data. This use case is architecturally significant because it describes acquiring meteorological data from various sources and creating dynamic atmospheric transmission model to support the prediction of infrasonic signal detections.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Analytics for Metabolic Engineering

Realizing the promise of metabolic engineering has been slowed by challenges related to moving beyond proof-of-concept examples to robust and economically viable systems. Key to advancing metabolic engineering beyond trial-and-error research is access to parts with well-defined performance metrics that can be readily applied in vastly different contexts with predictable effects. As the field now stands, research depends greatly on analytical tools that assay target molecules, transcripts, proteins, and metabolites across different hosts and pathways. Screening technologies yield specific information for many thousands of strain variants, while deep omics analysis provides a systems-level view of the cell factory. Efforts focused on a combination of these analyses yield quantitative information of dynamic processes between parts and the host chassis that drive the next engineering steps. Overall, the data generated from these types of assays aid better decision-making at the design and strain construction stages to speed progress in metabolic engineering research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Hybrid magnonics: Physics, circuits, and applications for coherent information processing

Hybrid dynamic systems have recently gained interest with respect to both fundamental physics and device applications, particularly with their potential for coherent information processing. In this work, we will focus on the recent rapid developments of magnon-based hybrid systems, which seek to combine magnonic excitations with diverse excitations for transformative applications in devices, circuits, and information processing. Key to their promising potentials is that magnons are highly tunable excitations and can be easily engineered to couple with various dynamic media and platforms. The capability of reaching strong coupling with many different excitations has positioned magnons well for studying solid-state coherent dynamics and exploiting unique functionality. In addition, with their gigahertz frequency bandwidth and the ease of fabrication and miniaturization, magnonic devices and systems can be conveniently integrated into microwave circuits for mimicking a broad range of device concepts that have been applied in microwave electronics, photonics, and quantum information. We will discuss a few potential directions for advancing magnon hybrid systems, including on-chip geometry, novel coherent magnonic functionality, and coherent transduction between different platforms. As a future outlook, we will discuss the opportunities and challenges of magnonic hybrid systems for their applications in quantum information and magnonic logic.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Multidisciplinary design optimization in Architecture, Engineering, and Construction: a detailed review and call for collaboration

The design of buildings has become a complex and multidisciplinary problem involving multiple conflicting objectives as architects and designers address competing technical, economic, environmental, and societal concerns. This has been driving research in Architecture, Engineering, and Construction (AEC) toward rigorous multidisciplinary decision-making frameworks that generate and evaluate numerous design alternatives using multi-objective optimization in concert with simulation and analysis models of varying fidelity and computational expense. While such frameworks are well known and widely employed in the aerospace and systems engineering domains, efforts by design professionals and researchers in the AEC field are scattered at best. In this paper, we provide a detailed review of recent developments in optimization frameworks in the AEC field and subsequently highlight how such developments are largely compartmentalized into separate domains such as structural, energy, daylighting, and other performance factors. Herein, we further discuss the technical challenges involved in concurrent coupled multidisciplinary design optimization (MDO) in the AEC field such as interoperability issues between Building Information Modeling (BIM) environments, analysis/simulation tools, and optimization frameworks. We conclude by outlining research needed for more unified modeling and simulation-based optimization frameworks to aid in complex and multidisciplinary building design processes. We also highlight the need for the identification and development of multi-fidelity simulation tools for use across multiple design phases. As such, this paper contributes a novel roadmap to leverage aerospace and systems engineering research in MDO into the field of AEC, along with a call for researchers in the MDO community to seek collaborations in AEC field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

DS-TIDE: Harnessing Dynamical Systems for Efficient Time-Independent Differential Equation Solving

Time-Independent Differential Equations (TIDEs) are central to modeling equilibrium behavior across a wide range of scientific and engineering domains, from electrostatics to porous media flow. Conventional numerical solvers offer reliable solutions but incur significant computational costs due to fine-grained discretization and iterative procedures. Machine learning-based approaches address this by replacing iterative solving processes with one-time inference; however, their sophisticated models require extensive training resources that often exceed those of traditional solvers. Consequently, designing a TIDE solver that achieves high accuracy, broad applicability, and exceptional computational efficiency remains a fundamental challenge. In this paper, we propose DS-TIDE, a novel hardware solver that is inspired by, and subsequently leverages, the intrinsic connection between Dynamical Systems (DS) and Differential Equations (DEs) to efficiently and accurately solve TIDEs. DS-TIDE employs a CMOS-compatible DS-based processor, whose physical states evolve under carefully designed DE-driven dynamics and naturally converge to equilibrium -- the solution of the target TIDE -- within ~1µs on a ~1-watt DS-TIDE processor. To enhance expressivity, DS-TIDE incorporates Heterogeneous Dynamics with Temporal Layering (HDTL), which solves TIDEs through a three-stage DS evolution -- conditioning, solving, and decoding -- each governed by specialized dynamics. The entire evolution process is analogous to an infinitely deep neural network temporally unrolled, offering the system the capability of representing complex equations. Furthermore, DS-TIDE is equipped with an on-device DS-DE Auto-Alignment mechanism that dynamically adapts intrinsic hardware dynamics within milliseconds, effectively aligning the system’s dynamics to diverse target DEs. Experimental results across TIDEs from a wide range of scientific and engineering domains demonstrate that DS-TIDE achieves ~10^3× speedup, ~10^5× energy savings, and competitive or superior accuracy compared to state-of-the-art numerical and ML-based solvers.

Liu, Chuan↗
DOE OSTI2019

110th Anniversary: Bridging the Time and Length Scales of Process Systems with Data

Here we report on the role of data as a "bridge" connecting the different time/length scales of chemical processes in mathematical modeling and multi-scale, integrated decision making. We argue that this is a fitting role of "big data" in the chemical industry, an area that comprises complicated yet deterministic physical systems. Such systems can be described using physical and chemical laws that are generally well-understood. Accordingly, data and data analysis are less likely to provide the unexpected and/or surprising insights that they have generated in other sectors (e.g., the transactional economy, social sciences). Nevertheless, historical operating data (which are often plentiful and available at little cost) can be converted to very useful information for multi-scale mathematical modeling of chemical processes. Several examples of integration are provided, mapped on the continuum of time and length scales of process systems. Current research challenges and potential directions for future work are discussed.

42 ENGINEERING↗
DOE OSTI2015

The history and evolution of optically accessible research engines and their impact on our understanding of engine combustion

The development and application of optically accessible engines to further our understanding of in-cylinder combustion processes is reviewed, spanning early efforts in simplified engines to the more recent development of high-pressure, high-speed engines that retain the geometric complexities of modern production engines. Limitations of these engines with respect to the reproduction of realistic metal test engine characteristics and performance are identified, as well as methods that have been used to overcome these limitations. Finally, the role of the work performed in these engines on clarifying the fundamental physical processes governing the combustion process and on laying the foundation for predictive engine simulation is summarized.

33 ADVANCED PROPULSION SYSTEMS↗