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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 505 records · Page 28

Modular Processing of Flare Gas for Carbon Nanoproducts

This project demonstrated the technical viability and economic promise of a modular system for converting flared natural gas into valuable carbon nanoproducts (CNPs) through catalytic chemical vapor deposition (CVD). All major project milestones were successfully completed, including reactor design and commissioning, catalyst development, process optimization, technoeconomic analysis, and application testing in concrete systems. The overarching goal was to create a scalable, field-deployable process that valorizes stranded methane by producing high-value carbon materials for use in cementitious composites. At the lab scale, the team designed and built a fluidized bed reactor optimized for use with silica fume-supported nickel catalysts synthesized via atomic layer deposition (ALD). A statistically designed sintering study enabled precise tuning of nickel nanoparticle size, identifying the influence of oxygen partial pressure, time, and temperature on catalyst morphology and performance. These insights allowed the team to target catalyst conditions that maximize carbon nanofilament growth. Subsequent CVD experiments achieved up to 31.8 wt% carbon deposition under optimized conditions, with TEM confirming the presence of nanofilament structures and sustained hydrogen evolution during reaction. Reactor upgrades and empirical fluidization studies supported the development of reliable, repeatable experimental protocols. The modular pilot-scale skid reactor was fully constructed, instrumented, and commissioned. Capable of operating at 675–800°C and pressures up to 290 psig, the system was designed for continuous operation at a carbon production rate of 1 kg/hr. Initial demonstration runs confirmed solids handling, thermal control, and system leak-tightness, although a critical reactor component (the downfeed tube) was inadvertently omitted during final assembly. This omission limited gas–solid contact and prevented meaningful carbon deposition during pilot-scale CVD runs. Nonetheless, the system operated safely under design conditions, and the root cause of performance limitations was clearly identified. Complementary work on UHPC formulations demonstrated that small additions of carbon nanoproducts, including those derived from flare gas, can significantly enhance mechanical performance while preserving workability. A comprehensive study of CNF dispersion techniques and mix design optimization led to a clear protocol for integrating these nanomaterials into concrete. Incorporation of CNPs improved flexural toughness and reduced porosity, supporting their use in high-performance infrastructure applications. A technoeconomic analysis (TEA) confirmed that this process can produce CNP-loaded catalyst material at a levelized cost below $\$$7/kg across a range of catalyst loadings and reaction yields. With estimated market values for the carbon composite product ranging from $\$$14 to over $\$$60/kg, and the ability to blend CNPs into concrete at sub-percent levels with less than 10% added cost, the system presents a compelling economic case. While additional engineering work is needed to optimize fluidization and heat transfer at scale, this project establishes a strong foundation for commercial development. The process is not only technically sound but also economically promising, representing a viable pathway for flare gas mitigation through modular carbon nanomaterial production.

03 NATURAL GAS↗

A Hierarchical OPF Algorithm with Improved Gradient Evaluation in Three-Phase Networks

Linear approximation commonly used in solving alternating-current optimal power flow (AC-OPF) simplifies the system models but incurs accumulated voltage errors in large power networks. Such errors will make the primal-dual type gradient algorithms converge to solutions with voltage violation. In this paper, we improve a recent hierarchical OPF algorithm that rested on primal-dual gradients evaluated with a linearized distribution power flow model. Specifically, we propose a more accurate gradient evaluation method based on an unbalanced three-phase nonlinear distribution power flow model to mitigate the errors arising from linearization. The resultant gradients feature a blocked structure that enables our development of an improved hierarchical primal-dual algorithm to solve the OPF problem. Numerical results on the IEEE 123-bus test feeder and a 4,518-node test feeder show that the proposed method can enhance voltage safety at comparable computational efficiency with the linearized algorithm.

approximation algorithms↗

Uncertainty quantification and sensitivity analysis of a nuclear thermal propulsion reactor startup sequence

The research presented in this article describes progress in applying stochastic methods, uncertainty quantification, parametric studies, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated via the radiation transport code Griffin to simulate neutronics. Our goal is to develop a reduced-order (surrogate) model that can be rapidly sampled with perturbations to multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums (CDs), which is itself controlled by a hybrid proportional-integral-derivative (PID) controller actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time [Λ] and effective delayed neutron fraction [ β eff ] from a transient Griffin simulation executed via Griffin’s improved quasi-static solver to provide the kinetic parameters) as inputs to functions that control the CD rotation angle. By investigating numerous stochastic approaches, we developed a dual-purpose surrogate model of the NTP system, using polynomial regression in the Multiphysics Object-Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM). The trained model can be rapidly sampled while simultaneously perturbing various input parameters, such as coefficients on the PID control or temperature (directly affecting the neutron cross section). The surrogate model delivers accurate (within 5%) results at speeds orders of magnitude faster (minutes, not days of computational time) than the base model. Once the surrogate model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs as well as the effects of these inputs on the model output. For example, coefficients used in the PID control system may vary due to some type of physical interference, or uncertainty may exist in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters, and operational boundaries can be determined. The goal of this work is to support development of an advanced control system for operating CDs in a functioning NTP system. This work is a scoping study of the MOOSE STM.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Evaluation of color in digital nuclear power plant control room displays

Human system interface design in industrial process control is guided by industry standards, human factors best practices, and domain-specific conventions, and often there is a conflict between one or more of the sources of design input for specific design elements. In the nuclear domain, one design element for which conflict arises is the use of color to represent equipment state. Here, this study evaluates the tradeoffs associated with using color in a process control display versus using white and shades of gray. The performance metrics were response time, accuracy, and eye movement metrics using a simplified experimental task and professional operators. Results revealed that adhering to color conventions in nuclear power yielded small advantages in simple tasks, but did not exist for more complex tasks. The results did not provide strong evidence for or against using a particular color scheme and revealed the need for further research on the use of color for commercial nuclear power plants and other process control industries.

99 GENERAL AND MISCELLANEOUS↗

Autonomous Operations for Advanced Reactors Utilizing Supervisory Control

Automation is a critical tenet of reactor plant operations as reliance on nuclear energy increases. Nuclear power plants require a large workforce which does not scale with output; that is, the cost per megawatt increases as reactor output becomes smaller. The economic viability of advanced reactors, particularly small modular reactors (SMRs) and microreactors, requires a significantly reduced onsite workforce. The logical solution is establishing a systematic process of elimination of reliance on human operators, and to the extent possible, replacing these actions with automated functions. In this paper, we propose a method for such transformation to establish a robust technical basis to enable transition to autonomy. Our method is based on finite state automata (FSA)—also known as finite state machines (FSMs). Relying on this method allows us to exploit the rich set of mathematical proofs available in the field of regular languages. FSA are one of the mathematical tools to model discrete event systems (DES). These properties are applied to produce an automated startup controller for the Massachusetts Institute of Technology Research Reactor (MITR). The startup procedure is captured in terms of discrete changes from one state to another while an independent supervisory control system directs the sequence of states and alerts a human in the event of an abnormal operation. First, the design and behavior of the MITR rod control system were modeled in Simulink. Then, the startup procedure was applied to the rod control system and the DES performed a startup by procedurally withdrawing rods to the subcritical position. The simulation also stops rod motion in response to an uncontrollable event and restarts rod motion once the event has been cleared.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Optomechanical self-organization in a mesoscopic atom array

Increasing the number of particles in a system often leads to qualitative changes in its properties, such as breaking of symmetries and the appearance of phase transitions. This renders a macroscopic system fundamentally different from its individual microscopic constituents. Lying between these extremes, mesoscopic systems exhibit microscopic fluctuations that influence behaviour on longer length scales, leading to critical phenomena and dynamics. Therefore, tracing the properties of well-controlled mesoscopic systems can help bridge the gap between an exact description of few-body microscopic systems and the emergent description of many-body systems. Here we explore the mesoscopic signatures of an optomechanical self-organization phase transition using arrays of cold atoms inside an optical cavity. By precisely engineering atom–cavity interactions, we reveal how critical behaviour depends on the atom number, identify characteristic dynamical behaviours in the self-organized regime and observe a finite optomechanical susceptibility at the critical point. These findings advance our understanding of particle-number- and time-resolved properties of phase transitions in mesoscopic systems.

Atomic and molecular interactions with photons↗

Multiscale Dynamics of Reactive Fronts in the Subsurface

Understanding and predicting flow and reactive transport in rocks (i.e. geologic porous media) is critical to many technologies at the heart of the energy transition, including CO 2 sequestration and H2 storage. However, accurate modeling and prediction of these systems is very complex because physico-chemical processes that occur at very small spatial scales, i.e. in the pores of the rocks, can dramatically control the system performance at the field scale (km). For example, precipitation reactions at the pore-scale can lead to large permeability changes at the field scale and dramatically alter the migration of stored gases. Properly accounting for multi-scale coupling effects is critical to achieve predictivity and confidence in model outputs, which then can guide design and optimization at the system-scale. This can be achieved through the development of rigorous mathematical models that can appropriately account for fine-scale effects at the large scale. The final report of the Early Career award DE-SC0019075 “Multiscale dynamics of reactive fronts in the subsurface” summarizes the mathematical, numerical and experimental advancements to study and predict reactive transport in geologic porous media across scales.

58 GEOSCIENCES↗

Development of an Optimal Variable-Pitch Controller for Floating Axial-Flow Marine Hydrokinetic Turbines: Preprint

This article discusses the development of an optimal variable-pitch controller for floating, axial-flow marine turbines. Recently, OpenFAST, an open-source wind turbine modeling tool, has been extended to model marine turbines. A controller is necessary to simulate marine turbines for different load cases using OpenFAST, which greatly impacts the performance of the energy system. Previous studies have designed controllers using a linearized model of the marine turbine, which can be timeconsuming and require the expertise of a control engineer. In this study, we use an automated approach that uses generic models of the marine turbine to identify the controller gains, which can expedite the process of designing a controller. Using an optimizer to identify the control system parameters can additionally improve the controller's performance. The optimal controller tuned using such an approach results in a 20% reduction in the towerbase damage equivalent loading and better tracking of the rated generator speed and power.

closed-loop control↗

Stochastic Adaptive Droop Control in Frequency Regulation of Power Systems With Intermittent Generators

Modern power systems (MPSs), including microgrids (MGs), are increasingly incorporating multiple renewable energy sources (RESs) such as wind and solar power, as well as battery storage and controllable loads. While environmentally beneficial, these sources pose challenges for control and management due to their intermittent and stochastic nature, especially in maintaining frequency stability with multiple interconnected generators of varying capacities. Traditional droop control methods are effective in systems with generators that are dispatchable and have fixed generation capacities, but they fall short when applied to systems with RESs, where generation capacities are dynamic and affected by unpredictable environmental conditions. To address these challenges, this paper introduces a novel stochastic adaptive droop control (SADC) method for load frequency control (LFC). The proposed method adapts droop coefficients in real time, based on the measured stochastic data of power generation capacities, enabling more effective frequency regulation in systems with variable and intermittent power generation. Unlike traditional adaptive control methods, which assume constant or slowly-varying system parameters, this approach accounts for stochastic processes by modeling them as Markov chains, enabling robust performance under highly dynamic and unpredictable conditions. The key contributions of this work include the development of real-time droop coefficient adaptation algorithms, derivation of their stability and convergence properties, and the demonstration of the advantages of the method through simulations. Case studies highlight the improved performance of frequency regulation, particularly in addressing the impact of stochastic weather conditions and the benefits of reducing dependence on battery reserves in dealing with intermittency of RESs. Finally, this paper provides a comprehensive analysis of the theoretical foundations of the method, as well as practical implementation insights for future power systems with high penetration of RESs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Nonlinear model predictive control for mode‐switching operation of reversible solid oxide cell systems

Abstract Solid oxide cells (SOCs) are a promising dual‐mode technology for the production of hydrogen through high‐temperature water electrolysis, and the generation of power through a fuel cell reaction that consumes hydrogen. Switching between these two modes as the price of electricity fluctuates requires reversible SOC operation and accurate tracking of hydrogen and power production set points. Moreover, a well‐functioning control system is important to avoid cell degradation during mode‐switching operation. In this article, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional‐integral (PI) control strategies, while switching between the modes of hydrogen and power production. While both control methods provide similar performance across various metrics during mode switching, NMPC demonstrates a significant advantage in reducing cell thermal gradients and curvatures (mixed spatial‐temporal partial derivatives), thereby helping to mitigate long‐term degradation.

08 HYDROGEN↗

Transverse emittance growth due to rf noise in crab cavities: Theory, measurements, cure, and high luminosity LHC estimates

The High-Luminosity LHC (HL-LHC) upgrade with planned operation from 2029 onward has a goal of achieving a tenfold increase in the integrated number of recorded collisions thanks to a doubling of the intensity per bunch ( 2.2 × 10 11 protons) and a reduction of β * (the β value in the two high luminosity detectors, namely ATLAS and CMS) to 15 cm. Such an increase in recorded collisions would significantly expedite new discoveries and exploration. Crab cavities are an important component of the HL-LHC upgrade and will contribute strongly to achieving an increase in the number of recorded collisions. However, noise injected through the crab cavity radio frequency (rf) system could cause significant transverse emittance growth and limit luminosity lifetime. We presented a theoretical formalism relating transverse emittance growth to rf noise in an earlier work. In this follow-up paper, we summarize measurements in the super-proton synchrotron (SPS) at CERN that validate the theory, we present estimates of the emittance growth rates using state-of-the-art rf and low-level rf (LLRF) technologies, and we set the rf noise specifications to achieve acceptable performance. A novel dedicated feedback system acting through the crab cavities to mitigate emittance growth will be required. In this work, we develop a theoretical formalism to evaluate the performance of such a feedback system in any collider, identify limiting components, present simulation results to validate these studies, and derive key design parameters for an HL-LHC implementation of such a feedback system. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

A Neural Optimizer With Decision-Focused Learning for Optimal Energy Storage Operation

Here, this article introduces a neural optimizer-based framework for optimizing battery energy storage system (BESS) control for grid services, including demand charge and energy cost reduction. By leveraging decision-focused learning (DFL), the proposed framework ensures seamless integration and adaptation, significantly enhancing control performance. A patch time-series transformer is employed for peak load forecasting, incorporating aleatoric uncertainty quantification to account for forecasting uncertainties within the decision-making process. The framework utilizes a solver-in-the-loop approach to generate optimal BESS actions, which are then used to train the neural optimizer-based agent. By co-optimizing both BESS operational modes and output power within the NN, the system achieves improved performance and robustness. After initial training, the forecasting and control models are jointly fine-tuned to account for forecasting errors, further improving decision precision and efficiency through DFL. Case studies are performed to validate the performance of the framework using multiple real-world datasets, demonstrating superior performance in monthly peak load forecasting compared to state-of-the-art models. In addition, the results are compared against existing decision-making approaches. The results demonstrate a reduction in monthly peak forecasting error by approximately 15% across various performance measures and achieve an optimization gap for BESS operation that is about three times smaller compared to existing methods.

Kim, Hyeonjin [Pacific Northwest National Laborato↗

Nuclear Safety [Vol. 35, No. 2, July-December 1994]

Nuclear Safety is a journal that covers significant issues in the field of nuclear safety. Its primary scope is safety in the design, construction, operation, and decommissioning of nuclear power reactors worldwide and the research and analysis activities that promote this goal, but it also encompasses the safety aspects of the entire nuclear fuel cycle, including fuel fabrication, spent-fuel processing and handling, and nuclear waste disposal, the handling of fissionable materials and radioisotopes, and the environmental effects of all these activities. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 179 Consideration of Postaccident Consequences in the Determination of Safety Objectives for Future Nuclear Power Plants in France, D. Queniart, A. Sugier, and J. Lochard; ACCIDENT ANALYSIS: 187 Nuclear Safety Research: The Phebus FP Severe Accident Experimental Program, P. von der Hardt, A. V. Jones, C. Lecomte, and A. Tattegrain; 205 Containment Performance Analysis of the Advanced Neutron Source Reactor at the Oak Ridge National Laboratory, S. H. Kim, R. P. Taleyarkhan, and V. Georgevich; 213 Assessment of Fission Product Deposits in the Reactor Coolant System: The DEVAP Program, G. Le Marois and M. Megnin; 222 Erratum to “A Review of the Available Information on the Triggering Stage of a Steam Explosion," Vol. 35, No. 1, CONTROL AND INSTRUMENTATION: 223 Effects of Normal Aging on Calibration and Response Time of Nuclear Plant Resistance Temperature Detectors and Pressure Sensors, H. M. Hashemian; DESIGN FEATURES: 235 Defense in Depth Against the Hydrogen Risk—A European Research Program, F. Fineschi; ENVIRONMENTAL EFFECTS: 246 Technical Note: A Preliminary Analysis of the Risks to Hong Kong Resulting from Potential Accidents of Daya Bay Nuclear Power Plant, Z. Shi and X. Wei; OPERATING EXPERIENCES: 253 Reactor Shutdown Experience, Compiled by J. W. Cletcher; SPECIAL SECTION ON TMI-2 VESSEL INVESTIGATION PROJECT: 256 Three Mile Island—New Findings 15 Years After the Accident A. M. Rubin and E. Beckjord; 269 Relocation of Molten Material to the TMI-2 Lower Head, J. R. Wolf, D. W. Akers, and L. A. Neimark; 280 Insight Into the TMI-2 Core Material Relocation Through Examination of Instrument Tube Nozzles, L. A. Neimark; 288 Physical and Radiochemical Examinations of Debris from the TMI-2 Lower Head, D. W. Akers and B. K. Schuetz; 301 Results of Metallographic Examinations and Mechanical Tests of Pressure Vessel Samples from the TMI-2 Lower Head, D. R. Diercks and G. E. Korth; 313 Margin-to-Failure Calculations for the TMI-2 Vessel, J. Rempe, L. Stickler, S. Chavez, G. Thinnes, R. Witt, and M. Corradini; U.S. NUCLEAR REGULATORY COMMISSION INFORMATION AND ANALYSES: 328 1993 Accident Sequence Precursor (ASP) Program Results, L. N. Vanden Heuvel, J. W. Cletcher, D. A. Copinger, J. W. Minarick, B. W. Dolan, and P. D. O’Reilley; RECENT DEVELOPMENTS: 339 Reports, Standards, and Safety Guides, D. S. Queener; 345 Proposed Rule Changes as of June 30, 1994; ANNOUNCEMENTS: 234 Thirty-First Annual Meeting of the National Council on Radiation Protection and Measurements; 356 1995 International Incineration Conference; 358 Fifth International Controls and Instrumentation Conference; 359 ANS International Topical Meeting on Safety of Operating Reactors; 359 Fifth International Conference on Nuclear Criticality Safety; 360 International Conference on Probabilistic Safety Assessment Methodology and Applications; 351 The Authors; 357 Reviewers of Nuclear Safety, Vol. 35.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Engineering microalgal cell wall-anchored proteins using GP1 PPSPX motifs and releasing with intein-mediated fusion

AbstractHarnessing and controlling the localization of recombinant proteins is critical for advancing applications in synthetic biology, industrial biotechnology, and drug delivery. This study explores protein anchoring and controlled release inChlamydomonas reinhardtii, providing innovative tools for these fields. Using truncated variants of the GP1 glycoprotein fused to the plastic-degrading enzyme PHL7, we identified the PPSPX motif as essential for anchoring proteins to the cell wall. Constructs with increased PPSPX content exhibited reduced secretion but improved anchoring, pinpointing the potential anchor-signal sites of GP1 and highlighting the distinct roles of these motifs in protein localization. Building on the anchoring capabilities established with these glycomodules, we also demonstrated a controlled release system using a pH-sensitive intein derived from RecA fromMycobacterium tuberculosis. This intein efficiently cleaved and released PHL7 and mCherry that was fused to GP1 under acidic conditions, enabling precise temporal and environmental control. At pH 5.5, fluorescence kinetics demonstrated significant mCherry release from the pJPW4mCherry construct within 4 hours. In contrast, release was minimal under pH 8.0 conditions and negligible for the pJPW2mCherry (W2) control, irrespective of the pH. Additionally, bands on the Western blot at the expected size of mCherry also showed its efficient release from the mCherry::intein::GP1 fusion protein at pH 5.5. Conversely, at pH 8.0, no bands were detected. This anchor-release approach offers significant potential for drug delivery, biocatalysis, and environmental monitoring applications. By integrating glycomodules and pH-sensitive inteins, this study establishes a versatile framework for optimizing protein localization and release inC. reinhardtii, with broad implications for proteomics, biofilm engineering, and scalable therapeutic delivery systems.Graphical Abstract

Kang, Kalisa (ORCID:0009000619398129)↗

An Innovative Energy Management System for Microgrids with Multiple Grid-Forming Inverters

As increasingly more grid-forming (GFM) inverter-based resources replace traditional fossil-fueled synchronous generators as the GFM sources in microgrids, the existing microgrid energy management systems (EMS) need to be updated to control and coordinate multiple GFM inverters that consider system control objectives under different microgrid connection states. For each state, we formulate an optimization problem and apply a real-time feedback-based control algorithm; altogether, the control algorithms seamlessly connect the states into a generic microgrid EMS that controls the nodal voltages and frequencies, becomes a virtual power plant (VPP) when connected to the main grid, and coordinates power sharing responsibility among GFM sources when islanded. We showcase the EMS on a real-world simulation of a microgrid under the different states to demonstrate its operational effectiveness.

energy management systems↗

(U)Vendor Sanitization Requirements – SIEMENS Control

This document defines the software requirements for the sanitization of the IPC and or the controller. The system is intended to manage part programs and associated data (e.g. simulations, probing data) by capturing metadata, securely sanitizing files, logging operations, backing up data to a defined path, deploying a user defined program to a controller, and restoring part programs and associated data when required.

42 ENGINEERING↗