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NASA NTRS2015

Intercomparison of Martian Lower Atmosphere Simulated Using Different Planetary Boundary Layer Parameterization Schemes

We use the mesoscale modeling capability of Mars Weather Research and Forecasting (MarsWRF) model to study the sensitivity of the simulated Martian lower atmosphere to differences in the parameterization of the planetary boundary layer (PBL). Characterization of the Martian atmosphere and realistic representation of processes such as mixing of tracers like dust depend on how well the model reproduces the evolution of the PBL structure. MarsWRF is based on the NCAR WRF model and it retains some of the PBL schemes available in the earth version. Published studies have examined the performance of different PBL schemes in NCAR WRF with the help of observations. Currently such assessments are not feasible for Martian atmospheric models due to lack of observations. It is of interest though to study the sensitivity of the model to PBL parameterization. Typically, for standard Martian atmospheric simulations, we have used the Medium Range Forecast (MRF) PBL scheme, which considers a correction term to the vertical gradients to incorporate nonlocal effects. For this study, we have also used two other parameterizations, a non-local closure scheme called Yonsei University (YSU) PBL scheme and a turbulent kinetic energy closure scheme called Mellor- Yamada-Janjic (MYJ) PBL scheme. We will present intercomparisons of the near surface temperature profiles, boundary layer heights, and wind obtained from the different simulations. We plan to use available temperature observations from Mini TES instrument onboard the rovers Spirit and Opportunity in evaluating the model results.

Natarajan, Murali↗
NASA NTRS2016

Global Statistical Maps of Extreme-Event Magnetic Observatory 1 Min First Differences in Horizontal Intensity

Analysis is made of the long-term statistics of three different measures of ground level, storm time geomagnetic activity: instantaneous 1 min first differences in horizontal intensity (delta)Bh, the root-mean-square of 10 consecutive 1 min differences S, and the ramp change R over 10 min. Geomagnetic latitude maps of the cumulative exceedances of these three quantities are constructed, giving the threshold(nTmin) for which activity within a 24 h period can be expected to occur once per year, decade, and century. Specifically, at geomagnetic 55deg, we estimate once-per-century (delta)Bh, S, and R exceedances and a site-to-site,proportional, 1 standard deviation range [1(sigma), lower and upper] to be, respectively, 1000, [690, 1450]; 500,[350, 720]; and 200, [140, 280] nTmin. At 40deg, we estimate once-per-century (delta)Bh, S, and R exceedances and1(sigma) values to be 200, [140, 290]; 100, [70, 140]; and 40, [30, 60] nTmin.

Love, Jeffrey J.↗
NASA NTRS2016

Improvement in the Characterization of MODIS Subframe Difference

MODIS is a key instrument of NASA's Earth Observing System. It has successfully operated for 16+ years on the Terra satellite and 14+ years on the Aqua satellite, respectively. MODIS has 36 spectral bands at three different nadir spatial resolutions, 250m (bands 1-2), 500m (bands 3-7), and 1km (bands 8-36). MODIS subframe measurement is designed for bands 1-7 to match their spatial resolution in the scan direction to that of the track direction. Within each 1 km frame, the MODIS 250 m resolution bands sample four subframes and the 500 m resolution bands sample two subframes. The detector gains are calibrated at a subframe level. Due to calibration differences between subframes, noticeable subframe striping is observed in the Level 1B (L1B) products, which exhibit a predominant radiance-level dependence. This paper presents results of subframe differences from various onboard and earth-view data sources (e.g. solar diffuser, electronic calibration, spectro-radiometric calibration assembly, Earth view, etc.). A subframe bias correction algorithm is proposed to minimize the subframe striping in MODIS L1B image. The algorithm has been tested using sample L1B images and the vertical striping at lower radiance value is mitigated after applying the corrections. The subframe bias correction approach will be considered for implementation in future versions of the calibration algorithm.

Li, Yonghong↗
NASA NTRS2015

Differences Between the HUT Snow Emission Model and MEMLS and Their Effects on Brightness Temperature Simulation

Microwave emission models are a critical component of snow water equivalent retrieval algorithms applied to passive microwave measurements. Several such emission models exist, but their differences need to be systematically compared. This paper compares the basic theories of two models: the multiple-layer HUT (Helsinki University of Technology) model and MEMLS (Microwave Emission Model of Layered Snowpacks). By comparing the mathematical formulation side-by-side, three major differences were identified: (1) by assuming the scattered intensity is mostly (96) in the forward direction, the HUT model simplifies the radiative transfer (RT) equation into 1-flux; whereas MEMLS uses a 2-flux theory; (2) the HUT scattering coefficient is much larger than MEMLS; (3 ) MEMLS considers the trapped radiation inside snow due to internal reflection by a 6-flux model, which is not included in HUT. Simulation experiments indicate that, the large scattering coefficient of the HUT model compensates for its large forward scattering ratio to some extent, but the effects of 1-flux simplification and the trapped radiation still result in different T(sub B) simulations between the HUT model and MEMLS. The models were compared with observations of natural snow cover at Sodankyl, Finland; Churchill, Canada; and Colorado, USA. No optimization of the snow grain size was performed. It shows that HUT model tends to under estimate T(sub B) for deep snow. MEMLS with the physically-based improved Born approximation performed best among the models, with a bias of -1.4 K, and an RMSE of 11.0 K.

Pan, Jinmei↗
NASA NTRS2017

Hemispheric Differences in the Annual Cycle of Tropical Lower Stratosphere Transport and Tracers

Transport in the tropical lower stratosphere plays a major role in determining the composition of the entire stratosphere. Previous studies that quantified the relative role of transport processes have generally assumed well-mixed tropics and focused on tropical-wide average characteristics. However, it has recently been shown that there is a hemispheric difference in the annual cycle of tropical lower stratosphere ozone and other tracers, with a larger amplitude in the northern tropics (NT) than in the southern tropics (ST). In this study, we examined the ability of chemistry climate models (CCMs) to reproduce the hemispheric differences in ozone (O3) and other tracers (i.e., hydrochloric acid, or HCl and nitrous oxide, or N2O), and then use the CCMs to examine the cause of these differences. Examination of CCM simulations from the CCMVal-2 project shows that the majority of the CCMs produce the observed feature of a larger annual cycle in the NT than ST O3 and other tracers. However, only around a third of the models produce an ozone annual cycle similar to that observed. Transformed Eulerian Mean analysis of two of the CCMs shows that seasonality in vertical advection drives the seasonality in ST O3 and N2O while seasonality of horizontal mixing drives the seasonality in NT O3 and N2O, with a large increase in horizontal mixing during northern summer (associated with the Asian monsoon). Thus, latitudinal and longitudinal variations within the tropics have to be considered to fully understand the balance between transport processes in tropical lower stratosphere.

transport↗
NASA NTRS2018

Tracer Transport Differences: Challenges and Implications for Flux Inversions

This poster demonstrates that different chemistry transport models (CTMs), each extensively validated, can have significant differences in the predicted transport of long-lived trace gases. For carbon dioxide (CO2), this difference is 0.5 ppm or greater in the total column. The value exceeds the nominal retrieval error requirements of the Total Carbon Column Observing Network (TCCON) and the Orbiting Carbon Observatory 2 (OCO-2), which were chosen based on the understanding of the accuracy necessary to infer surface fluxes of CO2 on regional and seasonal scales. This suggests that the transport errors of CTMs play a considerable role in the surface flux inversion of satellite-based measurements of long-lived trace gases and the interpretation of the inferred fluxes requires a careful understanding of this role.

Weir, B.↗
NASA NTRS2018

Subsample Difference Correction for Terra MODIS SWIR Bands 5-7 Using Lunar Observations

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key instruments on board the Terra (EOS (Earth Observing Satellite) AM-1) spacecraft. MODIS has 36 spectral bands ranging in wavelength between 0.4 and 14.2 microns, at three spatial resolutions of 250 meters (bands 1-2), 500 meters (bands 3-7), and 1 kilometer (bands 8-36). For each 1-km sample, the 250-m and 500-m bands use 4 and 2 detectors with each acquiring 4 and 2 subsamples respectively in order to maintain consistent along-scan and along-track resolutions at nadir. The SWIR (Short-Wave Infrared) bands, 57 and 26, share the same focal-plane array as the 1-km thermal emissive bands, 20-25. During one of the two 500-m subsamples for bands 57, sampling of the 1-km bands introduces increased electronic crosstalk contamination, resulting in a subsample difference for both Earth-view and on-board calibrator observations. For this work, we use data from lunar and on-board blackbody observations, which occur at different signal levels for bands 20-25, to derive a correction to the contamination. This correction can be applied to reduce the subsample differences in the MODIS Earth-view data over a wide range of scenes. The impact of this correction on the sensor calibration and Earth-view data will be assessed.

SWIR↗
NASA NTRS2019

Uniaxial Tensile Properties of AS4 3D Woven Composites with Four Different Resin Systems: Experimental Results and Analysis: Property Computations

As a part of the NASA Composite Technology for Exploration project, eight different AS4 3D orthogonal woven composite panels were manufactured and were subjected to mechanical testing including uniaxial tension along the weaves' warp direction. Each set, with four different resin systems (KCR-IR6070, EP2400, RTM6, and RS-50), included weave architectures designed using 12K and 6K AS4 carbon fiber yarns. For the tension testing conducted at Room Temperature Ambient (RTA) conditions, the elastic modulus and strength of these eight panels (as-processed and thermally-cycled) were measured and compared while the potential evolution of micro-cracking before and after thermal cycling were monitored via optical microscopy and X-Ray Computed Tomography. The data set also included test results of the as-processed materials at Elevated Temperature Wet (ETW) conditions. In the second part of this study, efforts were made to compute elastic constants for AS4 6K/RTM6 and AS4 12K/RTM6 materials by implementing a finite element approach and the Multiscale Generalized Method of Cells (MSGMC) technique developed at NASA Glenn Research Center. Digimat-FE was used to model the weave architectures, assign properties, calculate yarn properties, create the finite element mesh, and compute the elastic properties by applying periodic boundary conditions to finite element models of each repeating unit cell. The required input data for MSGMC was generated using Matlab® from Digimat exported weave information. Experimental and computational results were compared, and the differences and limitations in correlating to the test data were briefly discussed.

Property Computations↗
NASA NTRS2019

Data Validation: Difference Imaging and Centroid Analysis

This Design Note describes the theory and application of difference imaging for automated validation of planet candidates in the Data Validation (DV) CSCI. This is one of the diagnostic tools employed in DV for planet candidate validation. The other DV diagnostics are described in separate KADNs and in the reference documents listed below. This document describes the difference image generation process, PRF-based centroiding of the out-of-transit and difference images, computation of quarterly centroid offsets and associated uncertainties, and determination of robust weighted mean centroid offsets/uncertainties over all available quarterly data sets. PRF-based centroiding is performed with calls to a library of functions that is shared with thePhotometric Analysis (PA) and Photometer Data Quality (PDQ) CSCIs. The centroiding library will be the subject of a separate Design Note.

Twicken, Joseph↗
NASA NTRS2018

Terra and Aqua MODIS Intercomparison Using LEO-GEO Double Difference Method

The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites havesuccessfully operated since their launch in 1999 and in 2002, providing more than 18 and 16 years ofcontinuous global observations, respectively. The inter-comparison between the two MODIS instruments can bevery supportive for the instrument calibration and uncertainty assessment. Aqua and Terra MODIS have almostidentical relative spectral response, spatial resolution, and dynamic range for each band. Therefore, a sitedependent correction for a sensor spectral band pair is not necessary for their comparison. However, Terra is inthe morning orbit with an equator crossing time of 10:30 am, and Aqua is in the afternoon orbit with equatorcrossing time of 1:30 pm. Consequently, there is a dearth of simultaneous nadir overpasses (SNOs)between the two satellites. Major challenges in cross-sensor comparison of instruments on different satellitesinclude differences in observation time, solar angle, and view angle over selected pseudo-invariant sites.In this work, the inter-comparisons of thermal emissive bands are performed over a pseudo-invariant target,using the observations from a sensor onboard a geostationary satellite as a bridge. Himawari8 was launched onOctober 7, 2014. The Advanced Himawari Imager (AHI) onboard Himawari8 can be used as a reference tobridge the comparison between Terra and Aqua MODIS. AHI has 16 channels; with spatial resolutions from 0.5km to 2 km at nadir and produces a full disk observations every 10 minutes. The band spectral coveragematchup, comparable spatial resolution and near-simultaneous observation between MODIS and AHI providefeasibility to implement a double difference method. This comparison method minimizes the impact of thedifference in observation time and solar angle. The comparison results will be used as an assessment for MODISinstrument calibration and will be helpful for future enhancement of the L1B product.

Himawari8↗
NASA NTRS2019

Comparison of MODIS Solar Diffuser Stability Monitor Calibration Results for Different Operational Configurations

The MODIS instruments on the Terra and Aqua spacecraft use a sunlit solar diffuser (SD), with an optional SD attenuation screen (SDS), to calibrate the reflective solar bands. A solar diffuser stability monitor (SDSM) is used to track the SD reflectance degradation on orbit, by taking a ratio of the detector response when viewing the SD compared to the response when viewing the sun. The MODIS SDSMs have been operated both with and without the SDS in place. The SDSMs have also been operated in both a fixed and an alternating mode. In the alternating mode, the SDSM detectors view the SD, sun, and a dark background in an alternating pattern with the view changing on every MODIS scan within a single orbit. In the fixed mode, the SDSM detectors are fixed on the sun view for one orbit, and then are fixed on the SD view for the following orbit. This paper reviews the history of the SDSM operational configurations used throughout the MODIS missions and discusses the differences in the SD degradation results, which may be due to differences in sun-satellite geometry, SD signal level, and stray light effects. We highlight Aqua SDSM results from two recent dates in October 2017 and July 2019, where both the fixed and alternating mode calibrations were run on the same day, providing clear examples of the calibration differences. Additionally, we show how mixing the results from calibrations done with and without the SDS for Aqua MODIS can provide more stable results.

Twedt, Kevin A.↗
NASA NTRS2019

Uniaxial Tensile Properties of AS4 3D Woven Composites with Four Different Resin Systems: Experimental Results & Analysis - Property Computations

As a part of the NASA Composite Technology for Exploration project, eight different AS4 3D orthogonal woven composite panels were manufactured and were subjected to mechanical testing including uniaxial tension along the weaves' warp direction. Each set, with four different resin systems (KCR-IR6070, EP2400, RTM6, and RS-50), included weave architectures designed using 12K and 6K AS4 carbon fiber yarns. For the tension testing conducted at Room Temperature Ambient (RTA) conditions, the elastic modulus and strength of these eight panels (as-processed and thermally cycled) were measured and compared while the potential evolution of micro-cracking before and after thermal cycling were monitored via optical microscopy and X-Ray Computed Tomography. The data set also included test results of the as-processed materials at Elevated Temperature Wet (ETW) conditions. In the second part of this study, efforts were made to compute elastic constants for AS4 6K/RTM6 and AS4 12K/RTM6 materials by implementing a finite element approach and the Multiscale Generalized Method of Cells (MSGMC) technique developed at NASA Glenn Research Center. Digimat-FE was used to model the weave architectures, assign properties, calculate yarn properties, create the finite element mesh, and compute the elastic properties by applying periodic boundary conditions to finite element models of each repeating unit cell. The required input data for MSGMC was generated using Matlab® from Digimat exported weave information. Experimental and computational results were compared, and the differences and limitations in correlating to the test data were briefly discussed.

Property Computations↗
NASA NTRSDate not supplied

Saccade-Pursuit Coordination during Ocular Tracking across Different Impairment Sources

Purpose: Sleep loss and alcohol have been shown to impair smooth pursuit and its underlying visual motion processing in humans. This study examines the saccadic compensation for this poor pursuit. Methods: Using an established behavioral ocular-tracking paradigm (Liston & Stone, 2014, doi:10.1167/14.14.12), we examined the dose-response of ground lost (pursuit deficit integrated across our 300-ms steady-state tracking interval) and ground gained (increased saccadic response harnessed to compensate)across three separate studies – acute low-dose alcohol administration (LDA; n = 16 subjects), acute sleep loss(ASL; n = 12), and chronic sleep restriction (CSR; n = 12). We computed dose-responses as the linear regression slopes of ground lost and gained across treatment dose (% blood alcohol concentration [BAC] or hours awake). For the CSR study, we computed the mean effect for a single dose (5-hours nightly sleep for 1week). Results: For LDA, there was significantly increased ground lost (P < 0.001) and gained (P < 0.001) with increased %BAC. In addition, the dose-responses were not significantly different (P = 0.35), indicating effectively complete saccadic compensation due to significant increases in both saccadic rate (P < 0.05) and amplitude (P < 0.001). For ASL, there was significantly increased ground lost with time awake (P < 0.01),however ground gained was significantly lower (P < 0.001), indicating, at best, incomplete compensation due to a significant increase in saccadic rate (P < 0.001) but not amplitude (P = 0.10). With CSR, pursuit was again significantly impaired (P < 0.05), with saccadic rate significantly increased (P < 0.05) but, surprisingly, amplitude was significantly decreased (P < 0.05), effectively eliminating ground gained (P = 0.90). Conclusions: Our analyses show that LDA, ASL, and CSR affect tracking differently, suggesting the involvement of different brain pathways. With LDA, the effect appears largely due to the cortical impairment of visual motion processing with largely healthy brainstem and mid-brain responses (driving effective saccadic compensation). ASL and CSR however appear to affect both cortical and sub-cortical pathways, with at best partial saccadic compensation. Lastly, CSR is associated with an additional compromise due to a maladaptive decrease in saccade amplitude.

saccade↗
NASA NTRSDate not supplied

Harvesting Microgreens in Microgravity: Analysis of Six Different Methods

In long duration space missions, crops will be used to supplement the astronaut diet. One such proposed crop type is microgreens, the young seedlings of edible plants that are known for their high nutritional levels, intense flavors, colorful appearance, and variety of textures. While these characteristics make microgreens a great candidate for space crop production, their small size presents a unique challenge within the microgravity environment. To ensure that astronauts will be able to harvest microgreens in microgravity with ease while avoiding the introduction of debris to the spacecraft cabin, multiple harvesting methods were developed by the Space Crop Production Team at NASA’s Kennedy Space Center. Three parabolic flights were conducted in November and December of 2021 and during those flights three different microgreen cutting methods (guillotine, pepper grinder, scissors) as well as two different bagging methods (attached and manual) were tested. In each flight, the microgreens were contained inside of a glovebox and footage of all the microgreen harvests was recorded. The cutting and bagging method combination that introduced the lowest average number of particulates into the glovebox was the scissors with attached bagging, closely followed by the pepper grinder with attached bagging. However, the scissors with attached bagging may had introduced fewer particulates into the glovebox because on average, 27% of the microgreens were never cut using the scissors method, so there were fewer free-floating particulates generated. The cutting and bagging method combination that left the lowest average percentage of microgreens remaining on the hardware post-harvest was the pepper grinder with an attached bag. Future directions include involving microgreen harvests in analog environments and further development of the different microgreen cutting and bagging methods. This research was funded by multiple NASA grants at the Kennedy Space Center.

Haley O Boles↗
NASA NTRSDate not supplied

Characterization of NU-LHT-4M Lunar Regolith Simulant Using Different Raman Configurations

As much as possible, structures to help sustain a long-term human presence on the moon will be constructed via in-situ resource utilization (ISRU) from lunar regolith. Various processes have been proposed to make lunar regolith-based construction materials, but one complication is that the lunar regolith is relatively complex in terms of composition and can vary quite significantly from one site to another. Some of these methods to make lunar regolith-based construction materials are quite sensitive to the composition and so in-situ methods for evaluating the composition of the lunar regolith could be critical. Various analytical instrumentation has been proposed for in-situ characterization of the composition of regolith on planetary bodies. Raman spectroscopy has been suggested and has some advantages over other in-situ techniques, such as potential for relatively high spatial resolution, direct determination of the mineralogy (while other methods may only infer the mineralogy), nondestructive analysis, relatively simple instrument configurations, and minimal sample preparation/handling. For example, Raman instrumentation has already been deployed in rover-based missions to Mars. Previously, we developed the Standoff Ultracompact Micro-Raman Sensor (SUCR), which is a portable Raman spectroscopy instrument capable to be integrated into a rover or onto a lander. Here, we present work on Raman spectroscopy measurements of NU-LHT-4M lunar simulant using three different Raman instruments with different configurations for collecting Raman data with the goal to explore the effect of these different configurations on the results, especially for use in a lunar environment.

Raman Spectroscopy↗
NASA NTRS2024

Evaluating Differences Among Crop Models in Simulating Soybean in-Season Growth

Crop models are useful tools for simulating agricultural systems that require continued model development and testing to increase their robustness and improve how they describe our current understanding of processes. Coordinated and “blind” evaluation of multiple models using same protocols and experimental datasets provides unique opportunities to further improve models and enhance their reliability. For soybean [Glycine max (L.) Merr.], there has been limited coordinated multi-model evaluations for the simulation of in-season plant growth dynamics. We evaluated ten dynamic soybean crop models for their simulation of in-season plant growth using data from five experiments conducted in Argentina, Brazil, France, and USA. We evaluated models after a Blind (using only phenology data) and a Full calibration (with in-season and end-of-season variables). Calibration reduced model uncertainty by reducing standard bias for the simulation of in-season variables (biomass, leaf, pod, and stem weights, and leaf area index, LAI). However, we found that most models had difficulty in reproducing leaf growth dynamics, with normalized root mean squared error (nRMSE) of 56% for leaf weight and 43% for LAI (across locations and models after Full calibration). Models with different levels of complexity and experience were capable of simulating final seed yield at maturity with reasonable accuracy (nRMSE of 8–31% after Full calibration). However, the nRMSE for pod weight (of 17–64% after Full calibration) was two-fold larger than that of seed yield. Moreover, the models differed in how they simulated timing from sowing to beginning seed growth (47–93 days) and effective seed filling period (18–54 days), owing to model structural differences in defining the reproductive developmental stages. Overall, we identified the following processes that can benefit from further model improvement: leaf expansion and senescence, reproductive phenology, and partitioning to reproductive growth. Simulation of pod wall tissue and individual seed cohorts is another aspect that many models currently lack. Model improvement can benefit from high-temporal resolution experimental datasets that concurrently account for phenology, plant growth, and partitioning. Further, we recommend collecting reproductive phenology in the field consistent with actual dry matter allocation to organs in the models and collecting multiple observations of seed and pod weight to aid model improvement for simulation of seed growth and yield formation.

Agricultural Model Intercomparison and Improvement↗
NASA NTRS2026

Fatigue Behavior of Laser Powder Bed Fused HAYNES 214: Effects of Different Surface Treatments

In this study, under NASA’s Rapid and Analysis Manufacturing Propulsion Technology (RAMPT) project, effects of different surface post-treatments on surface texture and fatigue behavior of L-PBF Alloy 214 were investigated. Various subtractive SPTs including abrasive flow machining (AFM), machining (M), shot peening (SP), vapormatt (VM), dry electropolishing (DE), chemical milling (CM), chemical-mechanical polishing (CMP), electro chemical (ECP) were applied to study the variations of the surface texture, microstructure and uniaxial fatigue behavior under fully reversed strain-controlled condition at four different strain amplitudes of 0.005, 0.004, 0.003, and 0.0025 mm/mm. The insights gained regarding the relationship between structural and mechanical properties for different SPTs can help establish guidelines for selecting the most effective process to enhance the performance of Laser Powder Bed Fusion (L-PBF) Alloy 214, especially for critical aerospace applications.

Post-Processing↗
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↗