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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Hybrid Thermally Efficient Core (HyTEC) HyTEC Phase 1 – Combustor Final Report

The objective of the HyTEC – Combustor Technology project is to develop technology for a compact, low emissions, rich-burn combustor that maintains a high-level of durability. To accomplish this, the combustor will incorporate CMC liners and a CMC Dome to enable improved air utilization for mixing and NOx reduction. In particular, three technology areas were matured: metallic swirler attachment to the CMC dome, Nickel diffusion in CMC, and EBC advancements with improved durability. The maturation of these technology areas is critical to successfully designing a combustor for an engine intended to demonstrate increased thermal efficiency with integrated high-power density-core engine technologies. As part of the project, multiple swirler attachment architectures were matured through the design process, manufactured, and tested in simulated engine conditions. These architectures utilized two different approaches to attachment: a pressure loaded approach and a clamped approach. Each approach required testing at simulated engine conditions to mature the technology. These tests were developed to ensure that the probable failure mechanisms for each architecture were assessed relative to its long-term durability. After successfully testing both approaches, the pressure loaded approach was chosen based on its simplicity and its similarity to the attachment approach used on lean burn combustors. Finally, this successful testing resulted in the swirler attachment technology achieving TRL 4 status. Another aspect of concern with the metallic swirler attachment is the potential for nickel diffusion into the CMC to cause durability shortfalls. A series of tests were completed to understand both the amount of nickel that is expected to diffuse into the CMC and the effect this diffusion will have on mechanical properties of the CMC. After successfully completing this testing, the reduction in local mechanical properties was found to not have an impact on the overall durability of the CMC Dome. To further improve the overall durability, three different EBC coating architectures were also studied. One of these coatings being the current state of the art for CMC liners with the other two being proposed improvements. Coupons were produced using each coating and subjected to a series of laboratory testing. One coating was found to have an overall superior durability in laboratory testing and survived rig testing without indication of degradation. This successful testing resulted in the EBC technology achieving TRL 5 status. Overall, a design approach was successfully down-selected that achieves both the TPM requirements and the need for TRL 4+ status. This design incorporates a pressure loaded swirler attachment with an improved EBC coating (Architecture 1). This combination allows the continued use of a CMC dome and results in an improved durability for the proposed compact core combustor.

CMC↗
DOE OSTI2021

Chapmanite [Fe 2 Sb(Si 2 O 5 )O 3 (OH)]: thermodynamic properties and formation in low-temperature environments

Abstract. of synthetic Sb 2 O 5 , MgSb 2 O 6 (analogue of the mineral byströmite), Mg[Sb(OH) 6 ] 2 ∙6H 2 O (brandholzite), and natural chapmanite [(Fe 1.88 Al 0.12 )Sb(Si 2 O 5 )O 3 (OH)]. Enthalpies of reactions, including formation enthalpies, were evaluated using reference compounds Sb, Sb 2 O 3 , Sb 2 O 5 , and other phases, with high-temperature oxide melt solution calorimetry in lead borate and sodium molybdate solvents. Heat capacity and entropy were determined by relaxation and differential scanning calorimetry. The best set of Δ f H o (kJ mol -1 ) and S o (J mol -1 K -1 ) is byströmite -1733.0±3.6, 139.3±1.0; brandholzite -5243.1±3.6, 571.0±4.0; and chapmanite -3164.9±4.7, 305.1±2.1. The data for chapmanite give Δ f G o of -2973.6±4.7 kJ mol -1 and log K=-17.10 for the dissolution reaction (Fe 1.88 Al 0.12 )Sb(Si 2 O 5 )O 3 (OH) + 6H + → 1.88Fe 3+ + 0.12Al 3+ + 2SiO$_2^0$ + Sb(OH)$_3^0$ + 2H 2 O. Analysis of the data showed that chapmanite is finely balanced in terms of its stability with schafarzikite (FeSb 2 O 4 ) and tripuhyite (FeSbO 4 ) under a specific, narrow range of conditions when both aqueous Fe(III) and Sb(III) are abundant. In such a model, chapmanite is metastable by a narrow margin but could be stabilized by high SiO$_2^0$(aq) activities. Natural assemblages of chapmanite commonly contain abundant amorphous silica, suggesting that this mechanism may be indeed responsible for the formation of chapmanite. Chapmanite probably forms during low-temperature hydrothermal overprint of pre-existing Sb ores under moderately reducing conditions; the slightly elevated temperatures may help to overcome the kinetic barrier for its crystallization. During weathering, sheet silicates may adsorb Sb 3+ in tridentate hexanuclear fashion, thus exposing their chapmanite-like surfaces to the surrounding aqueous environment. Formation of chapmanite, as many other sheet silicates, under ambient conditions, is unlikely.

58 GEOSCIENCES↗
NASA NTRS1976

Crack growth in Ti-8Al-1Mo-1V with real-time and accelerated flight-by-flight loading

Crack growth in Ti-8Al-1Mo-1V was measured and calculated for real-time and accelerated simulations of supersonic airplane loading and heating. Crack-growth rates calculated on the assumption that an entire flight could be represented by a single cycle predicted the experimental rates poorly. Calculated crack-growth rates were slower than the experimental rates for all tests with flight-by-flight loading. For room-temperature accelerated tests, the calculated rates agreed well with the experimental rates; but the calculations became progressively less accurate for progressively more complex test conditions (tests that included elevated temperature). Calculations of crack growth using the crack-closure concept can probably be improved through study of crack-opening stresses using finite-element models that account for variable-amplitude loading, residual stresses, and temperature effects. The calculations of crack growth could also be improved through detailed studies of material properties and interactions among stress, temperature, and time as appropriate for the real-time operating conditions of a supersonic transport airplane.

Imig, L. A.↗
NASA NTRS2007

Reliability and Creep/Fatigue Analysis of a CMC Component

High temperature ceramic matrix composites (CMC) are being explored as viable candidate materials for hot section gas turbine components. These advanced composites can potentially lead to reduced weight and enable higher operating temperatures requiring less cooling; thus leading to increased engine efficiencies. There is a need for convenient design tools that can accommodate various loading conditions and material data with their associated uncertainties to estimate the minimum predicted life as well as the failure probabilities of a structural component. This paper presents a review of the life prediction and probabilistic analyses performed for a CMC turbine stator vane. A computer code, NASALife, is used to predict the life of a 2-D woven silicon carbide fiber reinforced silicon carbide matrix (SiC/SiC) turbine stator vane due to a mission cycle which induces low cycle fatigue and creep. The output from this program includes damage from creep loading, damage due to cyclic loading and the combined damage due to the given loading cycle. Results indicate that the trends predicted by NASALife are as expected for the loading conditions used for this study. In addition, a combination of woven composite micromechanics, finite element structural analysis and Fast Probability Integration (FPI) techniques has been used to evaluate the maximum stress and its probabilistic distribution in a CMC turbine stator vane. Input variables causing scatter are identified and ranked based upon their sensitivity magnitude. Results indicate that reducing the scatter in proportional limit strength of the vane material has the greatest effect in improving the overall reliability of the CMC vane.

Murthy, Pappu L. N.↗
DOE OSTI2022

A Conditional Autoencoder for Galaxy Photometric Parameter Estimation

Astronomical photometric surveys routinely image billions of galaxies, and traditionally infer the parameters of a parametric model for each galaxy. This approach has served us well, but the computational expense of deriving a full posterior probability distribution function is a challenge for increasingly ambitious surveys. In this paper, we use deep learning methods to characterize galaxy images, training a conditional autoencoder on mock data. The autoencoder can reconstruct and denoise galaxy images via a latent space engineered to include semantically meaningful parameters, such as brightness, location, size, and shape. Our model recovers galaxy fluxes and shapes on mock data with a lower variance than the Hyper Suprime-Cam photometry pipeline, and returns reasonable answers even for inputs outside the range of its training data. When applied to data in the training range, the regression errors on all extracted parameters are nearly unbiased with a variance near the Cramr-Rao bound.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2003

Focused Assessment with Sonography for Trauma in weightlessness: a feasibility study

BACKGROUND: The Focused Assessment with Sonography for Trauma (FAST) examines for fluid in gravitationally dependent regions. There is no prior experience with this technique in weightlessness, such as on the International Space Station, where sonography is currently the only diagnostic imaging tool. STUDY DESIGN: A ground-based (1 g) porcine model for sonography was developed. We examined both the feasibility and the comparative performance of the FAST examination in parabolic flight. Sonographic detection and fluid behavior were evaluated in four animals during alternating weightlessness (0 g) and hypergravity (1.8 g) periods. During flight, boluses of fluid were incrementally introduced into the peritoneal cavity. Standardized sonographic windows were recorded. Postflight, the video recordings were divided into 169 20-second segments for subsequent interpretation by 12 blinded ultrasonography experts. Reviewers first decided whether a video segment was of sufficient diagnostic quality to analyze (determinate). Determinate segments were then analyzed as containing or not containing fluid. A probit regression model compared the probability of a positive fluid diagnosis to actual fluid levels (0 to 500 mL) under both 0-g and 1.8-g conditions. RESULTS: The in-flight sonographers found real-time scanning and interpretation technically similar to that of terrestrial conditions, as long as restraint was maintained. On blinded review, 80% of the recorded ultrasound segments were considered determinate. The best sensitivity for diagnosis in 0 g was found to be from the subhepatic space, with probability of a positive fluid diagnosis ranging from 9% (no fluid) to 51% (500 mL fluid). CONCLUSIONS: The FAST examination is technically feasible in weightlessness, and merits operational consideration for clinical contingencies in space.

NASA Discipline Life Sciences Technologies↗
NASA NTRS2011

Probabilistic Analysis of a Composite Crew Module

An approach for conducting reliability-based analysis (RBA) of a Composite Crew Module (CCM) is presented. The goal is to identify and quantify the benefits of probabilistic design methods for the CCM and future space vehicles. The coarse finite element model from a previous NASA Engineering and Safety Center (NESC) project is used as the baseline deterministic analysis model to evaluate the performance of the CCM using a strength-based failure index. The first step in the probabilistic analysis process is the determination of the uncertainty distributions for key parameters in the model. Analytical data from water landing simulations are used to develop an uncertainty distribution, but such data were unavailable for other load cases. The uncertainty distributions for the other load scale factors and the strength allowables are generated based on assumed coefficients of variation. Probability of first-ply failure is estimated using three methods: the first order reliability method (FORM), Monte Carlo simulation, and conditional sampling. Results for the three methods were consistent. The reliability is shown to be driven by first ply failure in one region of the CCM at the high altitude abort load set. The final predicted probability of failure is on the order of 10-11 due to the conservative nature of the factors of safety on the deterministic loads.

FROM↗
NASA NTRS1989

Dynamics of face and annular seals with two-phase flow

A detailed study was made of face and annular seals under conditions where boiling, i.e., phase change of the leaking fluid, occurs within the seal. Many seals operate in this mode because of flashing due to pressure drop and/or heat input from frictional heating. High pressure, water pumps, industrial chemical pumps, and cryogenic pumps are mentioned as a few of many applications. The initial motivation was the LOX-GOX seals for the space shuttle main engine, but the study was expanded to include any face or annular seal where boiling occurs. Some of the distinctive behavior characteristics of two-phase seals were discussed, particularly their axial stability. While two-phase seals probably exhibit instability to disturbances of other degrees of freedom such as wobble, etc., under certain conditions, such analyses are too complex to be treated at present. Since an all liquid seal (with parallel faces) has a neutral axial stiffness curve, and is stabilized axially by convergent coning, other degrees of freedom stability analyses are necessary. However, the axial stability behavior of the two-phase seal is always a consideration no matter how well the seal is aligned and regardless of the speed. Hence, axial stability is thought of as the primary design consideration for two-phase seals and indeed the stability behavior under sub-cooling variations probably overshadows other concerns. The main thrust was the dynamic analysis of axial motion of two-phase face seals, principally the determination of axial stiffness, and the steady behavior of two-phase annular seals. The main conclusions are that seals with two-phase flow may be unstable if improperly balanced. Detailed theoretical analyses of low (laminar) and high (turbulent) leakage seals are presented along with computer codes, parametric studies, and in particular a simplified PC based code that allows for rapid performance prediction. A simplified combined computer code for the performance prediction over the laminar and turbulent ranges of a two-phase seal is described and documented. The analyses, results, and computer codes are summarized.

Hughes, William F.↗
DOE OSTI2025

RLGBS: Reinforcement Learning-Guided Beam Search for process optimization in a paper machine dryer section

Paper drying is responsible for over two-thirds of energy consumption in the U.S. pulp and paper industry, presenting significant potential for energy savings through optimization of process parameters. Current approaches often assume fixed operating conditions, neglecting dynamic ambient and process variations that limit achievable savings and real-world applicability. To this end, we develop a physics-based simulation environment for a paper machine dryer section and propose a reinforcement learning (RL) framework to minimize overall energy consumption by optimizing drying process parameters under diverse operating conditions. To mitigate overdrying and numerical instabilities caused by suboptimal local RL actions, we introduce Reinforcement Learning-Guided Beam Search (RLGBS), which explores multiple action sequences in parallel using beam search. Instead of making step-by-step decisions, RLGBS prioritizes solutions based on cumulative probability, reducing the impact of individual suboptimal actions. Experiments demonstrate that RLGBS achieves consistent energy savings under unseen operating conditions not encountered during training, outperforming conventional RL methods. While validated in drying optimization, this framework is broadly applicable to other RL-based industrial process control problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2003

Modeling, Analyzing, and Mitigating Dissonance Between Alerting Systems

Alerting systems are becoming pervasive in process operations, which may result in the potential for dissonance or conflict in information from different alerting systems that suggests different threat levels and/or actions to resolve hazards. Little is currently available to help in predicting or solving the dissonance problem. This thesis presents a methodology to model and analyze dissonance between alerting systems, providing both a theoretical foundation for understanding dissonance and a practical basis from which specific problems can be addressed. A state-space representation of multiple alerting system operation is generalized that can be tailored across a variety of applications. Based on the representation, two major causes of dissonance are identified: logic differences and sensor error. Additionally, several possible types of dissonance are identified. A mathematical analysis method is developed to identify the conditions for dissonance originating from logic differences. A probabilistic analysis methodology is developed to estimate the probability of dissonance originating from sensor error, and to compare the relative contribution to dissonance of sensor error against the contribution from logic differences. A hybrid model, which describes the dynamic behavior of the process with multiple alerting systems, is developed to identify dangerous dissonance space, from which the process can lead to disaster. Methodologies to avoid or mitigate dissonance are outlined. Two examples are used to demonstrate the application of the methodology. First, a conceptual In-Trail Spacing example is presented. The methodology is applied to identify the conditions for possible dissonance, to identify relative contribution of logic difference and sensor error, and to identify dangerous dissonance space. Several proposed mitigation methods are demonstrated in this example. In the second example, the methodology is applied to address the dissonance problem between two air traffic alert and avoidance systems: the existing Traffic Alert and Collision Avoidance System (TCAS) vs. the proposed Airborne Conflict Management system (ACM). Conditions on ACM resolution maneuvers are identified to avoid dynamic dissonance between TCAS and ACM. Also included in this report is an Appendix written by Lee Winder about recent and continuing work on alerting systems design. The application of Markov Decision Process (MDP) theory to complex alerting problems is discussed and illustrated with an abstract example system.

Song, Lixia↗
NASA NTRSDate not supplied

Derivation of the Most Influential Medical Conditions for An Extended Duration Artemis Mission

BACKGROUND: The risk of loss of mission due to medical conditions may be influenced by loss of crew life (LOCL), need for evacuation (RTDC; return to definitive care), and crew task time lost. Predicting what medical conditions are most likely to lead to crew morbidity and mortality may influence medical system design, clinical capability prioritization, and research strategies. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) applies Probabilistic Risk Assessment (PRA) methodology to assess these risks. OVERVIEW: A team of subject matter experts (SME) from a variety of medical disciplines developed a consensus-based process to determine 120 of the most clinically relevant medical conditions for long-duration exploration missions (LDEMs) . This IMPACT Condition List (ICL) expanded upon previous work done for Integrated Medical Model (IMM). For each condition a best-case and worst-case definition were derived. These definitions were used to identify probability of occurrence, proportion of cases that are best case vs. worst case, clinical phase duration, and risk of outcomes (task time loss [TTL], RTDC, and LOCL) for both treated and untreated states. These data were sources from existing spaceflight databases (e.g. Longitudinal Survey of Astronaut Health), relevant models (e.g. the ISS fire model), and/or terrestrial literature. Each condition was then tied to diagnostic and therapeutic resources and capabilities. IMPACT was then run for the LDLOLS DRM (see Abstract #2 for this panel). DISCUSSION: This abstract will present the process for generating the IMPACT condition list, the relevant data for each clinical condition, and present results for the ten most influential conditions impacting LOCL, RTDC, and TTL for a representative extended duration Artemis mission.

A Nelson↗
DOE OSTI2024

Risk-based System Upgrade Planning for AOT-IC [Capstone Project]

The Accelerator Operations and Technology Instrumentation and Controls Group (AOT IC) at the Los Alamos Neutron Science Center (LANSCE) has established a comprehensive risk-based system upgrade planning strategy which has been utilized as a tool to prioritize system upgrade projects for the past several years. A challenge with the current system is that the group often lacks the data to quantify the probability and impact of system failures, so the group often relies instead on qualitative risk assessments as well as evaluations of a potential upgrade project’s alignment with group strategy and vision to prioritize projects. A proposed framework to enable quantitative risk probability and impact assessments has been developed and tested on three pilot systems chosen to broadly represent the types and conditions of equipment used by the group. The proposed framework incorporates availability data gathered from the LANSCE control room logbooks and the LANSCE work control system, as well as a system health evaluation which is conducted from a variety of resources to assess the probability of equipment failure. The impact of system failure is viewed from the perspective of impact on mission and schedule, where spares status, system documentation status, and the functional distribution of deployed systems are used to quantify these impacts.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

On the quantification and efficient propagation of imprecise probabilities with copula dependence

This paper addresses the problem of quantification and propagation of uncertainties associated with dependence modeling when data for characterizing probability models are limited. Practically, the system inputs are often assumed to be mutually independent or correlated by a multivariate Gaussian distribution. However, this subjective assumption may introduce bias in the response estimate if the real dependence structure deviates from this assumption. In this work, we overcome this limitation by introducing a flexible copula dependence model to capture complex dependencies. Here, a hierarchical Bayesian multimodel approach is proposed to quantify uncertainty in dependence model-form and model parameters that result from small data sets. This approach begins by identifying, through Bayesian multimodel inference, a set of candidate marginal models and their corresponding model probabilities, and then estimating the uncertainty in the copula-based dependence structure, which is conditional on the marginals and their parameters. The overall uncertainties integrating marginals and copulas are probabilistically represented by an ensemble of multivariate candidate densities. A novel importance sampling reweighting approach is proposed to efficiently propagate the overall uncertainties through a computational model. Through an example studying the influence of constituent properties on the out-of-plane properties of transversely isotropic E-glass fiber composites, we show that the composite property with copula-based dependence model converges to the true estimate as data set size increases, while an independence or arbitrary Gaussian correlation assumption leads to a biased estimate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Lessons Learned in Employing Data Analytics to Predict Oxidation Kinetics and Spallation Behavior of High-Temperature NiCr-Based Alloys

Machine learning (ML) can offer many advantages in predicting material properties over traditional materials development methods based solely on limited experimental investigations or physical-based simulations with the capability to reduce development cost, risk, and time. However, so far, limited efforts have been made to predict alloy oxidation kinetics and spallation behavior via ML due to the lack of consistently measured and sufficient experimental data and the inherent complexity in oxidation behavior of multicomponent high-temperature alloys. A previous study reported the ability of ML to predict oxidation kinetics of NiCr-based alloys as a function of alloy composition and operating conditions. Here, the performance of a ML model in predicting rate constants and spallation probability was evaluated in light of the roles of the data distribution of the experimental dataset (data analytics), the alloy composition, the exposure environment and the chosen oxidation approach to extracting kinetic values from the measured mass changes (but using either a simple parabolic law or a statistical cyclic oxidation model). Potential strategies to improve the predictions and enhance the extrapolative capability of the previously trained model will be discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Agent-based simulation and child protection systems: Rationale, implementation, and verification

Simulation models are an important tool used in health care and other disciplines to support operational research and decision-making. In the child protection literature, simulation models are an under-utilized source of research evidence. Here, in this paper, we describe the rationale for and the development of an agent-based simulation of a child protection system in the US. Using the investigation, prevention service, and placement histories of 600,000 children served in an urban child welfare system, we walk the reader through the development of a prototype known as OSPEDALE. The governing equations built into OSPEDALE probabilistically simulate the onset of investigations. Then, drawing from empirical survival distributions, the governing equations trace the probability of subsequent interactions with the system (recurrence of maltreatment, service referrals, and placement) conditional on the characteristics of children, their assessed risk level, and prior child protection system involvement. As an initial test of OSPEDALE's utility, we compare empirical admission counts with counts generated from OSPEDALE. Though the verification step is admittedly simple, the comparison shows that OSPEDALE replicates the empirical count of new admissions closely enough to justify further investment in OSPEDALE. Management of public child protection systems is increasingly research evidence-dependent. The emphasis on research evidence as a decision-support tool has elevated evidence acquired through randomized clinical trials. Though important, the evidence from clinical trials represents only one type of research evidence. Properly specified, simulation models are another source of evidence with real-world relevance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The Monomeric Alanediyl : AlAr i Pr8 (Ar i Pr8 = C 6 H-2,6-(C 6 H 2 -2,4,6-Pr i 3 ) 2 -3,5-Pr i 2 ): An Organoaluminum(I) Compound with a One-Coordinate Aluminum Atom

Reduction of the aluminum iodide AlI 2 Ar i Pr8 ( 1 ; Ar i Pr8 = C 6 H-2,6-(C 6 H 2 -2,4,6-Pr i 3 ) 2 -3,5-Pr i 2 ) with 5% w/w Na/NaCl in hexanes gave a dark red solution from which the monomeric alanediyl : AlAr i Pr8 ( 2 ) was isolated in ca. 28% yield as yellow-orange crystals. Compounds 1 and 2 were characterized by X-ray crystallography, electronic and NMR spectroscopy, and theoretical calculations. The Al atom in 2 is one-coordinate, and the compound displays two absorptions in its electronic spectrum at 354 and 455 nm. It reacts with H 2 under ambient conditions to give the aluminum hydride {AlH(μ-H)Ar i Pr8 } 2 , probably via a weakly bound dimer of 2 as an intermediate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Monte Carlo event generator for initial conditions of conserved charges in nuclear geometry

At top collider energies where baryon stopping is negligible, the initial state of heavy-ion collisions is overall charge neutral and predominantly composed of gluons. Nevertheless, there can also be significant local fluctuations of the baryon number, strangeness, and electric charge densities about zero, perturbatively corresponding to the production of quark/antiquark pairs. These previously ignored local charge fluctuations can permit the study of charge diffusion in the quark-gluon plasma (QGP), even at top collider energies. In this paper we present a new model denoted ICCING (initial conserved charges in nuclear geometry) which can reconstruct the initial conditions of conserved charges in the QGP by sampling a (g→q¯q) splitting probability over the initial energy density. We find that the new charge distributions generally differ from the bulk energy density; in particular, the strangeness distribution is significantly more eccentric than standard bulk observables and appears to be associated with the geometry of hot spots in the initial state. The new information provided by these conserved charges opens the door to studying a wealth of new charge- and flavor-dependent correlations in the initial state and ultimately the charge transport parameters of the QGP.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Risk Importance Ranking of Fire Data Parameters to Enhance Fire PRA Model Realism

Fire is historically and analytically a significant contributor to nuclear power plant risk. The level of fire risk and the methods, tools and data for modeling this risk is highly debated by experts. One area of debate is the input data used in fire modeling and how to deal with this data’s high uncertainty. This report outlines initial work performed for determining the key parameters causing this uncertainty and how it propagates into nuclear power plant models. This research paves the way for the development of methods to reduce fire data uncertainty used in modeling. The Nuclear Regulatory Commission has mandated that nuclear power plants perform fire risk modeling. However, there are several issues with the current risk modeling implementation that affect the results. Approved modeling methods can be overly conservative and often do not match plant experience. Also, the data used in the modeling can have high uncertainties and is influenced by expert judgement. To evaluate input data uncertainty, researchers performed an initial review of several fire experiments done at Sandia National Laboratories. Uncertainties for fire data can come from many sources, such as experiment design constraints, environmental conditions, or other plant-specific aspects. There are many different significant and insignificant parameters driving the uncertainty. Additionally, the uncertainty of the different input data used in the fire modeling could have a significant or insignificant effect on the entire plant risk. A four-step methodology was developed to perform Integrated Probabilistic Risk Assessment Importance Ranking. A demonstration case using these steps was set up and three of the four steps were completed in fiscal year (FY) 2019 and the fourth step done FY 2020. These steps are: 1. The qualitative analysis of potential sources was conducted with the following items identified for the demonstration. • Maximum heat release rate • Time to maximum heat release rate • Duration of max heat release rate • Time to decay • Thermal conductivity of concrete • Specific heat of concrete • Density of concrete • Cable jacket thickness 2. A quantitative characterization of dominant sources of uncertainty was performed. A list of distributions and determined values of the dominant sources is shown in Appendix A. 3. A quantitative screening of the potential sources of uncertainty using Morris Elementary Effects Analysis was completed. An experimental model using the physics-based fire modeling tool Fire Dynamics Simulator was developed and coupled with the Risk Analysis Virtual Environment. The Morris analysis identified at least two parameters that can be eliminated as significant contributors (specific heat of concrete and cable jacket thickness). 4. Global importance measure (Global IM) analysis to generate a comprehensive ranking based on their influence on the plant risk. In this research, a moment-independent Global IM is used since it can address (a) uncertainty in the input parameters of the fire model, (b) uncertainty in the risk outputs, and (c) non-linearity and interactions among input parameters in the fire model, more accurately than the correlation-based and variance-based global methods. The observations from the research showed that, depending on the initial and boundary conditions of the fire scenarios, fire-induced damage could have a very small probability and could be dominated by the tail of the uncertainty distribution; hence, the accuracy of the correlation-based and variance-based methods is questionable. The moment-independent Global IM analysis in this research provides a better understanding of how experimental uncertainty data affects industry’s plant models and where improvements in that data will have the largest benefit for improving fire modeling accuracy in causing core damage. Among the five unscreened parameters obtained from the Morris EE analysis, the Global IM analysis results for the case study indicated that max heat release rate and fire location are the most important parameters. The report also outlines benefits of using a unified computational platform that integrates the underlying simulations (e.g., a fire progression model), quantitative screening (using the Morris EE method), and the Global IM analysis. A unified platform can (i) facilitate the ranking of input parameters considering multiple key fire scenarios simultaneously, rather than considering one scenario at a time, (ii) contribute to more explicit and accurate treatment of dependencies at multiple levels of Fire PRA, (iii) facilitate the sampling-based uncertainty quantification for Fire PRA, and (iv) help generating both “industry-wide” and "plant-specific" ranking of uncertainty sources in Fire PRA. Future research should be done to include additional parameters such as detection/suppression or cable fire spread. Adding a PRA software such as SAPHIRE to the RAVEN platform would help with plant model integration and improve treatment of fire-induced dependency. The I-PRA risk importance ranking methodology offered in this report can provide valuable information for efficiently (a) enhancing the realism of Fire PRA for existing plants and (b) supporting the development of Dynamic Fire PRA for advanced reactors and new plants.

97 MATHEMATICS AND COMPUTING↗