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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

A stochastic model for photon noise induced by charged particles in multiplier phototubes of the space telescope fine guidance sensors

The Space Telescope (ST) is subjected to charged particle strikes in its space environment. ST's onboard fine guidance sensors utilize multiplier phototubes (PMT) for attitude determination. These tubes, when subjected to charged particle strikes, generate spurious photons in the form of Cerenkov radiation and fluorescence which give rise to unwanted disturbances in the pointing of the telescope. A stochastic model for the number of these spurious photons which strike the photocathode of the multiplier phototube which in turn produce the unwanted photon noise are presented. The model is applicable to both galactic cosmic rays and charged particles trapped in the Earth's radiation belts. The model which was programmed allows for easy adaption to a wide range of particles and different parameters for the phototube of the multiplier. The probability density functions for photons noise caused by protons, alpha particles, and carbon nuclei were using thousands of simulated strikes. These distributions are used as part of an overall ST dynamics simulation. The sensitivity of the density function to changes in the window parameters was also investigated.

Howell, L. W.↗
DOE OSTI2023

Frost prediction using machine learning and deep neural network models

This study describes accurate, computationally efficient models that can be implemented for practical use in predicting frost events for point-scale agricultural applications. Frost damage in agriculture is a costly burden to farmers and global food security alike. Timely prediction of frost events is important to reduce the cost of agricultural frost damage and traditional numerical weather forecasts are often inaccurate at the field-scale in complex terrain. In this paper, we developed machine learning (ML) algorithms for the prediction of such frost events near Alcalde, NM at the point-scale. ML algorithms investigated include deep neural network, convolution neural networks, and random forest models at lead-times of 6–48 h. Our results show promising accuracy (6-h prediction RMSE = 1.53–1.72°C) for use in frost and minimum temperature prediction applications. Seasonal differences in model predictions resulted in a slight negative bias during Spring and Summer months and a positive bias in Fall and Winter months. Additionally, we tested the model transferability by continuing training and testing using data from sensors at a nearby farm. We calculated the feature importance of the random forest models and were able to determine which parameters provided the models with the most useful information for predictions. We determined that soil temperature is a key parameter in longer term predictions (>24 h), while other temperature related parameters provide the majority of information for shorter term predictions. The model error compared favorable to previous ML based frost studies and outperformed the physically based High Resolution Rapid Refresh forecasting system making our ML-models attractive for deployment toward real-time monitoring of frost events and damage at commercial farming operations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Experimental Verification of Buffet Calculation Procedure Using Unsteady PSP

Typically a limited number of dynamic pressure sensors are employed to determine the unsteady aerodynamic forces on large, slender aerospace structures. The estimated forces are known to be very sensitive to the number of the dynamic pressure sensors and the details of the integration scheme. This report describes a robust calculation procedure, based on frequency-specific correlation lengths, that is found to produce good estimation of fluctuating forces from a few dynamic pressure sensors. The validation test was conducted on a flat panel, placed on the floor of a wind tunnel, and was subjected to vortex shedding from a rectangular bluff-body. The panel was coated with fast response Pressure Sensitive Paint (PSP), which allowed time-resolved measurements of unsteady pressure fluctuations on a dense grid of spatial points. The first part of the report describes the detail procedure used to analyze the high-speed, PSP camera images. The procedure includes steps to reduce contamination by electronic shot noise, correction for spatial non-uniformities, and lamp brightness variation, and finally conversion of fluctuating light intensity to fluctuating pressure. The latter involved applying calibration constants from a few dynamic pressure sensors placed at selective points on the plate. Excellent comparison in the spectra, coherence and phase, calculated via PSP and dynamic pressure sensors validated the PSP processing steps. The second part of the report describes the buffet validation process, for which the first step was to use pressure histories from all PSP points to determine the "true" force fluctuations. In the next step only a selected number of pixels were chosen as "virtual sensors" and a correlation-length based buffet calculation procedure was applied to determine "modeled" force fluctuations. By progressively decreasing the number of virtual sensors it was observed that the present calculation procedure was able to make a close estimate of the "true" unsteady forces only from four sensors. It is believed that the present work provides the first validation of the buffet calculation procedure which has been used for the development of many space vehicles.

Buffet↗
NASA NTRS2017

Experimental Verification of Buffet Calculation Procedure Using Unsteady Pressure-Sensitive Paint

Typically, a limited number of dynamic pressure sensors is employed to determine the unsteady aerodynamic forces on large, slender aerospace structures. This paper describes a robust calculation procedure based on frequency-specific correlation lengths and validation from an experiment conducted on a flat panel coated with fast response pressure-sensitive paint. The first part of the paper describes the procedure used to analyze the pressure sensitive paint images and a calibration method using dynamic pressure transducers. Excellent comparison in spectra, coherence, and phase, measured via pressure-sensitive paint and dynamic pressure sensors, validates the pressure-sensitive paint data. The second part of the paper describes the buffet validation process, the first step of which was to use pressure histories from all pixels to determine the true force fluctuations. In the next step, only a selected number of pixels was chosen as virtual sensors, and a correlation-length-based buffet calculation procedure was applied to determine modeled force fluctuations. By progressively decreasing the number of virtual sensors, it was observed that the present calculation procedure was able to make a close estimate of the true unsteady forces only from eight sensors. It is believed that the present work provides the first validation of a buffet calculation procedure.

Buffet↗
NASA NTRS2005

Mapping From an Instrumented Glove to a Robot Hand

An algorithm has been developed to solve the problem of mapping from (1) a glove instrumented with joint-angle sensors to (2) an anthropomorphic robot hand. Such a mapping is needed to generate control signals to make the robot hand mimic the configuration of the hand of a human attempting to control the robot. The mapping problem is complicated by uncertainties in sensor locations caused by variations in sizes and shapes of hands and variations in the fit of the glove. The present mapping algorithm is robust in the face of these uncertainties, largely because it includes a calibration sub-algorithm that inherently adapts the mapping to the specific hand and glove, without need for measuring the hand and without regard for goodness of fit. The algorithm utilizes a forward-kinematics model of the glove derived from documentation provided by the manufacturer of the glove. In this case, forward-kinematics model signifies a mathematical model of the glove fingertip positions as functions of the sensor readings. More specifically, given the sensor readings, the forward-kinematics model calculates the glove fingertip positions in a Cartesian reference frame nominally attached to the palm. The algorithm also utilizes an inverse-kinematics model of the robot hand. In this case, inverse-kinematics model signifies a mathematical model of the robot finger-joint angles as functions of the robot fingertip positions. Again, more specifically, the inverse-kinematics model calculates the finger-joint commands needed to place the fingertips at specified positions in a Cartesian reference frame that is attached to the palm of the robot hand and that nominally corresponds to the Cartesian reference frame attached to the palm of the glove. Initially, because of the aforementioned uncertainties, the glove fingertip positions calculated by the forwardkinematics model in the glove Cartesian reference frame cannot be expected to match the robot fingertip positions in the robot-hand Cartesian reference frame. A calibration must be performed to make the glove and robot-hand fingertip positions correspond more precisely. The calibration procedure involves a few simple hand poses designed to provide well-defined fingertip positions. One of the poses is a fist. In each of the other poses, a finger touches the thumb. The calibration subalgorithm uses the sensor readings from these poses to modify the kinematical models to make the two sets of fingertip positions agree more closely.

Goza, Michael↗
NASA NTRS1995

SXI prototype mirror mount

The purpose of this contract was to provide optomechanical engineering and fabrication support to the Solar X-ray Imager (SXI) program in the areas of mirror, optical bench and camera assemblies of the telescope. The Center for Applied Optics (CAO) worked closely with the Optics and S&E technical staff of MSFC to develop and investigate the most viable and economical options for the design and fabrication of a number of parts for the various telescope assemblies. All the tasks under this delivery order have been successfully completed within budget and schedule. A number of development hardware parts have been designed and fabricated jointly by MSFC and UAH for the engineering model of SXI. The major parts include a nickel electroformed mirror and a mirror mount, plating and coating of the ceramic spacers, and gold plating of the contact rings and fingers for the camera assembly. An aluminum model of the high accuracy sun sensor (HASS) was also designed and fabricated. A number of fiber optic tapers for the camera assembly were also coated with indium tin oxide and phosphor for testing and evaluation by MSFC. A large number of the SXI optical bench parts were also redesigned and simplified for a prototype telescope. These parts include the forward and rear support flanges, front aperture plate, the graphite epoxy optical bench and a test fixture for the prototype telescope. More than fifty (50) drawings were generated for various components of the prototype telescope. Some of these parts were subsequently fabricated at UAH machine shop or at MSFC or by the outside contractors. UAH also provide technical support to MSFC staff for a number of preliminary and critical design reviews. These design reviews included PDR and CDR for the mirror assembly by United Technologies Optical Systems (UTOS), and the program quarterly reviews, and SXI PDR and CDR. UAH staff also regularly attended the monthly status reviews, and made a significant number of suggestions to improve the design, assembly and alignment of the telescope. Finally, a high level assembly and alignment plan for the entire telescope was prepared by UAH. This plan addresses the sequence of assembly, the required assembly and alignment tolerances, and the methods to verify the alignment at each step during the assembly process. This assembly and alignment plan will be used to assemble and integrate the engineering model (EM) of the telescope. Later on, based on this plan more detailed assembly and alignment procedures will be developed for the lower-level assemblies of SXI.

Source record↗
DOE OSTI2021

Billion-pixel x-ray camera (BiPC-X)

The continuing improvement in quantum efficiency (above 90% for single visible photons), reduction in noise (below 1 electron per pixel), and shrink in pixel pitch (less than 1 μm) enable billion-pixel x-ray cameras (BiPC-X) based on commercial complementary metal–oxide–semiconductor (CMOS) imaging sensors. We describe BiPC-X designs and prototype construction based on flexible tiling of commercial CMOS imaging sensors with millions of pixels. Device models are given for direct detection of low energy x rays (<10 keV) and indirect detection of higher energies using scintillators. Modified Birks’s law is proposed for light yield non-proportionality in scintillators as a function of x-ray energy. Single x-ray sensitivity and spatial resolution have been validated experimentally using a laboratory x-ray source and the Argonne Advanced Photon Source. Possible applications include wide field-of-view or large x-ray aperture measurements in high-temperature plasmas, the state-of-the-art synchrotron, x-ray free electron laser, and pulsed power facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

DINGO: Digital assistant to grid operators for resilience management of power distribution system

With increasing adverse weather events and disasters, enabling resiliency of the power distribution system (PDS) is becoming increasingly important. Here in this work, resiliency is defined as the systems ability to keep supplying critical loads even with multiple contingencies. Resiliency may depend on: (a) advanced tools to assist operators in situational awareness and decision making with the increasing volume of data generated by the PDS, (b) visualization and ease of interaction with system resources and information, especially during extreme events and resulting human operator stress, and (c) flexible resources and autonomous control. Operators and support engineers need to interact with the system for key information and take action under stress, given the requirement for decisions in a short time. Integrated technological solutions are prevailing steps to support the most appropriate decision during critical times to serve essential loads. In order to meet the required goals, a Real-time Resiliency Monitoring and Operational Decision Support (RT-RMOD) tool have been developed. It supports various functionalities, including real-time monitoring, resilience assessment, and proactive decision support. However, this work makes advanced feature additions to the tool by developing data-enabled resilience management algorithms for (i) outage detection and localization, (ii) Resiliency-metric driven restoration and reconfiguration, and (iii) NLP based digital assistant for operators called DINGO (DIgital assistaNt to Grid Operators) to interact with Advanced Distribution Management System (ADMS) and RT-RMOD. The developed algorithm was validated for multiple cases of weather events using a real-world, off-grid microgrid system modeled in a real-time simulator, sensor data, and software tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Integrated Approach to Fluoride High Temperature Reactor Technology and Licensing Challenges (FHR-IRP)

This document constitutes progress made on this project by the Georgia Tech led Integrated Approach to Fluoride High Temperature Reactor Technology and Licensing Challenges (FHR-IRP). This is the first draft of the project final report. Chapter 3 is focused on Tritium management. Tritium management in Fluoride-salt High-temperature Reactors (FHRs) presents a major operational concern and a significant challenge. Tritium is generated via multiple pathways including various interactions in fuel and structural materials, as well as coolant (primarily interaction with lithium and beryllium), leading to a complex evolution and spatial distribution of tritium generation rate. FHR generates orders of magnitude more tritium than in LWRs, and has potential for a significant release, via permeation through structural materials (due to high temperature), and through heat exchanger(s). Therefore, accurate estimate is necessary. For that purpose relevant tritium production pathways were identified. A methodology to obtain space-time dependent tritium generation rate was developed and implemented, employing SCALE and MCNP codes. Detailed models of the reference Advanced High Temperature Reactor (AHTR) design were developed. A multi-parametric metrics was introduced to capture relevant tritium production indicators, including the instantaneous tritium production rate, total tritium production (neglecting subsequent decay), and accumulated tritium production (accounting for the decay). The obtained results will inform tritium management, including the sizing of the components, and to gain insight on the impact of the core design parameters on tritium generation rates. Research effort on Liquid Salt Impurity Removal, Redox and Corrosion Control is discussed in Chapter 4. Section 4.1 is an introduction chapter. Based on the current available knowledge and operation experience on previous MSRs and other types of nuclear reactors, the report identifies the major impurities that are related to either material compatibility, salt properties or radioactive source terms, and the potential contamination sources of these impurities, their transport in the primary coolant loop and available cleanup methodologies for a particular group of impurity. In section 4.2, the available purification methods were discussed, including the liquid/liquid extraction using liquid Bi-Li which has been applied in MSBR and electrochemical purification which is developed based on Pyroprocessing. In this section, the new multi-stage and multi-salt-component was developed and discussed. Section 4.3 discussed the redox potential control for salt chemistry and corrosion mitigation, including the control theory and the soluble/soluble buffer control method. The section also developed method on how to analyze soluble/soluble redox reaction in a molten salt system and designed an electrochemical sensor for redox potential control. Corrosion models were also reported in this section. Section 4.4 focused on how to measure the fundamental properties in a molten salt. As an example, the section focused on La fluoride in the molten salt. The section developed methods on how analyze electrochemical measurement data to obtain the fundamental properties including the redox potential, diffusion coefficient and exchange current density. All these fundamental information is important for salt purification system development. Section 4.5 focused on measurements of corrosion products in the salts. Because of the different behaviors between Cr and La in the salt, new analysis method for Cr fluorides in the salt was developed. Some results for Fe fluoride in the salt and corrosion measurements were also reported. Section 4.6 demonstrated the separation of oxide from the salt. This section also measured the solubility of La 2 O 3 in the salt as function of temperature. Section 4.7 focused on the separation of La and Ce from the molten salt. These two elements were selected because La was found to be separated by using inert electrode, while for separation of Ce, reactive electrode must be selected. Section 4.8 demonstrated the separation iodine ions from the molten salt. Two kinds of working electrode materials (metal W and graphite) were investigated. Section 4.9 focused on the fundamental data of fission products and actinides in liquid Bi. The chapter reviewed the available data, then based a CALPHAD model, the available data were broadened to the concentration-dependent cases.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2016

MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) Retrieval Algorithm: Towards Extending Multi-Decadal NASA EOS Atmospheric Composition Data Records

Multi-Spectra, Multi-Species, Multi-Sensors (MUSES): Builds off of heritage from the Tropospheric Emission Spectrometer (TES) optimal estimation (OE) algorithm to combine a priori and satellite data, including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation; has generic design to incorporate forward model radiances from hyperspectral measurements from multiple sensors into the joint retrieval algorithm.

Fu, Dejian↗
NASA NTRS1994

Assessment of climate variability of the Greenland Ice Sheet: Integration of in situ and satellite data

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland Ice Sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meteorological data sets. Operational satellite sensors are calibrated based on ground measurements and atmospheric modeling prior to large scale analysis to ensure the quality of the satellite data. Further, several satellite sensors of different spatial and spectral resolution are intercompared to access the parameter accuracy. Proposed parameterization schemes to derive key component of the energy balance from satellite data are validated. For the understanding of the surface processes a field program was designed to collect information on spectral albedo, specular reflectance, soot content, grain size and the physical properties of different snow types. Further, the radiative and turbulent fluxes at the ice/snow surface are monitored for the parameterization and interpretation of the satellite data. The expected results include several baseline data sets of albedo, surface temperature, radiative fluxes, and different snow types of the entire Greenland Ice Sheet. These climatological data sets will be of potential use for climate sensitivity studies in the context of future climate change.

Steffen, K.↗
NASA NTRS2002

Navigation Algorithms for the SeaWiFS Mission

The navigation algorithms for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) were designed to meet the requirement of 1-pixel accuracy-a standard deviation (sigma) of 2. The objective has been to extract the best possible accuracy from the spacecraft telemetry and avoid the need for costly manual renavigation or geometric rectification. The requirement is addressed by postprocessing of both the Global Positioning System (GPS) receiver and Attitude Control System (ACS) data in the spacecraft telemetry stream. The navigation algorithms described are separated into four areas: orbit processing, attitude sensor processing, attitude determination, and final navigation processing. There has been substantial modification during the mission of the attitude determination and attitude sensor processing algorithms. For the former, the basic approach was completely changed during the first year of the mission, from a single-frame deterministic method to a Kalman smoother. This was done for several reasons: a) to improve the overall accuracy of the attitude determination, particularly near the sub-solar point; b) to reduce discontinuities; c) to support the single-ACS-string spacecraft operation that was started after the first mission year, which causes gaps in attitude sensor coverage; and d) to handle data quality problems (which became evident after launch) in the direct-broadcast data. The changes to the attitude sensor processing algorithms primarily involved the development of a model for the Earth horizon height, also needed for single-string operation; the incorporation of improved sensor calibration data; and improved data quality checking and smoothing to handle the data quality issues. The attitude sensor alignments have also been revised multiple times, generally in conjunction with the other changes. The orbit and final navigation processing algorithms have remained largely unchanged during the mission, aside from refinements to data quality checking. Although further improvements are certainly possible, future evolution of the algorithms is expected to be limited to refinements of the methods presented here, and no substantial changes are anticipated.

Hooker, Stanford B.↗
DOE OSTI2020

A radiative transfer model for solar induced fluorescence using spectral invariants theory

Solar Induced chlorophyll Fluorescence (SIF) shows promise as an approach for estimating gross primary production (GPP) remotely. However, sun-target-sensor geometry and within-canopy absorption of SIF can alter the relationship between measured SIF and GPP, because sensors can only retrieve some unknown fraction of the total emitted SIF. Radiative transfer models that allow for variation in canopy structure and sensor angles are therefore needed to properly interpret SIF measurements. Spectral invariants allow decoupling of the wavelength-independent canopy structure and the wavelength-dependent leaf and soil spectrum in the radiative transfer process. Here we develop a simple analytical Fluorescence Radiative Transfer model based on Escape and Recollision probability (FluorRTER) to investigate the impact of canopy structure and sun-target-sensor geometry on SIF emissions. SIF simulations using the FluorRTER model agreed well the one-dimensional Soil-Canopy Observation of Photochemistry and Energy balance (SCOPE) model and the three-dimensional Fluorescence model with Weighted Photon Spread (FluorWPS) model. The fractional vegetation cover (FVC) and clumping effect have a large influence the SIF emission of 3D discontinuous canopies. For a moderate solar zenith angle (30°) and a clumped canopy (FVC?=?0.6), the difference between the directional observed SIF of a 3D discontinuous canopy and a 1D homogeneous canopy was as large as 43.2% and 38.4% for Photosystem I?+?II fluorescence at 685?nm and at 740?nm, respectively. By bridging the gap between observed SIF and total emitted SIF over 3D heterogeneous vegetation canopies, the FluorRTER model can assist with the angular normalization of SIF measurements and enable the more robust interpretation of how variations in SIF from directional and hemispherical in-situ, airborne and satellite observations relate to leaf and whole-canopy physiological processes.

Zeng, Yelu↗
DOE OSTI2022

Evaluating Image Classification Deep Convolutional Neural Network Architectures for Remaining Useful Life Estimation of Turbofan Engines

Accurate estimation of the remaining useful life (RUL) is a key component of condition-based maintenance (CBM) and prognosis and health management (PHM). Data-based models for the estimation of RUL are of particular interest because expert knowledge of systems is not always available, and physical modeling is often not feasible. Additionally, using data-based models, which make decisions based on raw sensor data, allow features to be learned instead of manually determined. In this work, deep convolutional neural network (CNN) architectures are investigated for their ability to estimate the RUL of turbofan engines. To improve the accuracy of the models, CNN architectures, which have proven successful in image classification, are implemented and tested. Specifically, the blocks used in the Visual Geometry Group (VGG) architecture, inception modules used in the GoogLeNet architecture, and residual blocks used in the ResNet architecture are incorporated. To account for varying flight lengths, the input to the models is a window of time series data collected from the engine under test. Window locations at the climb, cruise, and descent stages are considered. To further improve the RUL estimations, multiple overlapping windows at each location are used. This increases the amount of training data available and is found to increase the accuracy of the resulting RUL estimations by averaging the estimates from all overlapping segments. The model is trained and tested using the new Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) data set, and high prognosis accuracy was achieved. Furthermore, this work expands on the model developed and used in the 2021 PHM Society Data Challenge, which received second place.

convolutional neural networks↗
NASA NTRS2014

Amazon Forests Maintain Consistent Canopy Structure and Greenness During the Dry Season

The seasonality of sunlight and rainfall regulates net primary production in tropical forests. Previous studies have suggested that light is more limiting than water for tropical forest productivity, consistent with greening of Amazon forests during the dry season in satellite data.We evaluated four potential mechanisms for the seasonal green-up phenomenon, including increases in leaf area or leaf reflectance, using a sophisticated radiative transfer model and independent satellite observations from lidar and optical sensors. Here we show that the apparent green up of Amazon forests in optical remote sensing data resulted from seasonal changes in near-infrared reflectance, an artefact of variations in sun-sensor geometry. Correcting this bidirectional reflectance effect eliminated seasonal changes in surface reflectance, consistent with independent lidar observations and model simulations with unchanging canopy properties. The stability of Amazon forest structure and reflectance over seasonal timescales challenges the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions. Correcting optical remote sensing data for artefacts of sun-sensor geometry is essential to isolate the response of global vegetation to seasonal and interannual climate variability.

dry season↗
NASA NTRSDate not supplied

Operational Experience with the Electromagnetic Position Sensor (EPS) for the NASA 6-inch MSBS

We rebuilt the wind tunnel model position signal conditioner for the MIT 6-Inch Magnetic Suspension and Balance System (MSBS) Electromagnetic Position Sensor (EPS) that is now in use at the NASA Langley Research Center (LaRC). The effort began at LaRC in ~1990 to replace the original MIT system that was still operating with the low speed wind tunnel until its decommissioning a few years later. The MIT filtering and demodulating scheme mostly remained in the newly designed two-layer printed circuit boards (PCB) with some rearranging of order. The finished product was hampered by noise problems due to problematic grounding design etc. and never successfully operated in the MSBS. After over 20 years, the Langley unit was recovered from Old Dominion University where the MSBS was on loan from NASA but never refurbished. The EPS was brought back to LaRC in 2015 while planning for the return of the MSBS and work began to evaluate its condition and acquire supporting instrumentation. The repair, testing, operational issues, and future improvements are discussed along with an overview of the EPS as a subsystem.

Timothy D Schott↗
DOE OSTI2023

2023 Real-time Optimization Workflow Status Update

Nuclear integrated energy systems are composed of a diverse set of energy generation sources and exist in dynamic and competitive electricity markets. With the inclusion of thermal energy storage, nuclear power systems can store heat for future use through various processes, such as water desalination or hydrogen generation. This heat storage can be managed in such a way as to economically optimize its usage. By combining real-time price data from the day-ahead and real-time markets with predictive and intelligent models, the charging and discharging of the thermal energy storage may be determined and optimized. This research details an approach through models and systems for the real-time optimization (RTO) of capacity allocation. Virtual models of the energy system and its physics phenomenon and component interactions provide intelligence to verification and prediction of operations. An optimization framework can use data generated from both a set of physical assets as well as the virtual models to predict future performance and create optimization and control workflows. Data warehouse technologies can be used to combine data across models, optimization workflows, market price data, and sensor data to intuitively store various types of data and provide integrations to physical control systems as well as user visualizations. Put together, these components can create a system for the RTO of nuclear integrated energy systems. Various virtual models and bench-scale physical demonstrations have been successfully performed and verified using this system. Larger scale testbeds that include thermal energy storage systems have been identified as future opportunities. A gap analysis that details the steps necessary to reach a physical demonstration at this scale is provided, along with conclusions on the current effort and future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Comparing Control Performance Between Simulation and Experiment using the Microreactor Automated Control System Testbed

In the advanced reactor domain, a flexible and scalable software/hardware infrastructure is crucial for integrating and validating various control technologies. This study used the Microreactor Automated Control System (MACS) hardware platform as a testbed. MACS was originally designed to mirror Idaho National Laboratory (INL)'s Microreactor Applications Research Validation and Evaluation (MARVEL), a 85-kW thermal fission microreactor. It features control drums for simulated reactivity control; lights that function as a surrogate reactor core, with the brightness being proportional to the reactor power; and light sensors that emulate neutron detectors. To transform MACS into a physical twin of MARVEL for evaluating control methods, the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software was employed. This software integrated the hardware with two models of the MARVEL core, based on Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The study aimed to demonstrate the gap between control theory and actual practice—a gap that often necessitates empirical adjustments such as control gain retuning, filters, time discretization, and integrator anti-windup measures. Controllers were developed based on increasingly complex simulations without hardware, starting from the base MARVEL model and then introducing actuator saturation constraints and sensor noise. The final control strategy was then tested using MACS, and a comparative performance analysis was conducted.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗