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NASA NTRS2021

Terra MODIS Sees Solar Eclipses: Analysis of Reflective Solar Band Response at Multiple Radiance Levels

The MODIS imaging spectroradiometer instruments on-board NASA's Terra and Aqua satellites have 20 reflective solar bands (RSB) covering a wavelength range from 400 to 2200 nm. Radiance is calculated from processing raw signals with background, temperature, and electronic contamination corrected. Measured gain is calibrated with a fully Sunlit solar diffuser (SD) at a stable radiance level, considering a slowly changing SD reflectance degradation. These measurements provide time-dependent gain adjustment factors, and the calibration assumes a linear response for each band and detector. Hence, an analysis of the dependence on different radiance levels is warranted. The MODIS design has no mechanism for varying radiance levels, except for an attenuator screen. However, it has been in static configuration for Terra since mid-2003. An external source of radiance attenuation can be utilized during solar eclipse events, while maintaining high stability and accuracy of solar calibration standards. Due to its long mission lifetime, Terra has seen several Sun-Moon near-conjunction events when it coincides with the orbit path where the SD is directly illuminated. As of August 2020, we have identified 7 viable partial solar eclipses in the Terra mission data. We will discuss several results of our study, including comparison of measured SD signal to predicted radiance reduction based on a solar disk radiance model; nominal and outlier behavior as a function of bands, detectors, and mirror-sides; and comparison with other data sets. Our main conclusion from this study is that there is no notable correlation of detector-dependent trend with radiance level for most RSB bands.

Terra↗
NASA NTRS2023

The Complexity of the Day-Side X-Line During Southward Interplanetary Magnetic Field

High-resolution global magnetohydrodynamics (MHD) simulations include both meso- and global-scale processes occurring at the magnetopause, which interact to determine the time-dependent orientation of the day-side x-line (DXL). This study demonstrates that the global orientation of the DXL in GAMERA global MHD simulations varies on a time scale of minutes during steady southward interplanetary magnetic field conditions. This behavior manifests in observational data when reconnection outflows indicate that the direction to the x-line is opposite to the prediction from a steady-state model of the reconnection location. Because steady-state models of the DXL do not capture dynamics that are independent of solar wind variations, particularly surface waves and flux transfer events, they represent a time-averaged state of the system.

Brandon Burkholder↗
NASA NTRS2023

A Data-driven, Physics-based Transport Model of Solar Energetic Particles Accelerated by Coronal Mass Ejection Shocks Propagating through the Solar Coronal and Heliospheric Magnetic Fields

In an effort to develop computational tools for predicting radiation hazards from solar energetic particles (SEPs), we have created a data-driven physics-based particle transport model to calculate the injection, acceleration, and propagation of SEPs from coronal mass ejection (CME) shocks traversing through the solar corona and interplanetary magnetic fields. The model runs on an input of corona and heliospheric plasma and magnetic field configuration from a magnetohydrodynamic model driven by solar photospheric magnetic field measurements superposed with observed CME shocks determined from coronagraph images. SEP source particles are injected at the shock using the result of diffusive shock acceleration formulation from a characteristic obliquity-dependent injection from a heated solar wind thermal tail population. With several advanced computation techniques involving stochastic simulation and integration, the model obtains the particle intensity at any location in interplanetary space through the rigorous solution to the time-dependent 5D focus transport equation in the phase space that includes perpendicular diffusion. We apply the model to the 2011 November 3 CME event. The calculation results reproduce multispacecraft SEP observations at Earth and STEREO-B reasonably well without normalization of particle flux. The observations at STEREO-A can be reproduced by rescaling particle energy or modified energy dependence of particle diffusion coefficients. This circumsolar SEP event seen by spacecraft at Earth, STEREO-A, and STEREO-B at widely separated longitudes can be explained by diffusive shock acceleration by a single CME shock with a moderate speed.

Solar energetic particles↗
NASA NTRS2024

A Feasibility Study of 4-D Tomography of Soft X-ray Magnetosheath Emissivities Using Multi-Spacecraft Measurements

Upcoming heliophysics missions utilize state-of-the-art wide field-of-view (FOV) imaging technology to measure and investigate the space plasma environment on a global scale. At Earth, remote sensing of soft X-ray emissions, which are generated via the charge exchange interaction between heavy solar wind ions and exospheric neutral atoms, is a promising means to investigate the global magnetosheath structure, its response to varying solar wind conditions, and the spatiotemporal properties of the dayside magnetic reconnection. Data analysis techniques such as optical tomography can provide additional structural and time-varying information from the observed target and thus enhance the mission’s scientific return. In this work, we simulate multiple and simultaneous observations of the dayside magnetosphere using soft X-ray imagers located at long-distance vantage points to reconstruct the time-dependent, three-dimensional (3-D) structure of the magnetosheath using a dynamic tomographic approach. The OpenGCCM MHD model is used to simulate the time-varying response of the magnetosheath to solar wind conditions and, subsequently, generate synthetic soft X-ray images from multiple spacecraft vantage points separated along a common orbit. A detailed analysis is then performed to identify the nominal set of spacecraft that produces the highest fidelity tomographic reconstruction of the magnetopause. This work aims to (i) demonstrate, for the first time, the use of dynamic tomography to retrieve the time-varying magnetosheath structure and (ii) identify a nominal mission design for multi-spacecraft configurations aiming for optical tomography.

3-D/4_d tomography↗
NASA NTRS2024

Applications of ArcticDEM for measuring volcanic dynamics, landslides, retrogressive thaw slumps, snowdrifts, and vegetation heights

Topographical changes are of fundamental interest to a wide range of Arctic science disciplines faced with the need to anticipate, monitor, and respond to the effects of climate change, including geohazard management, glaciology, hydrology, permafrost, and ecology. This study demonstrates several geomorphological, cryospheric, and biophysical applications of ArcticDEM – a large collection of publicly available, time-dependent digital elevation models (DEMs) of the Arctic. Our study illustrates ArcticDEM's applicability across different disciplines and five orders of magnitude of elevation derivatives, including measuring volcanic lava flows, ice cauldrons, post-failure landslides, retrogressive thaw slumps, snowdrifts, and tundra vegetation heights. We quantified surface elevation changes in different geological settings and conditions using the time series of ArcticDEM. Following the 2014–2015 Bárðarbunga eruption in Iceland, ArcticDEM analysis mapped the lava flow field, and revealed the post-eruptive ice flows and ice cauldron dynamics. The total dense-rock equivalent (DRE) volume of lava flows is estimated to be (1431 ± 2) million m 3 . Then, we present the aftermath of a landslide in Kinnikinnick, Alaska, yielding a total landslide volume of (400 ± 8) × 103 m 3 and a total area of 0.025 km 2 . ArcticDEM is further proven useful for studying retrogressive thaw slumps (RTS). The ArcticDEM-mapped RTS profile is validated by ICESat-2 and drone photogrammetry resulting in a standard deviation of 0.5 m. Volume estimates for lake-side and hillslope RTSs range between 40,000 ± 9000 m 3 and 1,160,000 ± 85,000 m 3 , highlighting applicability across a range of RTS magnitudes. A case study for mapping tundra snow demonstrates ArcticDEM's potential for identifying high-accumulation, late-lying snow areas. The approach proves effective in quantifying relative snow accumulation rather than absolute values (standard deviation of 0.25 m, bias of −0.41 m, and a correlation coefficient of 0.69 with snow depth estimated by unmanned aerial systems photogrammetry). Furthermore, ArcticDEM data show its feasibility for estimating tundra vegetation heights with a standard deviation of 0.3 m (no bias) and a correlation up to 0.8 compared to the light detection and ranging (LiDAR). The demonstrated capabilities of ArcticDEM will pave the way for the broad and pan-Arctic use of this new data source for many disciplines, especially when combined with other imagery products. The wide range of signals embedded in ArcticDEM underscores the potential challenges in deciphering signals in regions affected by various geological processes and environmental influences.

Chunli Dai↗
NASA NTRSDate not supplied

High-Fidelity Modeling Approach for Coupling Thermal, Fluid, and Neutronic Analysis in an NTP Engine

Nuclear thermal propulsion (NTP), with its increased efficiency compared to traditional rocket engines, is a potentially enabling technology for space missions of higher complexity, such as delivering heavy machinery or crew to the moon or other planets. Thus, exploring modeling approaches that can effectively couple the thermal, fluid, and neutronic behaviors of NTP reactors is essential to mitigate cost and schedule challenges with hardware development. This paper details one such approach which utilizes Cardinal to unify reactor physics analysis performed using OpenMC, heat transfer analysis performed using the MOOSE framework, and thermal hydraulic analysis performed using the MOOSE Thermal Hydraulic Module. This approach is demonstrated with a proof of concept that focuses on a legacy reactor geometry from the historic NERVA program. This preliminary model found an overprediction in, when compared to the reference data, axial power peaking and the temperatures of both solids and fluids by roughly 20%. It is clear, however, that the model conserved a number of broad trends, and a few model refinements should reduce the observed error. This approach has definite merit and should enable the production of informative results for more modern NTP systems. This work is a first step in creating a transient reactor model that can be updated across a sequence of time steps based on continually fluctuating, time-dependent boundary conditions.

Nuclear Thermal Propulsion↗
DOE OSTI2011

Measurement of $D^0-overline{D}^0$ mixing parameters using $D^0 \to K_S^0 \pi^ \pi^-$ and $D^0 \to K_S^0 K^ K^-$ decays

We report a direct measurement of D{sup 0}-{bar D}{sup 0} mixing parameters through a time-dependent amplitude analysis of the Dalitz plots of D{sup 0} {yields} K{sub S}{sup 0}{pi}{sup +}{pi}{sup -} and, for the first time, D{sup 0} {yields} K{sub S}{sup 0}K{sup +}K{sup -} decays. The low-momentum pion {pi}{sub s}{sup +} in the decay D*{sup +} {yields} D{sup 0}{pi}{sub s}{sup +} identifies the flavor of the neutral D meson at its production. Using 468.5 fb{sup -1} of e{sup +}e{sup -} colliding-beam data recorded near {radical}s = 10.6 GeV by the BABAR detector at the PEP-II asymmetric-energy collider at SLAC, we measure the mixing parameters x = [1.6 {+-} 2.3 (stat.) {+-} 1.2 (syst.) {+-} 0.8 (model)] x 10{sup -3}, and y = [5.7 {+-} 2.0 (stat.) {+-} 1.3 (syst.) {+-} 0.7 (model)] x 10{sup -3}. These results provide the best measurement to date of x and y. The knowledge of the value of x, in particular, is crucial for understanding the origin of mixing.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

A COUPLED TH/NEUTRONICS/CRUD FRAMEWORK IN PREDICTION OF CIPS PHENOMENON

A coupled TH/Neutronics/CRUD framework, which is able to simulate the CRUD deposits impact on CIPS phenomenon, was described in this paper. This framework includes the coupling among three essential physics, thermal-hydraulics, CRUD and neutronics. The overall framework was implemented by using the CFD software STAR-CCM+, developing CRUD codes, and using the neutronics code DeCART. The coupling was implemented by exchanging data between softwares using intermediate exchange files. A typical 3 by 3 PWR fuel pin problem was solved under this framework. The problem was solved in a 12 months length period of time. Time-dependent solutions were provided, including CRUD deposits inventory and their distributions on fuels, boron hideout amount inside CRUD deposits, as well as power shape changing over time. The results clearly showed the power shape suppression in regions where CRUD deposits exist, which is a strong indication of CIPS phenomenon.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Dynamic modeling of a single-stage downward firing, entrained flow gasifier

The gasifier is the heart of the integrated gasification combined cycle (IGCC), a technology that has emerged as an attractive alternative to conventional coal-fired power plant technology due to its higher efficiency and cleaner environmental performance especially with the option of CO{sub 2} capture and sequestration. Understanding the optimal performance of the gasifier is therefore paramount for the efficient operation of IGCC power plants. Numerous gasifier models of varying complexity have been developed to study the various aspects of gasifier performance. These range from simple one-dimensional (1D) process-type models to rigorous higher order 2-3D models based on computational fluid dynamics (CFD). Whereas high-fidelity CFD models can accurately predict most key aspects of gasifier performance, they are computationally expensive and typically take hours to days to execute on high-performance computers. Therefore, faster 1D partial differential equation (PDE)-based models are required for use in dynamic simulation studies, control system analysis, and training applications. A number of 1D gasifier models can be found in the literature, but most are steady-state models that have limited application in the practical operation of the gasifier. As a result, 1D PDE-based dynamic models are needed to further study and predict gasifier performance under a wide variety of process conditions and disturbances. In the current study, a 1D transient model of a single-stage downward-fired GE/Texaco-type entrained-flow gasifier has been developed. The model comprises mass, momentum and energy balances for the gas and solid phases. The model considers the initial gasification processes of water evaporation and coal devolatilization. In addition, the key heterogeneous and homogeneous chemical reactions have been modeled. The resulting time-dependent PDE model is solved using the well-known method of lines approach in Aspen Custom Modeler®, whereby the PDEs in the spatial domain are discretized and the resulting differential algebraic equations (DAEs) are then integrated over time using a dynamic integrator. The dynamic response results of the gasifier performance parameters to certain disturbances commonly encountered during practical operation are presented. These disturbances include ramp and step changes to input variables such as coal flow rate, oxygen-to-coal ratio and water-to-coal ratio among others. Comparison of model predictions to available dynamic data will also be discussed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset

The primary objective of this research is to address challenges in the implementation of risk-informed, condition-based predictive maintenance (PdM), which reduces operating costs while still maintaining the safety and reliability of commercial nuclear power plants (NPPs). To achieve the objective, risk models are being developed by taking advantage of advancements in data analytics, deep learning, machine learning (ML), and artificial intelligence (AI). The notable outcomes presented in the report include ? Development of a ML models using heterogeneous plant process and vibration data collected at different spatial and temporal resolutions from the Salem?s CWS to diagnose a circulating water pump (CWP) failure based on salient fault signatures. The developed diagnostic models are extendable to other faults associated with CWPs and CWP motors given associated fault signatures. ? Development of a natural language processing (NLP) technique to automatically classify the WO data into different categories. The developed NLP technique was validated on independent WO data. This automates the tedious and time-consuming activity of mining and classifying WOs by subject matter experts. ? Estimation of mean time between downtime (i.e., time duration between time instances when 1 or more CWPs are not available) and developed an approach to establish reliability of CWS components using unstructured WO data along with CWS plant process data. ? Formulation of economic model based on Markov chain models. The parameters of associated with the transition rate between different states of Markov chain models were estimated using WO data. The economic model formulation and discussion captures both time-independent and time-dependent parameter variation, leading to risk-informed decision-making.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Examination of Digital-Delay Rossi-$\alpha$ for 252 Cf-Driven Highly Enriched Uranium Using Organic Scintillators

Neutron noise techniques constitute several analysis methods applicable to non-destructive assay. One technique is the Rossi-α method to calculate the prompt neutron decay constant (α) or its inverse, the prompt neutron period (1/α), for assemblies of fissionable material. This work evaluates a high-data-throughput measurement at the National Criticality Experiments Research Center (NCERC) with organic scintillators measuring a subcritical assembly of highly enriched uranium (HEU) metal (93% 235 U). The assembly comprises hemi shells stacked together to form fully closed shells and is driven by a Cf source at the center. The assembly is a total of 59.85 kg HEU and a k eff of 0.99, according to MCNP6.2 KCODE simulations. Measurements were acquired with a three-by-four array of 5.08-cm-diameter by 5.08-cm-length trans-stilbene crystals 166 cm from the assembly center. Two types of coincident binning methods are used to build the Rossi-α distribution of coincident neutron detections: A) type 1 binning, also known as any-and-all forward time differences, and B) type 1 binning with a digital-delay technique that is analogous to Orndoff’s use of delay cabling in early Rossi-alpha measurements. Method B) disregards same-detector coincidences and once all nearest time coincidences are collected between all detectors after a trigger, a time delay of 0.75 µs is implemented. The measured prompt neutron decay constants for both techniques are calculated from single exponential fits and the two methods are compared. Method A) shows an apparent timing discontinuity near 500 ns time differences. This timing discontinuity interferes with the fitting method used to calculate the prompt neutron decay constant. Method B) mitigates the artificial timing discontinuity and removes the disagreement of the fit. Future work will model the time-dependent detector response to discern why this timing discontinuity occurs, discern how Method B) reduces the amplitude of this timing discontinuity, and apply this method to critical assembly measurements to ultimately confirm the recommendation to use Method B) for high-data-throughput measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Level 1 transient model for a molybdenum-99 producing aqueous homogeneous reactor and its applicability to the tracy reactor

Babcock and Wilcox Technical Services Group (B and W) has identified aqueous homogeneous reactors (AHRs) as a technology well suited to produce the medical isotope molybdenum 99 (Mo-99). AHRs have never been specifically designed or built for this specialized purpose. However, AHRs have a proven history of being safe research reactors. In fact, in 1958, AHRs had 'a longer history of operation than any other type of research reactor using enriched fuel' and had 'experimentally demonstrated to be among the safest of all various type of research reactor now in use [1].' A 'Level 1' model representing B and W's proposed Medical Isotope Production System (MIPS) reactor has been developed. The Level 1 model couples a series of differential equations representing neutronics, temperature, and voiding. Neutronics are represented by point reactor kinetics while temperature and voiding terms are axially varying (one-dimensional). While this model was developed specifically for the MIPS reactor, its applicability to the Japanese TRACY reactor was assessed. The results from the Level 1 model were in good agreement with TRACY experimental data and found to be conservative over most of the time domains considered. The Level 1 model was used to study the MIPS reactor. An analysis showed the Level 1 model agreed well with a more complex computational model of the MIPS reactor (a FETCH model). Finally, a significant reactivity insertion was simulated with the Level 1 model to study the MIPS reactor's time-dependent response. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2013

Comparison of MCNP6 and experimental results for neutron counts, Rossi-{alpha}, and Feynman-{alpha} distributions

MCNP6, the general-purpose Monte Carlo N-Particle code, has the capability to perform time-dependent calculations by tracking the time interval between successive events of the neutron random walk. In fixed-source calculations for a subcritical assembly, the zero time value is assigned at the moment the neutron is emitted by the external neutron source. The PTRAC and F8 cards of MCNP allow to tally the time when a neutron is captured by {sup 3}He(n, p) reactions in the neutron detector. From this information, it is possible to build three different time distributions: neutron counts, Rossi-{alpha}, and Feynman-{alpha}. The neutron counts time distribution represents the number of neutrons captured as a function of time. The Rossi-a distribution represents the number of neutron pairs captured as a function of the time interval between two capture events. The Feynman-a distribution represents the variance-to-mean ratio, minus one, of the neutron counts array as a function of a fixed time interval. The MCNP6 results for these three time distributions have been compared with the experimental data of the YALINA Thermal facility and have been found to be in quite good agreement. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

A variable-order time-dependent neutron transport method for nuclear reactor kinetics using analytically-integrated space-time characteristics

A new time-dependent neutron transport method based on the method of characteristics (MOC) has been developed. Whereas most spatial kinetics methods treat time dependence through temporal discretization, this new method treats time dependence by defining the characteristics to span space and time. In this implementation regions are defined in space-time where the thickness of the region in time fulfills an analogous role to the time step in discretized methods. The time dependence of the local source is approximated using a truncated Taylor series expansion with high order derivatives approximated using backward differences, permitting the solution of the resulting space-time characteristic equation. To avoid a drastic increase in computational expense and memory requirements due to solving many discrete characteristics in the space-time planes, the temporal variation of the boundary source is similarly approximated. This allows the characteristics in the space-time plane to be represented analytically rather than discretely, resulting in an algorithm comparable in implementation and expense to one that arises from conventional time integration techniques. Furthermore, by defining the boundary flux time derivative in terms of the preceding local source time derivative and boundary flux time derivative, the need to store angularly-dependent data is avoided without approximating the angular dependence of the angular flux time derivative. The accuracy of this method is assessed through implementation in the neutron transport code DeCART. The method is employed with variable-order local source representation to model a TWIGL transient. The results demonstrate that this method is accurate and more efficient than the discretized method. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Calculating infinite-medium {alpha}-eigenvalue spectra with a transition rate matrix method

The time-dependent behavior of the energy spectrum in neutron transport was investigated with a formulation, based on continuous-time Markov processes, for computing {alpha}-eigenvalues and eigenvectors in an infinite medium. For this, a research Monte Carlo code called TORTE was created and used to estimate elements of a transition rate matrix. TORTE is capable of using both multigroup and continuous-energy nuclear data, and verification was performed. Eigenvalue spectra for infinite homogeneous mixtures were obtained and an eigenfunction expansion was used to investigate transient behavior of the neutron energy spectrum. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Pseudo-dynamic Aspen Plus{sup R} Model of the Defense Waste Processing Facility - 18475

The Defense Waste Processing Facility (DWPF) at the Savannah River Site converts legacy high-level waste from the Cold War into borosilicate glass for permanent disposal in a geological repository. The waste sludge is chemically adjusted by the addition of acid, mixed with frit, and concentrated in the DWPF Chemical Process Cell (CPC) to ensure that the final glass has the desired properties. The resulting mixture is fed into the melter where the waste is melted and poured into stainless steel storage canisters. We present an Aspen Plus{sup R} model of the DWPF CPC, which is being developed to aid chemical processing decisions pertaining to the current flowsheet and to aid decisions regarding optimizing future processing. Given a waste feed composition with acid and frit additions, the model will predict the sludge and off-gas compositions throughout the processing, as well as the final melter feed composition. This allows different processing scenarios to be investigated easily, reducing the reliance on experimental testing, and hence saving time and money. The model has multiple potential applications, including calculating the acid and frit additions required to give acceptable glass properties, off-gas permitting, tracking mercury steam-stripped from the waste in the off-gas system, tracking flammable gases in the offgas system, investigating the effect of reducing air purges in the condensers, and general process optimization. The waste is processed in the CPC in batches, requiring dynamic simulation to track the time-dependent operations. Accurate modeling of the processing also requires calculations of phase and electrolyte chemical equilibria and parallel rate-dependent reactions. Due to existing technical limitations with dynamic simulation of the complex chemical system, we have adopted a pseudo-dynamic approach in which time intervals are treated as consecutive steady-state operations in Aspen Plus{sup R}. Thus, the model consists of ∼100 replicas of the processing vessel and its off-gas system, with the sludge output by one replica (representing one time interval) becoming the feed to the next (representing the next time interval). By examining the results from these replicas in sequence, one can see the time evolution of the model. This general approach can be used wherever simultaneous calculation of phase and electrolyte chemical equilibria in a dynamically evolving system is needed. In addition to describing the general structure and chemistry of the model, we present results from tests of the model against experimental data. These data are from laboratory-scale process simulations of the CPC with a nonradioactive waste sludge simulant. These tests include the model's predictions of the offgas composition, the sludge pH, and the final sludge composition. We will also discuss planned future developments of the model. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Benchmarking of Different Inverse Point Kinetics Implementations for an Autocorrected Reactimeter Algorithm

In November 2017, the Transient Reactor Test Facility returned to operation. Since that time, many transient test series have been completed; each has provided valuable data for materials performance, reactor safety that can be applied in future designs. During each experimental series, detector count rates provided important information on the core behavior during transients. However, a limitation of these data is that variations in the neutron distribution during experiments cause errors when attempting to infer reactivity evolution from detector signals. Neutron physics codes can be used to compute the flux shape variations. However, this is a poor solution when the experimental data is used to do verification, validation and uncertainty quantification (VVUQ) on codes. Indeed, if the output of the code is used both as a reference and to correct what the reference is compared to, the circular dependency limits the quality of the VVUQ approach. To overcome this problem, an Autocorrected Reactimeter Algorithm (ACRA) has been developed. This approach infers time-dependent reactivity evolution by testing different spatial corrections and selecting the one that minimizes reactivity variations when the core is in a frozen configuration (i.e. when there is no variation in parameters affecting reactivity). However, the scope of this method was limited to transients where there were negligible thermal feedback. Indeed, the core is never in a frozen configuration when the fuel temperature varies during the whole transient. This is our motivation for the development of an improved version of the ACRA which does not require frozen configurations

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

(Doublon) Benchmarking of Different Inverse Point Kinetics Implementations for an Autocorrected Reactimeter Algorithm

In November 2017, the Transient Reactor Test Facility returned to operation. Since that time, many transient test series have been completed, such as the Transient Heatsink Overpower Response capsule (THOR), the Transient Water Irradiation System for TREAT (TWIST), and Sirius. Each has provided valuable data for materials performance and reactor safety that can be applied in future designs. During each experimental series, detector count rates provided important information on the core behavior during transients. However, a limitation of these data is that variations in the neutron distribution during experiments can cause errors when attempting to infer reactivity evolution from detector signals. Neutron physics codes can be used to compute the flux shape variations. However, this is a poor solution when the experimental data is used for code verification, validation and uncertainty quantification. Indeed, if the output of the code is used both as a reference and to correct what the reference is compared to, the circular dependency limits the quality of the verification, validation and uncertainty quantification approach. To overcome this problem, the autocorrected reactimeter algorithm (ACRA) has been developed. This approach infers a time-dependent reactivity evolution by testing different spatial corrections and selecting the one that minimizes reactivity variations when the core is in a frozen configuration (i.e., when there is no variation in parameters affecting reactivity). However, the scope of this method was limited to transients where there were negligible thermal feedback. Indeed, the core is never in a frozen configuration when the fuel temperature varies during the whole transient. This is our motivation for developing an improved version of the ACRA that does not require frozen configurations. To develop this new algorithm, we need a precise and unbiased implementation of the inverse point kinetic equations (IPKEs) as any error in the reactivity evaluation will be propagated into the choice of the optimal spatial correction. Indeed, the previous reactimeter algorithm would use approximations, such as a negligible flux amplitude derivative, to focus on rapidity. For the numerical validation of ACRA, we aim at absolute error under for reactivity derived from signals similar to the one of this study. In this summary, we test eight different IPKE implementations. Each will process a mockup signal built for this study, similar to those that the future ACRA will process. Each reactivity output will be compared to the reference reactivity that has been used to generate the mockup signal. The implementation minimizing the difference with the reference reactivity will be used in the development of a new ACRA formulation.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗