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DOE OSTI2022

Sensitivity analysis applied to SiC failure probability in TRISO modeled with BISON

Here, a sensitivity analysis on the failure probability of the Silicon Carbide (SiC) layer in tristructural isotropic (TRISO) nuclear fuel during transient conditions predicted by the BISON fuel performance code is performed. The principal goal of the analysis is to understand the most important parameters dictating SiC failure behavior in BISON during Reactivity Initiated Accidents (RIAs). SiC brittle fracture probability is modeled using Weibull statistics. A total of seven inputs related to SiC failure has been selected for the analysis, including the Weibull statistics parameters, elastic moduli for SiC and Pyrolitic Carbon (PyC) and SiC stress-free temperature. A 1D TRISO BISON model has been established for various reactivity insertions performed at the Nuclear Safety Research Reactor (NSRR). The principal advantage associated with the 1D TRISO model developed in this work is its computational efficiency. The Sobol variance decomposition method is used, and the sensitivity indices are presented for eight different values of the energy deposition. The results show that the two most important parameters impacting the predicted SiC failure probability are the Weibull modulus and the characteristic stress, and a co-variance amongst these parameters is obtained for low reactivity insertions. An additional new finding of this work is that the relative importance of Weibull parameters depends on the energy deposition, and thus reactivity, regime. For low energy depositions, two parameters are of influence on SiC failure probability, while for high energy depositions only one parameter impacts failure probability results. Moreover, optimization of the Weibull modulus and characteristic stress is performed by minimizing the RMSE between BISON failure probability predictions and experimental failure fractions for each energy deposition. This work also demonstrates the validity of the NSRR tests BISON simulations and of the respective sensitivity analysis results as conservative, yet indicative for slower transients characterized by lower deposited energies. Such verification is achieved through the partial extension of the analysis to a group Control Rod Withdrawal reproduced from a previous study. Another novel result of this analysis is that no single set of Weibull parameters can reproduce all reactivity insertion experimental failure results, which is related to the intrinsic nature of SiC failure properties, and a new range for the parameters is proposed to produce a failure probability envelope that encompasses the experimental fractions. Additionaly, this work proposes a new approach for future failure analysis with BISON, consisting in the use of Weibull parameters ranges, rather than fixed sets, along with failure envelopes generation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Mechanistic verification of empirical UO 2 fuel fracture models

Standard UO 2 fuel pellets used in light-water reactors fracture during irradiation due to the large thermal gradient in the radial direction. Over the decades, numerous researchers have explored fuel cracking from experimental and modeling points of view. To date, there have been both empirical and mechanistic approaches to predict the number of fragments that form in UO 2 . The empirical models only consider maximum power and burnup as inputs. Existing mechanistic approaches for normal operation have not accounted for irradiation effects. Here, this work employs a mechanistic fuel cracking model using the extended finite element method to explore radial crack formation while including a sensitivity analysis that accounts for the randomization of tensile strength within the fuel, the strength randomization criteria (uniform or volume-weighted Weibull), power ramping rates, computational mesh density, maximum power level, and irradiation (burnup) effects. The results indicate that the uncertainty in this mechanistic modeling approach envelopes the predicted values from three different empirical correlations in almost all cases. This means that, for computationally intensive analyses involving UO 2 fragmentation, the empirical correlations can be used. However, since the mechanistic calculations bound those of the empirical correlations, there is confidence in the applicability of the mechanistic approach developed in this work to generate a correlation for fuel types where limited data exists (e.g., doped-UO 2 , U 3 Si 2 ).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Probabilistic modeling and prediction of out-of-plane unidirectional composite lamina properties

Computational simulation provides an efficient means to predict the behavior of customized hybrid material configurations using validated, physics-based models. One limitation to this approach is the quality and quantity of available data to characterize the many constituent input properties. Therefore, a systematic approach to identify the most influential parameters on the hybrid behavior and quantify the corresponding uncertainty in predictive capabilities is required. Here, an approach using Bayesian multimodel inference and imprecise global sensitivity analysis is presented to investigate the effects of sparse constituent data on the prediction of composite material properties. The methodology allows the identification, using quantified uncertainties, of the most influential constituent material parameters for specified homogenized properties. This sensitivity analysis further enables a dimension reduction when assessing the influence of uncertainties on material properties and can be used to inform testing programs of the constituent properties that require additional testing/data collection in order to minimize uncertainty in macro-scale composite properties. The methodology is specifically demonstrated on the prediction and sensitivity analysis of out-of-plane mechanical properties of a unidirectional lamina.

36 MATERIALS SCIENCE↗

NASA NTRS1991

A real time dynamic data acquisition and processing system for velocity, density, and total temperature fluctuation measurements

The real time Dynamic Data Acquisition and Processing System (DDAPS) is described which provides the capability for the simultaneous measurement of velocity, density, and total temperature fluctuations. The system of hardware and software is described in context of the wind tunnel environment. The DDAPS replaces both a recording mechanism and a separate data processing system. DDAPS receives input from hot wire anemometers. Amplifiers and filters condition the signals with computer controlled modules. The analog signals are simultaneously digitized and digitally recorded on disk. Automatic acquisition collects necessary calibration and environment data. Hot wire sensitivities are generated and applied to the hot wire data to compute fluctuations. The presentation of the raw and processed data is accomplished on demand. The interface to DDAPS is described along with the internal mechanisms of DDAPS. A summary of operations relevant to the use of the DDAPS is also provided.

Clukey, Steven J.↗

NASA NTRS1994

Dexterous end effector flight demonstration

The Dexterous End Effector Flight Experiment is a flight demonstration of newly developed equipment and methods which make for more dexterous manipulation of robotic arms. The following concepts are to be demonstrated: The Force Torque Sensor is a six axis load cell located at the end of the RMS which displays load data to the operator on the orbiter CCTV monitor. TRAC is a target system which provides six axis positional information to the operator. It has the characteristic of having high sensitivity to attitude misalignment while being flat. AUTO-TRAC is a variation of TRAC in which a computer analyzes a target, displays translational and attitude misalignment information, and provides cues to the operator for corrective inputs. The Magnetic End Effector is a fault tolerant end effector which grapples payloads using magnetic attraction. The Carrier Latch Assembly is a fault tolerant payload carrier, which uses mechanical latches and/or magnetic attraction to hold small payloads during launch/landing and to release payloads as desired. The flight experiment goals and objectives are explained. The experiment equipment is described, and the tasks to be performed during the demonstration are discussed.

Carter, Edward L.↗

DOE OSTI2017

LANL-SNL Collaboration on NCS Validation.

During 2016, nuclear criticality safety (NCS) practitioners from SNL and code developers from LANL collaborated in several areas of interest to the DOE/NNSA Nuclear Criticality Safety Program (NCSP). This collaboration involved. Testing of the preliminary release of the MCNP6- Whisper methodology, with feedback to the developers, Sharing of the benchmark catalogs (the collection of MCNP input files and benchmark results), with 1101 cases from LANL and 866 cases from SNL, Comparison and analysis of 357 benchmarks common to both catalogs, Investigation of the impact of the different benchmark catalogs on sensitivity-uncertainty based NCS validation results from MCNP6-Whisper, Investigation of the impact of randomized selections from the benchmark catalog on sensitivity-uncertainty based validation results from MCNP6-Whisper. Investigation of the use of MCNP6-Whisper in selecting benchmarks for use in NCS validation for unique, nonstandard, legacy fuel applications. This paper summarizes the collaboration work and initial results. It must be noted that the results described herein are preliminary and need further research and detailed analysis. However, the initial results are very interesting, and it is important to share them with the NCSP community.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Energy balance for uranium recovery from seawater

The energy return on investment (EROI) of an energy resource is the ratio of the energy it ultimately produces to the energy used to recover it. EROI is a key viability measure for a new recovery technology, particularly in its early stages of development when financial cost assessment would be premature or highly uncertain. This paper estimates the EROI of uranium recovery from seawater via a braid adsorbent technology. In this paper, the energy cost of obtaining uranium from seawater is assessed by breaking the production chain into three processes: adsorbent production, adsorbent deployment and mooring, and uranium elution and purification. Both direct and embodied energy inputs are considered. Direct energy is the energy used by the processes themselves, while embodied energy is used to fabricate their material, equipment or chemical inputs. If the uranium is used in a once-through fuel cycle, the braid adsorbent technology EROI ranges from 12 to 27, depending on still-uncertain performance and system design parameters. It is highly sensitive to the adsorbent capacity in grams of U captured per kg of adsorbent as well as to potential economies in chemical use. This compares to an EROI of ca. 300 for contemporary terrestrial mining. It is important to note that these figures only consider the mineral extraction step in the fuel cycle. At a reference performance level of 2.76 g U recovered per kg adsorbent immersed, the largest energy consumers are the chemicals used in adsorbent production (63%), anchor chain mooring system fabrication and operations (17%), and unit processes in the adsorbent production step (12%). (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

LANL-SNL Collaboration on NCS Validation

During 2016, nuclear criticality safety (NCS) practitioners from SNL and code developers from LANL collaborated in several areas of interest to the DOE/NNSA Nuclear Criticality Safety Program (NCSP). This collaboration involved: - Testing of the preliminary release of the MCNP6- Whisper methodology, with feedback to the developers, - Sharing of the benchmark catalogs (the collection of MCNP input files and benchmark results), with 1101 cases from LANL and 866 cases from SNL, - Comparison and analysis of 357 benchmarks common to both catalogs, - Investigation of the impact of the different benchmark catalogs on sensitivity-uncertainty based NCS validation results from MCNP6-Whisper, - Investigation of the impact of randomized selections from the benchmark catalog on sensitivity-uncertainty based validation results from MCNP6-Whisper. - Investigation of the use of MCNP6-Whisper in selecting benchmarks for use in NCS validation for unique, nonstandard, legacy fuel applications. This paper summarizes the collaboration work and initial results. It must be noted that the results described herein are preliminary and need further research and detailed analysis. However, the initial results are very interesting, and it is important to share them with the NCSP community.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Warming and elevated CO 2 promote rapid incorporation and degradation of plant‐derived organic matter in an ombrotrophic peatland

Abstract Rising temperatures have the potential to directly affect carbon cycling in peatlands by enhancing organic matter (OM) decomposition, contributing to the release of CO 2 and CH 4 to the atmosphere. In turn, increasing atmospheric CO 2 concentration may stimulate photosynthesis, potentially increasing plant litter inputs belowground and transferring carbon from the atmosphere into terrestrial ecosystems. Key questions remain about the magnitude and rate of these interacting and opposing environmental change drivers. Here, we assess the incorporation and degradation of plant‐ and microbe‐derived OM in an ombrotrophic peatland after 4 years of whole‐ecosystem warming (+0, +2.25, +4.5, +6.75 and +9°C) and two years of elevated CO 2 manipulation (500 ppm above ambient). We show that OM molecular composition was substantially altered in the aerobic acrotelm, highlighting the sensitivity of acrotelm carbon to rising temperatures and atmospheric CO 2 concentration. While warming accelerated OM decomposition under ambient CO 2 , new carbon incorporation into peat increased in warming × elevated CO 2 treatments for both plant‐ and microbe‐derived OM. Using the isotopic signature of the applied CO 2 enrichment as a label for recently photosynthesized OM, our data demonstrate that new plant inputs have been rapidly incorporated into peat carbon. Our results suggest that under current hydrological conditions, rising temperatures and atmospheric CO 2 levels will likely offset each other in boreal peatlands.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2010

Mars-GRAM: Increasing the Precision of Sensitivity Studies at Large Optical Depths

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM's perturbation modeling capability is commonly used, in a Monte-Carlo mode, to perform high fidelity engineering end-to-end simulations for entry, descent, and landing (EDL). It has been discovered during the Mars Science Laboratory (MSL) site selection process that Mars-GRAM, when used for sensitivity studies for MapYear=0 and large optical depth values such as tau=3, is less than realistic. A comparison study between Mars atmospheric density estimates from Mars-GRAM and measurements by Mars Global Surveyor (MGS) has been undertaken for locations of varying latitudes, Ls, and LTST on Mars. The preliminary results from this study have validated the Thermal Emission Spectrometer (TES) limb data. From the surface to 80 km altitude, Mars-GRAM is based on the NASA Ames Mars General Circulation Model (MGCM). MGCM results that were used for Mars-GRAM with MapYear=0 were from a MGCM run with a fixed value of tau=3 for the entire year at all locations. This has resulted in an imprecise atmospheric density at all altitudes. To solve this pressure-density problem, density factor values were determined for tau=.3, 1 and 3 that will adjust the input values of MGCM MapYear 0 pressure and density to achieve a better match of Mars-GRAM MapYear 0 with TES observations for MapYears 1 and 2 at comparable dust loading. The addition of these density factors to Mars-GRAM will improve the results of the sensitivity studies done for large optical depths.

Justh, Hilary L.↗

DOE OSTI2025

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

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

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2015

A covariance methodology for theoretically generated thermal neutron inelastic scattering data - 14502

The The S(α,β) double-differential thermal neutron scattering law tabulated in ENDF File 7 is, by convention, produced theoretically through fundamental scattering physics models for material-specific interatomic structures. Differential and integral inelastic scattering cross sections are calculated by numerically integrating over S(α,β). This information is supplied to nuclear system simulation codes. For systems with a significant thermal neutron flux, calculated system response parameters can be sensitive to this thermal cross section data. Formats and procedures are currently established for representing uncertainty information, or covariances, for various types of ENDF reaction data. However, no published ENDF evaluations contain covariance data for S(α,β) or associated differential and integral inelastic scattering cross sections. Furthermore, no accepted methodology exists for quantifying or representing covariances for this thermal scattering data. For most solids, the influence of a material's interatomic structure and dynamics on inelastic scattering cross sections can be adequately described through the phonon density of states (DOS). The phonon DOS is a probability density function of the population of available vibrational modes in energy, and it is typically the fundamental input for calculating S(α,β). Probable variation in the spectral shape of the phonon DOS may be established which characterizes uncertainties in the physics models and methodology employed in its production. Through Monte Carlo sampling of perturbations from the reference phonon spectrum, an S(α,β) covariance matrix may be generated. With appropriate sensitivity information, this can be propagated to generate covariance data for differential and integral inelastic scattering cross sections. In this work, hexagonal graphite is used as an example material for the purpose of demonstrating procedures for analyzing, calculating and representing uncertainty information for thermal neutron inelastic scattering data. (authors)

42 ENGINEERING↗

NASA NTRS2006

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Kobayashi, Takahisa↗

DOE OSTI2017

Simulation of Precipitation Extremes Using a Stochastic Convective Parameterization in the NCAR CAM5 Under Different Resolutions

With the incorporation of the Plant-Craig stochastic deep convection scheme into the Zhang-McFarlane deterministic parameterization in the Community Atmospheric Model version 5 (CAM5), its impact on extreme precipitation at different resolutions (2°, 1°, and 0.5°) is investigated. CAM5 with the stochastic deep convection scheme (experiment (EXP)) simulates the precipitation extreme indices better than the standard version (control). At 2° and 1° resolutions, EXP increases high percentile (>99th) daily precipitation over the United States, Europe, and China, resulting in a better agreement with observations. However, at 0.5° resolution, due to enhanced grid-scale precipitation with increasing resolution, EXP overestimates extreme precipitation over southeastern U.S. and eastern Europe. The reduced biases in EXP at each resolution benefit from a broader probability distribution function of convective precipitation intensity simulated. Among EXP simulations at different resolutions, if the spatial averaging area over which input quantities used in convective closure are spatially averaged in the stochastic convection scheme is comparable, the modeled convective precipitation intensity decreases with increasing resolution, when gridded to the same resolution, while the total precipitation is not sensitive to model resolution, exhibiting some degree of scale-awareness. Sensitivity tests show that for the same resolution, increasing the size of spatial averaging area decreases convective precipitation but increases the grid-scale precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Validation of SAS4A/SASSYS-1 for predicting steady-state single-phase natural circulation

The validation of system analysis codes for nuclear reactor systems is required for the development and application of these computational tools. Designed as a comprehensive system analysis code for advanced nuclear reactors, SAS4A/SASSYS-1 requires validation of its physics model for capturing single-phase natural circulation behavior. To support the validation of SAS4A/SASSYS-1, high-precision experiments are performed capturing steady-state single-phase natural circulation on a scaled facility with comprehensive instrumentation. In this work, dedicated tests are performed quantifying the critical modeling parameters, and a single-phase natural circulation benchmark dataset is obtained with well-documented uncertainty and comprehensive facility description. The validation is then performed against the dataset examining the capability of SAS4A/SASSYS-1 in simulating steady-state single-phase natural circulation. The experimental facility is modeled in the candidate code. Solution verification is performed using Richardson-extrapolation-based estimators which quantify and restrict numerical errors from discretization. Input uncertainty provided by the benchmark dataset is forward propagated through the candidate code, quantifying the output uncertainty in a Monte Carlo approach. The composition of the output uncertainty is also quantified through a variance-based sensitivity analysis. With the uncertainty quantified for each individual condition, a detailed comparison between the simulation results and experimental data is performed covering the whole dataset. The results show consistent agreement for all primary parameters. The current validation activity provides a valuable benchmark dataset for the validation of system analysis codes in capturing single-phase natural circulation and demonstrates satisfactory prediction capability of SAS4A/SASSYS1 for steady-state single-phase natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Screening Fuels for Autoignition with Small-Volume Experiments and Gaussian Process Classification

Partially reacting candidate fuels under highly dilute conditions across a range of temperatures provides a means to classify the candidates based on traditional ignition characteristics using much lower quantities (sub-mL) than the full octane tests. Using a classifier based on a Gaussian Process model, synthetic species profiles obtained by plug flow reactor simulations at seven temperatures are used to demonstrate that the configuration can be used to classify 95% of the samples correctly for autoignition sensitivity exceeding a threshold (S = 8) and 100%of the samples correctly for research octane number exceeding a threshold (RON = 90). Molecular beam mass spectrometry (MBMS) experimental data at four temperatures is then used as the model input in a real-world test. Despite the nontrivial relationship between the MBMS measurements and speciation as well as experimental noise it is still possible to classify 95% of the samples correctly for RON and 85% of the samples correctly for S in a 'leave-one-out' cross validation exercise. The test data set consists of 45 fuels and includes a variety of primary reference fuels, ethanol blends and other oxygenates.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Heterotrophic respiration by soil microbes in a changing climate

Soil microbes strongly influence the soil organic carbon (SOC) pool, which globally stores ~2,000 PgC. Specifically, the balance between microbial heterotrophic respiration (R H ), which degrades SOC, and plant–microbe interactions that stabilize SOC determines whether terrestrial ecosystems are a net source or sink of CO 2 to the atmosphere. Here, in this Review, we evaluate how climate change alters these competing processes. R H is approximately half of total soil respiration, at ~50 PgC yr −1 , with 70% occurring in topsoils. Warming accelerates microbial metabolism, with a 10 °C temperature increase estimated to raise R H by ~50%, an effect that is particularly strong in Arctic soils. Warming also reduces soil moisture, further modulating R H , which responds nonlinearly to soil moisture, being limited by saturation and desiccation and meeting a maximum at intermediate levels. Consequently, R H is highly sensitive to future precipitation changes and drought. However, soil management strategies could enhance SOC stocks and persistence under climate change. Bacterial and fungal inoculants can promote SOC production and stabilization, while deep-rooting plants increase SOC inputs to deeper layers that experience lower R H . Agricultural practices and biochar amendments can also enhance SOC and reduce R H . Expanding field trials across regions, climates and soil types would improve empirical understanding of these responses and support better representation of R H in predictive models, enabling more accurate assessments of climate impacts on SOC storage.

Jansson, Janet K. [Pacific Northwest National Labo↗

DOE OSTI2023

BEYONDPLANCK IV. On end-to-end simulations in CMB analysis — Bayesian versus frequentist statistics

End-to-end simulations play a key role in the analysis of any high-sensitivity cosmic microwave background (CMB) experiment, providing high-fidelity systematic error propagation capabilities that are unmatched by any other means. In this paper, we address an important issue regarding such simulations, namely, how to define the inputs in terms of sky model and instrument parameters. These may either be taken as a constrained realization derived from the data or as a random realization independent from the data. We refer to these as posterior and prior simulations, respectively. We show that the two options lead to significantly different correlation structures, as prior simulations (contrary to posterior simulations) effectively include cosmic variance, but they exclude realization-specific correlations from non-linear degeneracies. Consequently, they quantify fundamentally different types of uncertainties. We argue that as a result, they also have different and complementary scientific uses, even if this dichotomy is not absolute. In particular, posterior simulations are in general more convenient for parameter estimation studies, while prior simulations are generally more convenient for model testing. Before BEYONDPLANCK, most pipelines used a mix of constrained and random inputs and applied the same hybrid simulations for all applications, even though the statistical justification for this is not always evident. BEYONDPLANCK represents the first end-to-end CMB simulation framework that is able to generate both types of simulations and these new capabilities have brought this topic to the forefront. The BEYONDPLANCK posterior simulations and their uses are described extensively in a suite of companion papers. In this work, we consider one important applications of the corresponding prior simulations, namely, code validation. Specifically, we generated a set of one-year LFI 30 GHz prior simulations with known inputs and we used these to validate the core low-level BEYONDPLANCK algorithms dealing with gain estimation, correlated noise estimation, and mapmaking.

79 ASTRONOMY AND ASTROPHYSICS↗