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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development and assessment of a model predictive controller enabling anticipatory control strategies for a heat-pipe system

To support the reliable and resilient operation of modular reactors and microreactors, anticipatory control strategies have been proposed for achieving faster-than-real-time predictions and decision-making capabilities in anticipation of potential anomalies, including setpoint changes and cyber incidents. Here this work presents how anticipatory control strategies can be implemented via model predictive control (MPC) of a single heat pipe’s temperature. Considering the uncertainty in developing and applying MPC, this work evaluates MPC performance given three different model forms: a linear response surface model, an artificial neural network (ANN), and an autoregressive model with exogenous input (ARX). This work also evaluates the impacts of different input biases and variance on MPC performance in order to account for potential sensor reading variations due to cyber incidents. We observe that nonparametric models such as the ANN and ARX result in more fluctuated control actions compared to the MPC applied to the linear response surface model. However, when the cyber incidents are of a large magnitude, the linear response surface model produces smaller feasible regions than the nonparametric models under identical constraints.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Uncertainty-Aware, Structure-Preserving Machine Learning Approach for Domain Shift Detection From Nonlinear Dynamic Responses of Structural Systems

Complex structural systems deployed for aerospace, civil, or mechanical applications must operate reliably under varying operational conditions. Structural health monitoring (SHM) systems help ensure the reliability of these systems by providing continuous monitoring of the state of the structure. SHM relies on synthesizing measured data with a predictive model to make informed decisions about structural states. However, these models—which may be thought of as a form of a digital twin—need to be updated continuously as structural changes (e.g., due to damage) arise. We propose an uncertainty-aware machine learning model that enforces distance preservation of the original input state space and then encodes a distance-aware mechanism via a Gaussian process (GP) kernel. The proposed approach leverages the spectral-normalized neural GP algorithm to combine the flexibility of neural networks with the advantages of GP, subjected to structure-preserving constraints, to produce an uncertainty-aware model. This model is used to detect domain shift due to structural changes that cannot be observed directly because they may be spatially isolated (e.g., inside a joint or localized damage). This work leverages detection theory to detect domain shift systematically given statistical features of the prediction variance produced by the model. The proposed approach is demonstrated on a nonlinear structure being subjected to damage conditions. In conclusion, it is shown that the proposed approach is able to rely on distances of the transformed input state space to predict increased variance in shifted domains while being robust to normative changes.

Algorithms↗
DOE OSTI2018

DNA Strand Buffers

A buffer reaction actively resists changes to the concentration of a chemical species. Typically, buffering reactions have only been able to regulate the concentration of hydronium (i.e., pH) and other ions. In this work, we develop a new class of buffers that regulate the concentrations of short sequences of DNA (i.e., oligonucleotides). A buffer’s behavior is determined by its set point concentration, capacity to resist disturbances, and response time after a disturbance. We provide simple mathematical formulas for selecting rate constants to tune each of these properties and show how to design DNA sequences and concentrations to implement the desired rate constants. We demonstrate several oligonucleotide buffers that maintain oligonucleotide set point concentrations between 10 and 80 nM in the presence of disturbances of 50 to 500 nM, with response times of less than 10 min to 1.5 h. Multiple buffers can regulate different sequences of DNA in parallel without crosstalk. Oligonucleotide buffers could stabilize and restore reactant concentrations in DNA circuits or in self-assembly processes, allowing such systems to operate reliably for extended durations. These buffers might also be coupled to other reactions to buffer molecules other than DNA. In general, an oligonucleotide buffer can be viewed as a chemical “battery” that maintains the total chemical potential of a buffered species in a closed system.

Biopolymers↗
DOE OSTI2026

The Heterogeneous Integration of Electronic Components

Heterogeneous integration (HI) of electronics components is broadly recognized as a powerful and crucial enabler for the continued growth of computing and communication. From 2010 onwards, the value of HI is increasingly visible in the advanced packaging used in artificial intelligence, high-performance computing, smartphones and communications product implementations. In this Perspective, we argue that HI is crucial to semiconductors and more broadly to the continued evolution of computing and communications. We use leading-edge advanced packaging examples to represent the value, advancements and opportunities for HI. To succeed, it is critical to develop comprehensive HI roadmaps that inform collaborations across the design, manufacturing and reliability spectrum between systems architects, packaging and semiconductor technologists to common goals. Although this article does not provide a full roadmap, we instead detail additional parameters for artificial intelligence, smartphone and other cellular communication devices, and their constituent building blocks including interconnects, power electronics, photonics, thermal management, reliability, modelling and co-design, to foster greater collaboration opportunities among academia, research laboratories and industry.

42 ENGINEERING↗
DOE OSTI2021

A Statistics-Based Threshold for the RMS-Energy Oscillation Detector

System operators and reliability coordinators currently rely on extensive baselining studies to set thresholds for their oscillation detectors. The resulting thresholds are based largely on engineering judgment and may vary significantly between organizations. In this paper, statistical distribution theory is used to derive a detection threshold for the widely deployed root-mean-square (RMS)-energy detector. This expression provides a theoretical basis for the detector's configuration, simplifies the process of selecting the threshold, and enables improved consistency among organizations that need to coordinate during system-wide events. Three methods for calculating the threshold using synchrophasor measurements are also proposed. These methods ensure that the threshold can be calculated reliably for various applications. Tests with simulated and field-measured data demonstrate that the statistics-based threshold provides consistent detection of grid disturbances while maintaining a low probability of false alarm.

Follum, James D.↗
DOE OSTI2017

Flywheel Energy Storage - Dynamic Modeling

A flywheel energy storage systems (FESS) is suitable for high-power, low-energy content to deliver or absorb power in surges. This type of application is very suitable for frequency regulation in an electric grid. In addition, a modern FESS is built as a high-efficiency, high-speed motor/generator drive system that employs modern power electronics, therefore, the power quality of the grid-connected output is excellent. In addition, a FESS is very valuable to delivering ancillary services to the grid, and it can contribute reactive power compensation. Thus, a FESS can maintain high reliability in power systems by providing ride-through capability to the power system area while the rest of the generating fleet, which has a slower response in the power system, performs primary and secondary frequency response to the grid. A FESS has several advantages compared to a chemical-based energy storage (CBES) system, namely: it has high energy density and durability, and it can be cycled frequently without impacting performance. The response of FESS is faster than that of a CBES. Also, unlike some CBES, FESS has the same performance regardless of the number of cycles of charging/discharging performed throughout its lifetime.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

A Catalog of Wide Binary and Multiple Systems of Bright Stars from Gaia-DR2 and the Virtual Observatory

Binary and multiple stars have long provided an effective empirical method of testing stellar formation and evolution theories. In particular, the existence of wide binary systems (separations >20,000 au) is particularly challenging to binary formation models as their physical separations are beyond the typical size of a collapsing cloud core (~5000–10,000 au). We mined the recently published Gaia-DR2 catalog to identify bright comoving systems in the five-dimensional space (sky position, parallax, and proper motion). We identified 3741 comoving binary and multiple stellar candidate systems, out of which 575 have compatible radial velocities for all the members of the system. The candidate systems have separations between ~400 and 500,000 au. We used the analysis tools of the Virtual Observatory to characterize the comoving system members and to assess their reliability. The comparison with previous comoving systems catalogs obtained from TGAS showed that these catalogs contain a large number of false systems. In addition, we were not able to confirm the ultra-wide binary population presented in these catalogs. The robustness of our methodology is demonstrated by the identification of well known comoving star clusters and by the low contamination rate for comoving binary systems with projected physical separations <50,000 au. These last constitute a reliable sample for further studies. The catalog is available online at the Spanish Virtual Observatory portal (http://svo2.cab.inta-csic.es/vocats/v2/comovingGaiaDR2/).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Frontier system-on-chip (SoC) technology for microwave diagnostics (invited)

The next generation of fusion reactors, exemplified by projects such as the Demonstration Power Plant following the International Thermonuclear Experimental Reactor, faces the monumental challenge of proving the viability of generating electricity through thermonuclear fusion. This pursuit introduces heightened complexities in diagnostic methodologies, particularly in microwave-based diagnostics. The increased neutron fluence necessitates significant reductions in vessel penetrations and the elimination of internal diagnostics, posing substantial challenges. SoC technology offers a promising solution by enabling the miniaturization, modularization, integration, and enhancing the reliability of microwave systems. After seven years of research, our team successfully pioneered the V- and W-band system-on-chip approach, leading to the development of active transmitters and passive receiver modules applied in practical settings, notably within the DIII-D tokamak project. Arrays of these modules have supported microwave imaging diagnostics. New physics measurement results from the Electron Cyclotron Emission Imaging system on DIII-D provide compelling evidence of improved diagnostics following the adoption of SoC technology. Furthermore, we achieved a breakthrough in developing an F-band SoC, advancing higher frequency capabilities for fusion devices. These achievements represent a significant leap forward in fusion diagnostic technology, marking substantial progress toward establishing reliable and efficient plasma diagnostics for future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Demonstrating Advanced Nuclear Energy Solutions for Net Zero

Background/Objectives. The aggressive goals being set by nation states, communities, and private industry for decarbonization of grid electricity, industrial heat sources, and transportation around the world are imperative to mitigating the devastating effects that we are seeing from climate change. Although many of these goals focus on accomplishments by 2035 or 2050, the decisions that we make today won’t just impact the landscape of energy systems for the next 20 or 30 years—they will shape the world’s environment for centuries to come. That means that we can’t just focus on technologies that will get us to 2050, but technologies that will withstand our energy demands over that long-ranging future. Success will require us to utilize all of the clean energy resources that we have available to meet demands for electricity, heat, and steam, and we will need energy carriers such as hydrogen that do not emit additional greenhouse gases at the point of use. Nuclear energy, ranging from technologies in service today to advanced, higher temperature and modular systems that will be in service this decade, will provide a robust complement to renewable energy resources that operate variably. Researchers across the U.S. Department of Energy laboratory complex are working to advance multiple aspects of these clean energy solutions, with many focusing on integrated energy system solutions that leverage all available clean energy assets to meet wide-ranging energy demands. Approach/Activities. Nuclear energy is a proven, zero-emission option during operation that can provide consistent, dispatchable power to meet electricity demands while also providing high-quality heat that can meet energy demands beyond the electricity sector. Energy system design should seek to maximize these assets. As a dispatchable energy source with a small land utilization footprint, nuclear energy can be collocated with renewable resources, and the smaller systems that will be deployed this decade (ranging from a few megawatts to hundreds of megawatts) can be installed right where that energy is needed. Integrated nuclear and renewable systems will enhance power grid reliability and resilience, and they will help stabilize the grid through their increasingly flexible operation. Licensing, installation, and broad adoption of these advanced nuclear energy systems are expected to progress significantly in the 2020s, but this may be longer than desired by some stakeholders wishing to implement impactful clean energy decisions today. However, one must recall that nuclear energy systems will operate for 80 or more years, as is being demonstrated by current fleet nuclear systems. The nuclear community is extremely thorough in reviewing these systems with regard to safety and security; these efforts ensure that the deployed systems will continue to provide reliable, resilient energy over that operational lifetime. That investment of time up front will ensure that we can support energy demands over the centuries to come. While advanced nuclear technologies move through this process, communities and private industry may choose to install renewable generation systems that can later be coupled to the complementary nuclear systems as they become available—thus moving closer to the net zero goals in the near term. Choosing technologies and deployment configurations that allow small modular nuclear powerhouses to be added to these “energy parks” as they become available will ensure that advanced technologies can be readily adopted to support growing demands for clean energy. Results/Lessons Learned. The primary focus of integrated energy systems (IES) research is to assess the technical and economic potential of novel multi-input, multioutput solutions that are expected to enhance energy system flexibility, reliability, and resilience as we pursue a clean energy transition. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. In early FY23 Idaho National Laboratory (INL) will commission thermal energy generation systems that emulate nuclear fission energy input using electric heating and will allow for integrated system testing with thermal energy storage, hydrogen production via high temperature electrolysis (HTE), and power systems hardware to demonstrate operation of a clean energy park within a microgrid or larger grid infrastructure, supporting up to 450 kW of heat input via electric heating and demonstrating operation of HTE systems at the multi-hundred kW scale. This presentation will highlight the wide array of RD&D being conducted at INL and partner laboratories to develop and deploy nuclear and renewable-based IES that will be key to achieving our net zero goals, including both computational and experimental demonstrations. By working with key collaborators in industry, analytical st

08 HYDROGEN↗
DOE OSTI2022

Techno-Economic Analysis of Natural Gas Fuel Cell Plant Configurations

The United States (U.S.) Department of Energy (DOE) Office of Fossil Energy and Carbon Management (FECM) and the National Energy Technology Laboratory (NETL) have been pursuing the development of solid oxide fuel cell (SOFC) technology to enable future power generation systems that are consistent with the cornerstones of the DOE mission—to ensure America’s security and prosperity by addressing its energy and environmental challenges through transformative science and technology solutions. The U.S. DOE FECM SOFC Program is currently focused on the development of low-cost, highly efficient, and reliable SOFC power systems. NETL’s SOFC technology development roadmap is aligned with near-term market opportunities in the distributed generation sector to validate and advance the technology while paving the way for utility-scale (> 50 MW) natural gas and coal-derived synthesis gas-fueled applications via progressively larger system demonstrations. The present study represents a part of a series of system evaluations being developed at NETL to aid in prioritizing technological advances along research pathways to the realization of utility-scale SOFC systems, a transformational goal of the fuel cell program. In particular, the system performance of utility-scale natural gas fuel cell (NGFC) systems with and without carbon dioxide (CO 2 ) capture is presented. The objective of the study is to provide targeted research and development (R&D) guidance to the FECM SOFC Program and SOFC commercial developers to accelerate technology deployment.

03 NATURAL GAS↗
DOE OSTI2014

Capturing Dynamics in the Power Grid: Formulation of Dynamic State Estimation through Data Assimilation

With the increasing complexity resulting from uncertainties and stochastic variations introduced by intermittent renewable energy sources, responsive loads, mobile consumption of plug-in vehicles, and new market designs, more and more dynamic behaviors are observed in everyday power system operation. To operate a power system efficiently and reliably, it is critical to adopt a dynamic paradigm so that effective control actions can be taken in time. The dynamic paradigm needs to include three fundamental components: dynamic state estimation; look-ahead dynamic simulation; and dynamic contingency analysis (Figure 1). These three components answer three basic questions: where the system is; where the system is going; and how secure the system is against accidents. The dynamic state estimation provides a solid cornerstone to support the other 2 components and is the focus of this study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Performance Evaluation of High-Temperature Ultrasonic Communication System

Ultrasonic communication is a technique that allows transmitting information through a solid material such as tubes or bars using high-frequency elastic waves. The communication channels often extend into a high-temperature range in the field of power, oil, or nuclear industry. When the temperature is taken into consideration, the ultrasonic wave propagation through the solid channel is complex and unpredictable. It is necessary to study the influence of temperature on the ultrasonic guided wave to improve ultrasonic communication. In this study, a temperature control system is assembled to adjust the temperature of a steel pipe channel ranging from room temperature to 150 degrees C. The temperature performance evaluation is conducted to estimate the signal-to-noise ratio (SNR) and bit error rate (BER) of transferring the ultrasonic signal. The work aims to develop a reliable ultrasonic communication system in a high-temperature environment. The system temperature can be maintained at 150 degrees C and the LiNbO3 transducers are used as transmitters and receivers. No power amplifier is used in the communication system. The high-temperature ultrasonic communication system (HT-UCS) is feasible at 150 degrees C and can achieve a bit rate of 10 kbps without any error.

HT-UCS↗
DOE OSTI2016

Smart Novel Semi-Active Tuned Mass Damper for Fixed-Bottom and Floating Offshore Wind (Paper)

The intention of this paper is to present the results of a novel smart semi-active tuned mass damper (SA-TMD), which mitigates unwanted loads for both fixed-bottom and floating offshore wind systems. The paper will focus on the most challenging water depths for both fixed-bottom and floating systems. A close to 38m Monopile and 55m Tension Leg Platform (TLP) will be considered. A technical development and trade-off analysis will be presented comparing the new system with existing passive non-linear TMD (N-TMD) technology and semi-active. TheSATMD works passively and activates itself with low power source under unwanted dynamic loading in less than 60msec. It is composed of both variable stiffness and damping elements coupled to a central pendulum mass. The analysis has been done numerically in both FAST(NREL) and Orcaflex (Orcina), and integrated in the Wind Turbine system employing CAD/CAE. The results of this work will pave the way for experimental testing to complete the technology qualification process. The load reductions under extreme and fatigue cases reach up significant levels at tower base, consequently reducing LCOE for fixed-bottom to floating wind solutions. The nacelle acceleration is reduced substantially under severe random wind and sea states, reducing the risks of failure of electromechanical components and blades at the rotor nacelle assembly. The SA-TMD system isa new technology that has not been applied previously in wind solutions. Structural damping devices aim to increase offshore wind turbine system robustness and reliability, which eases multiple substructures installations and global stability.

17 WIND ENERGY↗
DOE OSTI2013

Light Water Reactor Sustainability Program: Advanced Instrumentation, Information, and Control Systems Technologies Technical Program Plan for 2013

Reliable instrumentation, information, and control (II&C) systems technologies are essential to ensuring safe and efficient operation of the U.S. light water reactor (LWR) fleet. These technologies affect every aspect of nuclear power plant (NPP) and balance-of-plant operations. In 1997, the National Research Council conducted a study concerning the challenges involved in modernizing existing analog-based instrumentation and controls with digital instrumentation and control systems in NPPs. Their findings identified the need for new II&C technology integration. The objective of these efforts is to develop, demonstrate, and support deployment of new digital II&C technologies for nuclear process control, enhance worker performance, and provide enhanced monitoring capabilities to ensure the continued safe, reliable, and economic operation of the nation’s NPPs. Digital II&C technologies are deployed in a number of power generation settings worldwide. Current instrumentation and human-machine interfaces in the nuclear power sector employ analog technologies. In other power generation sectors, analog technologies have largely been replaced with digital technologies. This is in part due to the manufacturing and product support base transitioning to these newer technologies. It also accompanies the transition of education curricula for I&C engineers to digital technologies. Consequently, product manufacturers refer to analog I&C as having reached the end of its useful service life. Although considered obsolete by other industries, analog I&C continues to function reliably, though spare and replacement parts are becoming increasingly scarce as is the workforce that is familiar with and able to maintain it. Analog I&C was also the predominant means used for process control in an era when human labor was more affordable, and maintaining an I&C technology base through a larger workforce conducting frequent rounds for surveillances, inspections, and tests was accepted in the nuclear power generation business model. Today’s power generation business climate is much different and II&C technologies are needed in the long run that are more highly automated and require less cost to operate and maintain, are as highly reliable as those used today, and will be familiar to a future work force. They should also enable performance gains for the utility so that they are not merely a sunken cost, as this would weigh heavily on the balance sheet at a time of particularly high cost competitiveness in electricity markets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Chapter 7: Predictive Analytics in Future Power Systems: A Panorama and State-of-the-Art of Deep Learning Applications

The challenges surrounding the optimal operation of power systems are growing in various dimensions, due in part to increasingly distributed energy resources and a progression towards large-scale transportation electrification. Currently, the increasing uncertainties associated with both renewable energy generation and demand are largely being managed by increasing operational reserves - potentially at the cost of suboptimal economic conditions - in order to maintain the reliability of the system. This chapter looks at the big picture role of forecasting in power systems from generation to consumption and provides a comprehensive review of traditional approaches for forecasting generation and load in various contexts. This chapter then takes a deep dive into the state-of-the-art machine learning and deep learning approaches for power systems forecasting. Furthermore, a case study of multi-time-horizon solar irradiance forecasting using deep learning is discussed in detail. Smart grids form the backbone of the future interdependent networks. For addressing the challenges associated with the operations of smart grid, development and wide adoption of machine learning and deep learning algorithms capable of producing better forecasting accuracies is urgently needed. Along with exploring the implementation and benefits of these approaches, this chapter also considers the strengths and limitations of deep learning algorithms for power systems forecasting applications. This chapter, thus, provides a panoramic view of state-of-the-art of predictive analytics in power systems in the context of future smart grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Effect of ammoniacal nitrogen on one-stage and two-stage anaerobic digestion of food waste

Highlights: • Almost 100% of the biomethane potential of food waste was recovered during AD in a two-stage CSTR. • Recirculation of the liquid fraction of the digestate provided the necessary buffer in the AD reactors. • A higher OLR (0.9 gVS/L·d) led to higher accumulation of TAN, which caused more toxicity. • A two-stage reactor is more sensitive to elevated concentrations of ammonia. • The IC{sub 50} of TAN for the AD of food waste amounts to 3.8 g/L. - Abstract: This research compares the operation of one-stage and two-stage anaerobic continuously stirred tank reactor (CSTR) systems fed semi-continuously with food waste. The main purpose was to investigate the effects of ammoniacal nitrogen on the anaerobic digestion process. The two-stage system gave more reliable operation compared to one-stage due to: (i) a better pH self-adjusting capacity; (ii) a higher resistance to organic loading shocks; and (iii) a higher conversion rate of organic substrate to biomethane. Also a small amount of biohydrogen was detected from the first stage of the two-stage reactor making this system attractive for biohythane production. As the digestate contains ammoniacal nitrogen, re-circulating it provided the necessary alkalinity in the systems, thus preventing an eventual failure by volatile fatty acids (VFA) accumulation. However, re-circulation also resulted in an ammonium accumulation, yielding a lower biomethane production. Based on the batch experimental results the 50% inhibitory concentration of total ammoniacal nitrogen on the methanogenic activities was calculated as 3.8 g/L, corresponding to 146 mg/L free ammonia for the inoculum used for this research. The two-stage system was affected by the inhibition more than the one-stage system, as it requires less alkalinity and the physically separated methanogens are more sensitive to inhibitory factors, such as ammonium and propionic acid.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Evaluating Demand Response Impacts on Capacity Credit of Renewable Distributed Generation in Smart Distribution Systems

Environmental concerns and depletion of traditional energy lead to the booming development of renewable distributed generation (RDG) in the past decade. However, due to intermittent nature of renewable energy sources, to what extent RDG could provide capacity to power systems becomes a critical issue to the utility company when implementing long-term system strategic (generation expansion) planning. On the other hand, in a smart-grid frame, the popularization of different varieties of demand-side resources enables the system to operate at more flexible modes ever before. The potential variability in load demand not only introduces additional dynamics and uncertainties to the system, but could also affect the reliability benefits of RDG. Therefore, in practice, to effectively estimate the reliability value of RDG in power systems, the potential interaction between generation- and demand-side must be properly captured. In this paper, a study to assess the capacity credit (CC) of RDG in a context of distributed generation system is performed with consideration of the impacts of demand response (DR). A compound reliability model for DR is presented, which considers the uncertainties involved in both instant response and follow-on load recovery processes. On this basis, an assessment framework for the CC of RDG based on sequential Monte Carlo simulation is developed by which the inter-temporal characteristics of DR resources can be fully captured. The numerical study is implemented based on the IEEE-38 bus test case. The calculation results demonstrate that the CC of RDG would depend on a variety of factors, including penetration level, responsiveness of load demand and the correlations between RDG and DR availability. Also, it is shown that accounting for the underlying effect of DR is of absolute importance, otherwise the CC of RDG might be estimated erroneously in real practices.

capacity credit↗