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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Static and dynamic modeling of steam integration for a NuScale small modular reactor and pulp and paper mill coupling for carbon-neutral manufacturing

Small modular reactors (SMRs) are reactor designs producing less than 300 MWe and are generally planned for deployment as multimodule nuclear power plants. The possibility of factory-manufactured, flexibly sized plants expands the opportunities for nuclear power to different communities and industries, including manufacturing plants that currently utilize fossil fuels to produce both steam and electricity. This paper examines the feasibility of coupling a NuScale SMR with a midsize pulp and paper mill in the Southeastern United States. A steady-state mill model was developed in Aspen HYSYS, based on real data from the operation of the mill, and modified it to include the SMR while maintaining steam quality requirements and making as few changes as possible to existing equipment. Dynamic plant models were also developed Dymola to demonstrate possible plant conditions, using three configurations. Preliminary results suggest that, while SMR coupling is physically feasible, its economic feasibility is limited by the differences in steam and electricity demands. Because of limitations in the amount of steam the mill can take from the SMR, sizing the SMR for the plant’s steam demand may result in an electricity deficit, or vice versa. Furthermore, dynamic analyses show that the addition of a thermal storage system could reduce such deficits, but this entails its own challenges. Each plant must determine the best configuration and control scheme for itself, based on its electricity and heat needs, including the peak duration and intensity for both. Ultimately, an implementation of SMRs with manufacturing processes would benefit from partnering with a local utility to purchase excess electricity generated by the SMR. This will help manufacturing facilities meet their environmental and cost-savings goals, in addition to meeting the need for cost-effective baseload power across the United States.

03 NATURAL GAS↗
DOE OSTI2020

Modeling and Harmonic Stability of MMC-HVDC With Passive Circulating Current Filters

A modular multilevel converter (MMC) is an emerging converter technology widely used in wind power applications using high-voltage direct current (HVDC) transmission, and it has been largely investigated in medium-voltage solar harvesting as well as electric motor drives. Different from studies dealing with active circulating current control loops, this paper focuses on impedance modeling and harmonic stability studies for MMCs with passive circulating current filters (PCCFs). A power stage circuit including a PCCF is transformed and remodeled to obtain small-signal formulations. This transformation leads to additional high-order matrix computing complexity due to the added impedance subnetwork matrix from the PCCF as well as relevant crossed-frequency impacts. To simplify the computational burden, the proposed model aims to solve one arm equation instead of all six MMC arm equations. To achieve this result, additional challenges occur when the MMC is connected to a renewable energy source instead of the grid voltage, where low-level zero-sequence components might exist in the neutral point of three phases, especially in the case of no integrated advanced modular voltage balancing control, which prevents computational simplification. To overcome this challenge, further impedance matrix adjustments are conducted in this paper to theoretically suppress the impact of zero-sequence harmonics when obtaining small-signal impedance, taking into account the frequency coupling effect. Finally, simulations are carried out to validate the developed impedance model under different operating scenarios. Harmonic stability case studies of MMCs with PCCFs connected to renewable energy current sources are also presented, where frequency-domain stability analyses based on Bode diagrams are compared to time-domain simulation waveforms and FFTs, which validate the effectiveness of the proposed impedance model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Quantum efficiency of InGaN–GaN multi-quantum well solar cells: Experimental characterization and modeling

InGaN-based multi-quantum well (MQW) solar cells are promising devices for photovoltaics (e.g., for tandem solar cells and concentrator systems), space applications, and wireless power transfer. In order to improve the efficiency of these devices, the factors limiting their efficiency and stability must be investigated in detail. Due to the complexity of a MQW structure, compared with a simple pn junction, modeling the spectral response of these solar cells is not straightforward, and ad hoc methodologies must be implemented. In this paper, we propose a model, based on material parameters and closed-formula equations, that describes the shape of the quantum efficiency of InGaN/GaN MQW solar cells, by taking into account the layer thickness, the temperature dependence of the absorption coefficient, and quantum confinement effects. We demonstrate (i) that the proposed model can effectively reproduce the spectral response of the cells; in addition, (ii) we prove that the bulk p-GaN layer absorbs radiation, but the carriers photogenerated in this region do not significantly contribute to device current. Finally, we show that (iii) by increasing the temperature, there is a redshift of the absorption edge due to bandgap narrowing, which can be described by Varshni law and is taken into account by the model, and a lowering in the extraction efficiency due to the increase in recombination (mostly Shockley–Read–Hall) inside the quantum wells, which is also visible by decreasing light intensity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

A comparison study on trading behavior and profit distribution in local energy transaction games

With the increasing integration of distributed energy resources, localized peer-to-peer energy transactions are receiving more attention since they could absorb more distributed renewables locally and stabilize the power grid. To better study the trading behavior and provide guidance for a viable local market design, different game-theoretical frameworks including cooperative and non-cooperative games are established and compared here. For the cooperative grand coalition, the maximum social welfare is guaranteed, the Shapley value and bargaining based approaches are implemented for further profit redistribution. It is shown that the asymmetrical bargaining power can be critical in the final payment clearing and it is equivalent to the Shapley value allocation if prosumers bargain based on their marginal contributions. Non-cooperative trading is formulated by using a Stackelberg bilevel model in which the upper level has the privilege in internal price setting. However, system optimum is not obtained due to competition, and the selfish leader could take away 89% of the collective benefit by price-gap based arbitraging. Aiming for a long-lasting trading market, a virtual benevolent leader and a uniform price structure in which purchase price equals selling price are tested. Experimental results indicate that maximum social welfare and a fairer profit allocation can be achieved with a uniform price structure, regardless of the selfish or benevolent attitude.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Resonant torque differential magnetometry with high frequency quartz oscillators

Sensitive magnetometry has been a powerful probe for investigating quantum materials. Extreme conditions, such as sub-kelvin cryogenic temperatures and ultrahigh magnetic fields, demand further durability for sensitive magnetometry. However, significant mechanical vibrations and rapid magnetic field changes give enormous challenges to conventional magnetometry. Here, this article presents a possible solution to this problem by developing a new magnetometry technique using high-frequency quartz oscillators. The technique takes advantage of the symmetry and geometry of mechanical vibration configurations of standard commercially available MHz quartz oscillators, and the setup keeps the high quality factor resonance with the sample mounted on the oscillator. We further demonstrate the sensitivity of the technique using bismuth single crystals and a Fe 0.25 TaS 2 ferromagnetic material. Quantum oscillations are observed in the magnetometry response below 1 T, and the detected oscillation frequency is shown to come from the electron pockets of the bismuth.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Multisource Data Fusion Outage Location in Distribution Systems via Probabilistic Graphical Models

Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) last gasp signals, customer trouble calls, social media messages, weather data, vegetation information, and physical parameters of the network. This is a computationally complex task due to the high dimensionality of data in distribution grids. In this paper, we propose a multi-source data fusion approach to locate outage events in partially observable distribution systems using Bayesian networks (BNs). A novel aspect of the proposed approach is that it takes multi-source evidence and the complex structure of distribution systems into account using a probabilistic graphical method. Our method can radically reduce the computational complexity of outage location inference in high-dimensional spaces. The graphical structure of the proposed BN is established based on the network’s topology and the causal relationship between random variables, such as the states of branches/customers and evidence. Utilizing this graphical model, accurate outage locations are obtained by leveraging a Gibbs sampling (GS) method, to infer the probabilities of de-energization for all branches. Compared with commonly-used exact inference methods that have exponential complexity in the size of the BN, GS quantifies the target conditional probability distributions in a timely manner. As a result, a case study of several real-world distribution systems is presented to validate the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Accelerate microstructure evolution simulation using graph neural networks with adaptive spatiotemporal resolution

Abstract Surrogate models driven by sizeable datasets and scientific machine-learning methods have emerged as an attractive microstructure simulation tool with the potential to deliver predictive microstructure evolution dynamics with huge savings in computational costs. Taking 2D and 3D grain growth simulations as an example, we present a completely overhauled computational framework based on graph neural networks with not only excellent agreement to both the ground truth phase-field methods and theoretical predictions, but enhanced accuracy and efficiency compared to previous works based on convolutional neural networks. These improvements can be attributed to the graph representation, both improved predictive power and a more flexible data structure amenable to adaptive mesh refinement. As the simulated microstructures coarsen, our method can adaptively adopt remeshed grids and larger timesteps to achieve further speedup. The data-to-model pipeline with training procedures together with the source codes are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Comprehensive assessment of deep reinforcement learning approaches for economic dispatch in nuclear-driven microgrids

As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

On the Language of Reliability: A System Engineer Perspective

In its classical definition, risk is defined by three elements: what can go wrong, what are its consequences, and how likely is it to occur? While this definition makes sense in a regulatory-based framework where for the current fleet of operating light water reactors (LWRs), the risks associated with nuclear power plants typically are characterized in terms of core damage and large early release frequency (LERF), this approach does not provide a useful snapshot of the health of the plant from a broader perspective. This is due to the very narrow context in which the term “risk” typically is defined as nuclear safety aspects that have the potential to impact public health. In this paper, we take the viewpoint of nuclear safety that is reflective of the current fleet of operating LWRs for which core damage frequency and LERF are appropriate metrics. For other advanced reactor designs, other more applicable technology neutral metrics of reactor safety metrics would be specified. A possible alternate path would start by redefining the word risk with a broader meaning that better reflects the needs of a system health and asset management decision-making process. Rather than asking how likely an event could occur (in probabilistic terms), we can ask how far this event is from occurring. Our approach starts by defining and quantifying component and system health in terms of a “distance” between its actual and limiting conditions, i.e., determination of the margin that exists between the current state/condition and the state where the component/system is no longer capable of achieving its intended function. A margin is a measure that is more reflective of the current state or performance of a component, and therefore more closely tied to decisions that are made on an ongoing basis. Further, we will show how, given the data available from plant equipment reliability and monitoring (e.g., pump vibration data) and prognostic (e.g., component remaining useful life estimation) data, a margin can be described and determined for all types of maintenance approaches (e.g., corrective or predictive maintenance). We show how classical reliability models (e.g., fault trees) can be used to quantify the system margin provided component margin values. In the approach described in this paper, the propagation of margin values through classical reliability models are not performed using classical probabilistic calculations applied to sets (as performed in a typical plant probabilistic risk assessment). Instead, we show how it is possible to propagate margin values through Boolean logic gates (i.e., AND and OR operators) through distance-based operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Identification of a Delay Attack in the Secondary Control of Grid-Tied Inverter Systems

This work is developed for the identification of a denial-of-service cyberattack on the secondary controller of inverter systems which is connected to the power grid. The identification is made through the dynamic response of the reactive power (Q) of the system under attack. By observing the dynamic characteristic of Q, it is possible to correlate the attack with the nominal response of the hierarchical controller. The article shows that the occurrence of the attack can be identified through a supervisory control that runs a model in parallel. The article argues that after an early identification of the attack, a local controller can take action to mitigate its effects on the system’s response.

Roig Greidanus, Mateo D.↗
DOE OSTI2021

Greenhouse Gas Impact of Algal Bio-Crude Production for a Range of CO2 Supply Scenarios

Refined bio-crude production from hydrothermal liquefaction of algae holds the potential to replace fossil-based conventional liquid fuels. The microalgae act as natural carbon sequestrators by consuming CO2. However, this absorbed CO2 is released to the atmosphere during the combustion of the bio-crude. Thus, the life-cycle greenhouse gas (GHG) emissions of refined bio-crude are linked to the production and supply of the materials involved and the process energy demands. One prominent raw material is CO2, which is the main source of carbon for algae and the subsequent products. The emissions associated with the supply of CO2 can have a considerable impact on the sustainability of the algae-based refined bio-crude production process. Furthermore, the diurnal algae growth cycle complicates the CO2 supply scenarios. Traditionally, studies have relied on CO2 supplied from existing power plants. However, there is potential for building natural gas or biomass-based power plants with the primary aim of supplying CO2 to the biorefinery. Alternately, a direct air capture (DAC) process can extract CO2 directly from the air. The life-cycle GHG emissions associated with the production of refined bio-crude through hydrothermal liquefaction of algae are presented in this study. Different CO2 supply scenarios, including existing fossil fuel power plants and purpose-built CO2 sources, are compared. The integration of the CO2 sources with the algal biorefinery is also presented. The CO2 supply from biomass-based power plants has the highest potential for GHG reduction, with a GHG footprint of −57 g CO2 eq./MJ refined bio-crude. The CO2 supply from the DAC process has a GHG footprint of 49 CO2 eq./MJ refined bio-crude, which is very similar to the scenario that considers the supply of CO2 from an existing conventional natural gas-based plant and takes credit for the carbon utilization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Operating Procedure Extender For Novel Systems

Operating procedures that are used in nuclear power plants are primarily paper. These paper documents are functional for normal operations, but the process has remained relatively unchanged for thirty years. This neglects the digital technology advancements that have been made in that time. There are objectively more efficient ways to present a procedure to an operator using a digital interface. These digital interfaces require structured information to be able to function. This tool takes the procedure that has been written and converts it into the structured from required by the presentation system. This is accomplished through a reliable four phase compilation algorithm.

Lehmer, Jacob P↗
DOE OSTI2021

FY21 NREL Wind Energy Accomplishments and Mid Year Performance Report

This report takes stock of the research NREL conducted on behalf of DOE’s Wind Energy Technologies Office (WETO), other funding and research partners, and the people of the United States during the first half of FY21 (between Oct. 1, 2020 and March 30, 2021). While diverse, all of these efforts shared a common goal to accelerate the deployment of wind energy technologies by helping to improve wind power performance, lower costs, and reduce market barriers to create a more sustainable, secure, and resilient power grid and a cleaner energy future.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2020

Lighting Policy Options to Incentivize the Circular Economy

Energy codes and energy efficiency policy are primed for significant shifts in the coming decade. Consumers are increasingly asking manufacturers to take responsibility for products over the course of the product lifespan, including at end-of-life. Consumer demand for social and environmental responsibility may push new codes and policies that incentivize the circular economy. Within the lighting sector, for example, rapid innovations have created large energy savings but also created a complex waste stream. Traditional energy code approaches to lighting efficiency have considered only lighting power density or energy-based metrics. Shifting codes and policy to consider environmental impacts of the product lifecycle could include circular economy mechanisms such as product deposits or service-based business models. In this paper we consider the possible structures for both codes and policies, and provide an analysis of the merits of each policy using life cycle assessment and sustainability index (SI).

Dillon, Heather↗
DOE OSTI2025

Simulations of the fault current limiting operation of a long-length REBCO CORC ® superconducting cable cooled by helium gas

Conductor-on-round-core (CORC®) cables composed of rare-earth-barium-copper-oxide high-temperature superconducting (HTS) tapes are of great interest for power transmission applications due to their many advantages such as high power density, light weight, and low loss. Closed circulation loops of cryogenic helium gas can be used to cool HTS cables down to low temperatures to significantly improve their current-carrying capacity. Coupled circuit-electromagnetic-thermal finite element simulations implemented in the COMSOL Multiphysics package were developed, validated, and then used for simulating the fault current limiting (FCL) performance and the cooling processes of an 8-layer CORC® cable cooled with a flow of cryogenic helium gas. In the simulations, the temperature dependence of the electrical and thermal properties of all component materials is implemented for improved accuracy. To overcome computational challenges caused by the considerable difference in geometrical scales (i.e. few-µm-thick HTS layers versus 10 m-long HTS cable), the model is divided into two separate simulations. The first simulation is performed on the transverse cross-section of the cable to calculate the electric field, heating power and temperature rise in each component of a CORC® cable during FCL operation. The heating power calculated in the first simulation is transferred to the second model to simulate the cooling of a 10 m-long cable after the fault is cleared. The effect of the helium gas flow rate on the cooling process is also investigated to develop strategic approaches for optimizing cooling systems for HTS cables with FCL capability. The simulations indicated that a 40 ms fault with a voltage drop of 20 V m −1 along the cable can result in a temperature increase from 60 K to about 165 K inside the cable, and it takes about 500 s to cool the cable back to nearly 60 K with a flow of cold helium gas at a rate of 5 g s −1 .

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Pairing instability on a Luttinger surface: A non-Fermi liquid to superconductor transition and its Sachdev-Ye-Kitaev dual

Superconductivity results from an instability of the Fermi surface—contour of poles of the single-particle propagator—to an infinitesimally small attraction between electrons. Here, we instead discuss the analogous problem on a model Luttinger surface, or contour of zeros of the Green function. At zero temperature ($β → \infty$) and a critical interaction strength ($u_{c∞}$) characterized by the residue of self-energy pole, we find that the pair susceptibility diverges leading to a superconducting instability. We evaluate the pair fluctuation partition function and find that the spectral density in the normal state has an interaction-driven, power-law $\frac{1}{\sqrt{ω}}$ type, van-Hove singularity (vHS), indicating non-Fermi liquid (NFL) physics. Crucially, in the strong coupling limit ($βu \gg 1$), the leading-order fluctuation free-energy terms in the normal state of this NFL-SC transition resembles the equivalent [$\textit{O}(1)$] terms of the Sachdev-Ye-Kitaev (SYK) model. This free-energy contribution takes a simple form $–βF = βu_{c∞} – γ \text{ln}(βu_{c∞}$), where $\gamma$ is a constant equal to $\frac{1}{2}$. Weak impurity scattering ($τ \gg β^{–1}$) leaves the low-energy spectral density unaffected but leads to an interaction-driven enhancement of superconductivity. Our results in this work shed light on the role played by order-parameter fluctuations in providing the key missing link between Mott physics and strongly coupled toy models exhibiting gravity duals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Deciphering the archaeological record: Cosmological imprints of nonminimal dark sectors

Many proposals for physics beyond the Standard Model give rise to a dark sector containing many degrees of freedom. In this work, we explore the cosmological implications of the nontrivial dynamics which may arise within such dark sectors, focusing on decay processes which take place entirely among the dark constituents. First, we demonstrate that such decays can leave dramatic imprints on the resulting dark-matter phase-space distribution. In particular, this distribution need not be thermal—it can even be multimodal, exhibiting a nontrivial pattern of peaks and troughs as a function of momentum. We then proceed to show how these features can induce modifications to the matter power spectrum. Finally, we assess the extent to which one can approach the archaeological “inverse” problem of deciphering the properties of an underlying dark sector from the matter power spectrum. Indeed, one of the main results of this paper is a remarkably simple conjectured analytic expression which permits the reconstruction of many of the important features of the dark-matter phase-space distribution directly from the matter power spectrum. Here, our results provide an interesting toolbox of methods for learning about, and potentially constraining, the features of nonminimal dark sectors and their dynamics in the early universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Generalized Nuclear Code of Accounts for Cost Estimation Standardization

This is a joint INL-EPRI study. Link to corresponding page at the Electric Power Research Institute (EPRI): https://www.epri.com/research/products/000000003002028937 Recent Advanced Reactor (AR) designs typically offer features and attributes that depart from traditional water-cooled reactors in terms of fuel forms, coolants, structural materials, size, safety margins, and other important design and operational aspects. These departures, relative to the industry experience, will likely present a challenge for potential owner-operators when evaluating one or more AR designs for commercial deployment on a like-for-like basis. This is further exacerbated with new classes of reactors gaining prominence (e.g., microreactors) and new emerging applications (e.g., floating barge reactors or space propulsion reactors). The differences in design-specific technologies are compounded by the differences in approach to cost estimation. The lack of consistency in build up toward cost estimates creates a challenge when comparing competing concepts and evaluating their associated cost drivers. The outcome of a 2019 Scoping Study conducted by the Electric Power Research Institute (EPRI) indicated the need for a cost modeling guide (CMG), which would be underpinned by a technology-neutral and inclusive Generalized Nuclear Code of Accounts (GN-COA). A code of accounts (COA) is a tool by which costs are identified in even more specific categories, providing clarity on what specific costs are included in an estimate. A parallel independent effort was meanwhile taking place at Idaho National Laboratory via funding by the Systems Analysis Integration (SA&I) campaign of the Office of Nuclear Energy under the U.S. Department of Energy (U.S. DOE-NE) to also update the COA structure to enable more flexibility and encompass a wider variety of reactor technologies. After being made aware of these synergistic efforts, the two parties decided to combine efforts and develop a joint new standard format for nuclear cost estimation that builds on previous structures. This document describes the development of this joint GN-COA and provides guidance on the implementation of the tool, which is provided as the associated GN-COA Excel document. The main attributes of this novel COA format are that all items are functionally defined (in order to be technology and application agnostic) and grouped into logical arrangements that facilitate the tabulation of costs for reactor constructions under consideration. The intent is for the GN-COA to form a standard that is endorsed by future vendors and customers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗