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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

stochastic calculus↗
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 OSTI2023

Simulation-Based Recovery Action Analysis Using the EMRALD Dynamic Risk Assessment Tool

A recovery action is defined as the action that prevents deviant conditions from producing unwanted effects. It generally indicates a kind of countermeasure performed in response to a failure of human action. The recovery actions especially play an important role in complex systems like nuclear power plants (NPPs), which consist of highly sophisticated controllers to ensure that desired performance and safety must be achieved and maintained. This is because a combination of human error and its recovery failure may be able to cause a catastrophic effect on a system. Analyzing recovery actions has been a critical part of HRA, which is a technique to evaluate human errors and provide human error probabilities (HEPs) for application in probabilistic safety assessment (PSA). If recovery actions are not adequately analyzed and applied to PSA models, the PSA results may be under-estimated or be not able to reasonably account for the failure of human actions in the context of PSA. For this reason, some regulatory documents such as ASME/ANS RA-Sb-2013 by the American Society for Mechanical Engineers and the American Nuclear Society and NUREG-1792 by U.S. Nuclear Regulatory Commission have emphasized the importance of recovery analysis within the HRA. A couple of existing HRA methods, such as the Technique for Human Error-Rate Prediction (THERP), the Cause-Based Decision Tree (CBDT), and the Korean Standard HRA (K-HRA), have respectively suggested their own approaches to the HRA recovery analysis. However, there are a couple of limitations to treating recovery actions using only the current HRA methods available. The biggest limitation is that the existing recovery analysis does not explicitly consider a variety of recovery action types and recovery sequences as they occur in actual NPPs. To handle the limitations of existing recovery analysis, this study proposes a simulation-based recovery analysis method using the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software. The EMRALD software is a dynamic simulation tool for PSA. It supports realistic and dynamic modeling of human actions as they would be performed at NPPs. It is also favorable to simultaneously model the specific moment at which an action is performed, the time it takes to perform the action, and the failure probability of that action. In this paper, a detailed methodology for modeling recovery actions in the simulation platform is proposed with a couple of examples. Then, outputs from the simulation are discussed as reviewing if this novel approach can complement the challenges of existing recovery analyses.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Development of mechanistic, microstructure-informed BISON models for fission product-induced failure mechanisms in advanced nuclear fuels

The US continues to prioritize commercial deployment of advanced reactors—particularly those utilizing U-Zr metallic and TRISO particle fuels. Fission product-induced failure mechanisms for these systems include fuel–cladding chemical interaction in metallic fuel rods, which threatens cladding integrity, and Pd penetration in TRISO particles, which degrades SiC layer properties. Empirical models can be applied within the bounds of existing irradiation databases, but their utility is limited when considering new designs or investigating fundamental material behaviors. The Nuclear Energy Advanced Modeling and Simulation Program is therefore developing mechanistic models for these behaviors, which are expected to aid in fuel design, assist in development of failure mitigation strategies, and provide support for qualification and licensing. These efforts leverage multiscale capabilities to capture the microstructural features and processes that govern these behaviors. This talk summarizes past and ongoing efforts to develop and validate these models for the BISON fuel performance code.

FCCI↗
NASA NTRSDate not supplied

A Systems Approach to AI Model Integration and Performance Evaluation for the Generic UAM Simulation Framework

This paper introduces py-guam, an open-source experimentation framework developed for the NASA Generic Urban Air Mobility simulation (GUAM) environment, facilitating the integration and evaluation of advanced artificial intelligence (AI) algorithms. We present a systems approach which enables the seamless incorporation of data-driven models, including off-nominal and failure state detection, into the GUAM’s Cognitive Architecture (CA). The framework supports customizable experimentation parameters, derives Safety Performance Indicators (SPIs) from UL 4600 safety case analyses, and employs rapid UAM simulations to assess AI impacts on flight performance across diverse scenarios. Through comprehensive testing and validation experiments, we demonstrate GUAM’s capability to enhance safety and efficiency in urban air mobility operations. Additionally, the open-source nature of py-guam fosters community collaboration, ensuring continuous improvement and adaptability to evolving technological advancements. This work establishes a robust tool for developing and testing AI-driven urban air mobility (UAM) systems, advancing the safety and reliability of autonomous urban air vehicles.

Artificial Intelligence↗
NASA NTRS2008

Simulation of Stochastic Processes by Coupled ODE-PDE

A document discusses the emergence of randomness in solutions of coupled, fully deterministic ODE-PDE (ordinary differential equations-partial differential equations) due to failure of the Lipschitz condition as a new phenomenon. It is possible to exploit the special properties of ordinary differential equations (represented by an arbitrarily chosen, dynamical system) coupled with the corresponding Liouville equations (used to describe the evolution of initial uncertainties in terms of joint probability distribution) in order to simulate stochastic processes with the proscribed probability distributions. The important advantage of the proposed approach is that the simulation does not require a random-number generator.

Zak, Michail↗
DOE OSTI2021

Unraveling disadhesion mechanism of epoxy/CSH interface under aggressive conditions

Almost all FRP-reinforced concrete exposed to the marine environment are susceptible to durability deficiencies due to failure of the FRP/epoxy/concrete interface, especially the vulnerable epoxy/concrete interface, which is frequently attacked by water and ions. Herein, molecular dynamics simulations of epoxy/CSH interface under different environmental exposures are utilized to specifically elucidate the degradation principles of water and ions on the bonding properties and mechanical responses of the epoxy/concrete interface. The environmental sequences associated with the interfacial bonding degradation are arranged as Na{sub 2}SO{sub 4} + NaCl>NaCl>Na{sub 2}SO{sub 4} > Water>Dry. Remarkably, water molecules weaken the interaction between the epoxy and CSH by robbing interfacial H- and Ca-O bonds, thereby reducing the energy barrier to interfacial peel and shear failure. The weakening effects are exacerbated by the presence of aggressive ions, as Na{sup +} ions attracted to the CSH surface accumulate more water molecules in the interfacial region by forming hydrated ions clusters, which ultimately accelerates the epoxy/CSH interfacial degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Damage and Failure in a Statistical Crack Model

In this paper I will take a close look at a statistical crack model (SCM) as is used in engineering computer codes to simulate fracture at high strain rates. My general goal is to understand the macroscopic behavior effected by the microphysical processes incorporated into an SCM. More specifically, I will assess the importance of including local interactions between cracks into the growth laws of an SCM. My strategy will be to construct a numerical laboratory that represents a single computational cell containing a realization of a statistical distribution of cracks. The cracks will evolve by the microphysical models of the SCM, leading to quantifiable damage and failure of the computational cell. I will use the numerical data generated by randomly generated ensembles of the fracture process to establish scaling laws that will modify and simplify the implementation of the SCM into large scale engineering codes.

42 ENGINEERING↗
NASA NTRS2000

Sliding Mode Control of the X-33 with an Engine Failure

Ascent flight control of the X-3 is performed using two XRS-2200 linear aerospike engines. in addition to aerosurfaces. The baseline control algorithms are PID with gain scheduling. Flight control using an innovative method. Sliding Mode Control. is presented for nominal and engine failed modes of flight. An easy to implement, robust controller. requiring no reconfiguration or gain scheduling is demonstrated through high fidelity flight simulations. The proposed sliding mode controller utilizes a two-loop structure and provides robust. de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of engine failure, bounded external disturbances (wind gusts) and uncertain matrix of inertia. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues. Conditions that restrict engine failures to robustness domain of the sliding mode controller are derived. Overall stability of a two-loop flight control system is assessed. Simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in the presence of external disturbances and vehicle inertia uncertainties, as well as the single engine failed case. The designed robust controller will significantly reduce the time and cost associated with flying new trajectory profiles or orbits, with new payloads, and with modified vehicles

Shtessel, Yuri B.↗
DOE OSTI2022

Predicting the location of shear band initiation in a metallic glass

We report atomistic simulation results which indicate that the location of shear banding in a metallic glass (MG) can be ascertained with reasonably high accuracy solely from the undeformed static structure. Correlation is observed between the location of the initiation of shear bands in a simulated MG and the initial distribution of the density of fertile sites (DFS) for stress-driven shear transformations identified a priori based on a deep learning model devised in our recent work. In addition, we demonstrated that one can judge whether a glass is brittle or ductile solely based upon its initial DFS distribution. These validate that shear bands in MG arise from nonlinear instabilities and that the as-quenched glass structure contains inhomogeneities that influence these instabilities. In this study, we also reveal an important subtlety regarding the nondeterministic nature of athermal quasistatic shear simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mitigating Cascading Outages in Severe Weather Using Simulation-Based Optimization

Severe weather events can trigger cascading power outages and lead to significant losses. In this work, we investigate cascading outage mitigation under severe weather conditions. Given day-ahead weather forecasts and component failure models, we aim to identify a set of power lines that can be hardened to minimize the expected impact of potential cascading outages. Since the expected load shedding cannot be expressed as an explicit function of line hardening decisions and system states, we developed a cascading outage simulator to estimate the expected value of load shedding under various initial weather-related disruption scenarios generated using a weather forecast. To avoid massive enumeration of all possible combinations of line hardening decisions and reduce the simulation efforts, we employed an efficient simulation-based optimization approach that quickly identifies the (near) optimal line hardening decisions in the presence of both large simulation noises due to the highly variable initial disturbances and system states, and significant randomness in the subsequent cascades. Furthermore, the algorithm is also able to utilize parallel computing to dramatically reduce computation time to support decision making in preparation for severe weather conditions. We performed a case study on the Northeast Power Coordinating Council (NPCC) 140-bus system model to demonstrate that our approach can significantly improve power grid resilience to adverse weather events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

LaueMatching: an approach for rapid and robust indexing of Laue diffraction patterns

Traditional Laue diffraction pattern indexing often struggles with noisy data, weak signals, peak overlap and missing reflections, particularly from complex or deformed microstructures. Here, we introduce LaueMatching, a high-throughput indexing algorithm designed to overcome these limitations. LaueMatching utilizes a fundamentally different approach based on direct pattern correlation: experimentally pre-processed images are compared against a comprehensive pre-computed library of simulated diffraction patterns corresponding to a dense grid of possible orientations. This approach bypasses the need for explicit peak identification and fitting, steps that are often a failure point for traditional methods. The algorithm rapidly and robustly indexes multiple crystallographic orientations and crystal systems simultaneously, even from challenging patterns. LaueMatching's effectiveness and accuracy have been rigorously tested and validated on diverse experimental (Ni, Al, EuAl 2 O 4 ) and simulated diffraction patterns, demonstrating high-fidelity orientation refinement. Code to implement this approach on both CPU and GPU resources can be downloaded from https://github.com/AdvancedPhotonSource/LaueMatching.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rear-Side Irradiance Simulation of Field PV Modules

Assessing the durability of photovoltaic (PV) module backsheet is critical to increasing module lifetime. Historically, laboratory-based accelerated testing has insufficient in predicting large-scale failures of commercial polymeric materials. Additionally, there is growing concern that standard condition tests do not reflect non-uniformities in field exposure, and that certain modules experience more severe degradation due to their location. Anisotropy in field exposures is installation-dependent and reflects different levels of exposure to irradiance due to mounting geometry, ground surface albedo, and climatic zone. "Bificial_Radiance" [1], simulates the amount of reflected irradiance on the Polyethylene Naphthalate (PEN) backsheet of a PV array located in Maryland. In our work, site specific weather data are gathered for the entire length of exposure for the modules. The total full-spectrum dose for the incident irradiance on the backsheet was then determined. The simulation results are integrated with historical field survey data to better understand real orld outdoor degradation.

backsheet↗
DOE OSTI2023

Chapter 6: Abuse Response of Batteries Subjected to Mechanical Impact

Electrochemical and thermal models to simulate nominal performance and abuse response of lithium-ion cells and batteries have been reported widely in the literature. Studies on mechanical failure of cell components and how such events interact with the electrochemical and thermal response are relatively less common. This chapter outlines a framework developed under the Computer Aided Engineering for Batteries program to couple failure modes resulting from external mechanical loading to the onset and propagation of electrochemical and thermal events that follow. Starting with a scalable approach to implement failure criteria based on thermal, mechanical, and electrochemical thresholds, we highlight the practical importance of these models using case studies at the cell and module level. The chapter also highlights a few gaps in our understanding of the comprehensive response of batteries subjected to mechanical crash events, the stochastic nature of some of these failure events, and our approach to build safety maps that help improve robustness of battery design by capturing the sensitivity of some key design parameters to heat generation rates under different mitigation strategies.

abuse simulations↗
DOE OSTI2020

Enhancement of risk informed validation framework for external hazard scenario

In recent years, the U.S. Nuclear Regulatory Commission (USNRC) and the International Atomic Energy Agency (IAEA) have developed methodologies to assess the vulnerabilities of nuclear plants against site specific extreme hazards. In many cases, advanced simulation tools are being considered to simulate multi-physics, multi-scale phenomena and to evaluate vulnerability of nuclear facilities. The credibility of advanced simulation tools is assessed based on a formal verification, validation, and uncertainty quantification procedure. One of the key limitations in validation is the lack of relevant experimental data at system-level. This limitation leads to a decrease in the confidence of system-level risk predictions. Therefore, a robust validation framework is needed to formalize the confidence in predictive capability of advanced simulation results. Additionally, this study enhances the existing risk informed validation methodology, originally proposed by Kwag et al. [1] and Bodda et al. [2], by developing additional attributes and a new set of validation indicies for a complete and wider applicability of the framework. In this manuscript, the methodology to identify the critical path that leads to the system-level failure is illustrated. The overall validation is checked for completeness and consistency by comparing the critical path for both the system-level simulation and experimental models. The applicability of the code for an intended application is represented in terms of various maturity levels and helps in the process of decision making.

42 ENGINEERING↗
NASA NTRS2017

Quantifying Pilot Contribution to Flight Safety during Hydraulic Systems Failure

Accident statistics cite the flight crew as a causal factor in over 60% of large transport aircraft fatal accidents. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. The latter statement, while generally accepted, cannot be verified because little or no quantitative data exists on how and how many accidents/incidents are averted by crew actions. A joint NASA/FAA high-fidelity motion-base human-in-the-loop test was conducted using a Level D certified Boeing 737-800 simulator to evaluate the pilot's contribution to safety-of-flight during routine air carrier flight operations and in response to aircraft system failures. To quantify the human's contribution, crew complement (two-crew, reduced crew, single pilot) was used as the independent variable in a between-subjects design. This paper details the crew's actions, including decision-making, and responses while dealing with a hydraulic systems leak - one of 6 total non-normal events that were simulated in this experiment.

Kramer, Lynda J.↗
NASA NTRS2002

Computational Simulation of the High Strain Rate Tensile Response of Polymer Matrix Composites

A research program is underway to develop strain rate dependent deformation and failure models for the analysis of polymer matrix composites subject to high strain rate impact loads. Under these types of loading conditions, the material response can be highly strain rate dependent and nonlinear. State variable constitutive equations based on a viscoplasticity approach have been developed to model the deformation of the polymer matrix. The constitutive equations are then combined with a mechanics of materials based micromechanics model which utilizes fiber substructuring to predict the effective mechanical and thermal response of the composite. To verify the analytical model, tensile stress-strain curves are predicted for a representative composite over strain rates ranging from around 1 x 10(exp -5)/sec to approximately 400/sec. The analytical predictions compare favorably to experimentally obtained values both qualitatively and quantitatively. Effective elastic and thermal constants are predicted for another composite, and compared to finite element results.

Goldberg, Robert K.↗
DOE OSTI2023

TReactMech v4.217

TReactMech couples geomechanical processes (poroelasticity, failure, and inelastic strain) with multiphase nonisothermal flow (derived from TOUGH2) and reactive geochemical transport. At its core is the reactive-transport code TOUGHREACT v4.13. TReactMech is an efficient hybrid parallel simulator, solving the geomechanics using finite elements and MPI/PetSc, the multiphase flow using integrated finite difference and MPI/PETSc, and the reactive chemistry using OpenMP. The advantages of TReactMech are in its multiphase flow capabilities (e.g., supercritical CO2, supercritical water, air) and parallel geomechanics including full 3-D stress tensor, shear and tensile failure, coupled to porosity and permeability changes. It is backwardly compatible with TOUGH2 and TOUGHREACT v4.13, allowing for easier transitions between the codes. TReactMech can be used to simulate many natural and engineered subsurface systems, including geothermal reservoirs, borehole heat exchangers, geologic carbon sequestration, geologic storage of nuclear waste, groundwater resources, weathering, sediment diagenesis, seafloor hydrothermal circulation, hydrofracturing in unconventional reservoirs, and injection/production-induced surface deformation.

Sonnenthal, Eric↗