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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Scalable Framework of Hybrid Modeling with Anticipatory Control Strategy for Autonomous Operation of Modular and Microreactors

This poster provides a high level overview of the Scalable Framework of Hybrid Modeling with Anticipatory Control Strategy for Autonomous Operation of Modular and Microreactors LDRD program to be presented at a poster session for students of the 2021 MeV School. The purpose of the poster is to provide other participants of the MeV School with a high level overview of the author's research direction.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Data-Driven Model Predictive Control for Temperature Management of Heat Pipe Microreactor

To enable the self-regulating capability of heat pipe (HP) microreactors, an anticipatory control strategy through model predictive control (MPC) could proactively respond to potential disturbances and deviations in operating setpoints. However, a key factor prohibiting the widespread adoption of MPCs in nuclear applications is the effort and computational costs associated with learning and calibrating first-principles-based process models when the target system is complex and when there are gaps between modeled and target reactor systems. In this paper, we demonstrate data-driven MPC using three approaches for modeling the system dynamics, including a linear state-space model, feedforward neural network, and recurrent neural networks long short-term memory. We present the development and validation process of each model and compare the performance of data-driven MPCs in controlling the temperatures of selected HPs at the evaporator and condenser regions in a 37-HP-monolith system. Our results show that, qualitatively, all data-driven MPCs are producing similar control actions, while quantitatively, with artificial neural nets (especially feedforward neural nets), MPC can better follow drastic changes in setpoints with smallest errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

AI-ENABLED MONITORING OPTIONS TOWARDS SECURE MICROREACTOR DEPLOYMENT AND OPERATIONS

Global nuclear energy deployment scenarios suggest favorable economics for smaller, more versatile, and self-contained reactor technologies. Recognizing their key features as integrated, autonomous and either semi-remotely operated or fully remotely operated systems, microreactors are expected to be deployed in large numbers servicing off/micro-grids, many in geographically remote locations. Integrated nature of these systems as well as ease of their transportation as complete units, simplified installation and relocation/decommissioning challenge traditional continuity-of-knowledge practices used for conventional light water reactors where refueling is done onsite at designated times only replacing portions of their cores and only after their full commissioning for operations including completion of their containment building with security and safeguards measures in place. This effort is exploring AI (artificial intelligence)-enabled monitoring options that would be design agnostic and would assure secure unit deployment and operations. The principle is to maintain situational awareness via real-time evaluations of simultaneous and remotely transmitted monitoring data capturing key safeguards attributes including such characteristics as temperature, radiation, vibrational signals (inter alia), and others. The key principle is to provide reliable and resilient security options while maintaining simplified and economical deployment. The paper will review feasible options for AI-enabled solutions for such evaluations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Streaming in a Nuclear Grade Sandwich Composite for Microreactor Shielding

The NGSC is a new approach to develop a shield structure for microreactors which combines the biological shielding with the reactor pressure vessel. Six layers of SS316 skins and core materials are present in the NGSC, where the core materials are reduce the neutron and gamma dose. Previous work has examined how a simplified NGSC can be optimized for cost, dose, and weight. This work explored the inclusion of SS36 ribs, which helps maintain the structural integrity of the NGSC, affects the transportation of radiation through the NGSC. For B$_4$C layers, the addition of ribs reduces neutron absorption but increase photon absorption. For WB$_4$-cermet layers, the addition of ribs reduces neutron absorption and reduces photon absorption.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

The MARVEL microreactor

Short presentation of MARVEL microreactor status as June 2024. To be presented at the INL-UK NNL meeting.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

Integrate Power Conversion Unit with MAGNET to Enable Integrated Microreactor Heat Transfer System Testing

Idaho National Laboratory obtained a closed, Brayton-cycle, power conversion unit (PCU) from Sandia National Laboratories. This PCU began as a commercially available, 30 kWe, C30, gas turbine from Capstone. The C30 was modified to use heat from an electric heater in a closed-loop system pressurized with nitrogen or dry air. INL has modified the unit further to integrate it with MAGNET and use heat from a microreactor test article.

42 - ENGINEERING↗
DOE OSTI2024

Autonomous control for Heat-Pipe microreactor using Data-Driven model predictive control

To enable a self-regulating capability for heat pipe (HP) microreactors, an anticipatory control strategy achieved via model predictive control (MPC) could proactively respond to potential disturbances and deviations in operating setpoints. This paper demonstrates data-driven methods for predicting the distribution and transient of temperatures and heat fluxes at selected components and regions in a 37-HP system, based on which the optimal control actions in response to changes in user-defined setpoints can be found. We present the development and validation of linear state-space model, feedfoward, and recurrent neural networks. Here, we compare the performance of MPCs with different modeling approaches in terms of following setpoints for temperatures and averaged output heat fluxes. The accuracies of the three data-driven models are similar, but the control actions initiated by neural-network-based MPC can better adapt to drastic changes in setpoints yet generate the smallest errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A Markov chain Monte Carlo (MCMC) Bayesian inference approach to analyze apparent activation barriers and reaction orders from microreactor data

Statistical analysis of steady-state catalytic kinetic data is often limited by data sparsity due to the slow pace at which the data is collected. Data sparsity and limitations in statistical analysis make it difficult to differentiate between mechanistic models and catalytic sites. A Bayesian inference tool is reported for catalysis researchers to estimate error in the determination of reaction orders from steady state microreactor data. The benefits of a Bayesian inference approach are discussed, as an alternative to the more common frequentist approach. The approach incorporates prior knowledge of the system and the data collected to form an error estimate on reaction orders. We investigated the effects of three distinct data treatments—individual fitting of trials, pooled analysis, and constrained regression methods—on the precision and uncertainty of reaction order determinations. To assess the robustness of our findings, we conducted sensitivity analyses to evaluate the influence of Bayesian parameters on uncertainty estimation. Additionally, we utilized synthetic data to illustrate how data quality impacts the precision of uncertainty assessments. We show Bayesian analysis can obtain a more precise estimation of error with a sparse data set than a frequentist analysis. Finally, this work provides strong evidence that the adoption of Bayesian analysis of kinetic data may help researchers make more precise arguments as to the strength of their evidence for a particular mechanistic hypothesis, or in comparing across different catalysts.

42 ENGINEERING↗
DOE OSTI2017

Tabletop Femtosecond VUV Photoionization and PEPICO Detection of Microreactor Pyrolysis Products

Here, we report the combination of tabletop vacuum ultraviolet photoionization with photoion--photoelectron coincidence spectroscopy for sensitive, isomer-specific detection of nascent products from a pyrolysis microreactor. Results on several molecules demonstrate two essential capabilities that are very straightforward to implement: the ability to differentiate isomers, and to distinguish thermal products from dissociative ionization. We derive vacuum ultraviolet light is from a commercial tabletop femtosecond laser system, allowing data to be collected at 10 kHz; this high repetition rate is critical for coincidence techniques. The photoion—photoelectron coincidence spectrometer uses the momentum of the ion to identify dissociative ionization events, and coincidence techniques to provide a photoelectron spectrum specific to each mass, which is used to distinguish different isomers. We also have used this spectrometer to detect the pyrolysis products that result from the thermal cracking of acetaldehyde, cyclohexene, and 2-butanol. The photoion—photoelectron spectrometer can detect and identify organic radicals and reactive intermediates that result from pyrolysis. Direct comparison of laboratory and synchrotron data illustrate the advantages and potential of this approach.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Direct Conversion of Ethane to Oxygenates, Ethylene, and Hydrogen in a Noncatalytic Biphasic Plasma Microreactor

We selectively upgrade ethane (C 2 H 6 ) to ethanol (C 2 H 5 OH), methanol (CH 3 OH), and acetic acid (CH 3 COOH) in a catalyst-free, continuous, argon/water biphasic plasma microreactor. The water (H 2 O) evaporates and electron- dissociates into OH· radicals. OH· recombines with alkyl radicals, produced via electron dissociation of ethane, to generate the oxygenates that absorb into H 2 O. A plasma-assisted path, reminiscent of the low-temperature thermocatalytic ethane steam reforming, leads to significant H 2 coproduction. The gaseous stream also comprises CO 2 and C 2 H 4 . Up to 1.3 and 1 μmol min –1 of liquid C 2 H 5 OH and CH 3 OH are attained, respectively. Compared to CO 2 -assisted ethane plasma conversion, which produces many oxygenates with low selectivity, the carbon selectivity can range from >70% C 2 H 5 OH, CH 3 OH, and CH 3 COOH to 60% C 2 H 4 . Furthermore, the low carbon footprint, electrified, modular, intensified process using a reactive evaporation and separation plasma could pave the way for the valorization of underutilized shale gas resources in remote areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

An economics-by-design approach to a radiant integrated thermophotovoltaic microreactor system

This paper presents an application of the economics-by-design approach to the Radiant Integrated Thermo-photovoltaic Microreactor System (RITMS). The RITMS design is unique in that it directly couples a critical fission reactor with thermo-photovoltaic (TPV) panels for high efficiency energy conversion. This significant shift from electric conversion using traditional dynamic heat pumps leads to a simpler and more reliable system without turbomachinery and high pressurization. In working towards wrapping up the early design work, the economics-by-design approach, which centers economic competitiveness as the optimization parameter, is well suited in making a final determination on viability. This paper describes the computational sequence that was developed to couple the radiative and conductive heat transfer and feed operational performance to cost estimation. The framework was applied to maximize the power of the system, while minimizing the fuel enrichment. This method is applied to a reference RITMS design as part of a parametric sensitivity study, which revealed that the system is under moderated and that single unit plants could produce power as low as 300 dollar/MWh. This price point supports the notion that early in the RITMS design implementation, adoption into niche markets as a first-of-a-kind technology is possible. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Demonstrate embedding of sensors in a relevant microreactor component

This report describes the first successful embedding of sensors in stainless steel pipe specimens and a miniature hex block to support structural health monitoring of microreactor components during electrically heated testing in non-nuclear testbed facilities. Sensors were embedded with an ultrasonic additive manufacturing process that uses a combination of downward pressure and an ultrasonic scrubbing motion to bond stainless steel foils to underlying materials. After placing sensors within cavities that have been machined to the size of the sensors, the ultrasonic bonding process fills the gaps around the sensors and embeds them within the part. Both Type K thermocouples and spatially distributed fiber-optic strain sensors were successfully embedded within two pipe specimens and a miniature hex block. After the fiber-optic sensors were embedded, they were interrogated and found to have minimal signal attenuation within the embedded region—a significant improvement compared to previous trials. This is likely because of the low-bend-loss fiber that was used, which greatly reduces microbending losses that occur after the embedding process. In addition to showing minimal signal attention, the fibers also showed adequate compressive strain, which is a strong indication that the sensors are physically embedded in the parts as opposed to simply being loosely contained inside the machined cavities. The embedded fibers were able to capture the strain induced in one of the pipe specimens while the pipe was actively heated with a moving heat source.

42 ENGINEERING↗
DOE OSTI2022

ORNL Progress Report on Microreactor Functional Containment Economics

A summary of Oak Ridge National Laboratory’s (ORNL’s) initial contributions to the economic and functional containment evaluation approach for microreactors is presented. A final report will be completed at the end of 2022. This initial progress report does not represent a final product or an expression of a complete technical analysis. Initial contributions from ORNL can be categorized into two parts: (1) description of functional containment as a design optimization tool, and (2) summary of high level technology concepts for an evaluation of economic and functional containment analysis. Additionally, the initial portion of a functional containment evaluation is presented for a generic high temperature gas reactor technology. Remaining tasks include completing the functional containment evaluation by connecting economic and consequence metrics, as well as performing the same effort for other select reactor technologies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Assessing Several Modeling Approaches in Depletion Studies of a TRISO-Fueled Microreactor

The impact of MCNP6 depletion resolution on core lifetime is examined in the context of the Snowflake microreactor with explicit TRISO fuel. The change in core lifetime and isotope mass as a result of different tracked isotopes, timesteps, and spatial regions is discussed. Calculation speed of a prototype MCNP delta tracking module is compared to a reactivity equivalent physical transformation (RPT). Using a single depletion material underpredicts core lifetime by 15%, and the resolution necessary to converge isotope mass greatly depends on the specific isotope, in addition to the size (and location) of the depletion region. The prototype delta tracking module decreases the CPU time of explicit TRISO criticality calculations by 30%, but does not always result in a speedup when used with depletion. Significant depletion speedup is obtained using RPT (50% faster), and all isotope masses agreed within three percent.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗