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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Probabilistic Assessment of Structural Integrity

A probability-based approach, combining deterministic and probabilistic methods, was developed for analyzing building and component failures, which are especially crucial for complex structures like nuclear power plants. This method links finite element and probabilistic software to assess structural integrity under static and dynamic loads. This study uses NEPTUNE software, which is validated, for a deterministic transient analysis and ProFES software for probabilistic models. In a case study, deterministic analyses with varied random variables were transferred to ProFES for probabilistic analyses of piping failure and wall damage. A Monte Carlo Simulation, First-Order Reliability Method, and combined methods were employed for probabilistic analyses under severe transient loading, focusing on a postulated accident at the Ignalina Nuclear Power Plant. The study considered uncertainties in material properties, component geometry, and loads. The results showed the Monte Carlo Simulation method to be conservative for high failure probabilities but less so for low probabilities. The Response Surface/Monte Carlo Simulation method explored the impact load–failure probability relationship. Given the uncertainties in material properties and loads in complex structures, a deterministic analysis alone is insufficient. Probabilistic analysis is imperative for extreme loading events and credible structural safety evaluations.

Mathematics↗
DOE OSTI2024

How Does Vertical Wind Shear Influence Updraft Characteristics and Hydrometeor Distributions in Supercell Thunderstorms?

Abstract Vertical wind shear is known to affect supercell thunderstorms by displacing updraft hydrometeor mass downshear, thereby facilitating the storms’ longevity. Shear also impacts the size of supercell updrafts, with stronger shear leading to wider, less dilute, and stronger updrafts with likely greater hydrometeor production. To more clearly define the role of shear across different vertical layers on hydrometeor concentrations and displacements relative to supercell updrafts, a suite of idealized numerical model simulations of supercells was conducted. Shear magnitudes were systematically varied across the 0–1, 1–6, and 6–12 km AGL layers, while the thermodynamic environment was held fixed. Simulations show that as shear magnitude increases, especially from 1 to 6 km, updrafts become wider and less dilute with an increase in hydrometeor loading, along with an increase in the low-level precipitation area/rate and total precipitation accumulation. Even with greater updraft hydrometeor loading amid stronger shear, updrafts are more intense in stronger shear simulations due to larger thermal buoyancy owing to wider, less dilute updraft cores. Furthermore, downshear hydrometeor displacements are larger in environments with stronger 1–6-km shear. In contrast, there is relatively less sensitivity of hydrometeor concentrations and displacements to variations in either 0–1- or 6–12-km shear. Results are consistent across free tropospheric relative humidity sensitivity simulations, which show an increase in updraft size and hydrometeor mass with increasing free tropospheric relative humidity owing to a reduction in entrainment-driven dilution for wider updrafts in moister environments. Significance Statement Rotating thunderstorms, known as supercells, are able to persist for multiple hours. One common explanation is that large changes in wind speed and/or direction with height, or shear, transport rain/hail away from supercell updrafts, supporting their maintenance. The strong shear within supercell environments, however, may also lead to greater rail/hail amounts, thereby leading to weaker storms due to this extra mass of water/ice within updrafts. Furthermore, the impact of shear across different height layers on supercell rain/hail characteristics has not been thoroughly investigated. In this study, computer simulations of supercells were conducted to determine that shear occurring between 1 and 6 km above ground level has a large impact on rain/hail distribution in supercells and that stronger shear in this layer leads to wider/stronger supercells with greater rain/hail accumulations at the surface. Additionally, some of the extra mass of water/ice is transported farther away from updrafts due to the stronger environmental storm-relative winds.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Real-World Distribution System Modeling Framework for Transmission-and-Distribution Cosimulation: Preprint

This paper presents a modeling methodology for realistic distribution system simulation and analysis. The methodology involves three major approaches: utility model conversion, feeder load modeling, and feeder model validation. The feeder models obtained from the utility are converted to the format that is more flexible for analysis and algorithm development. The load profiles down to each node are modeled in detail using advanced metering infrastructure data and supervisory control and data acquisition (SCADA) system measured load data. Then the distribution system models are validated by comparing the simulated feeder-head voltage results and SCADA measured voltage data. To better understand the bulk system operations and the interactions between transmission and distribution systems, the modeled realistic distribution systems are integrated into a transmission-and-distribution cosimulation framework to perform the system simulation from the bulk system down to each node in the distribution system.

load modeling↗
DOE OSTI2024

Multiscale simulation of spatially correlated microstructure via a latent space representation

When deformation gradients act on the scale of the microstructure of a part due to geometry and loading, spatial correlations and finite-size effects in simulation cells cannot be neglected. We propose a multiscale method that accounts for these effects using a variational autoencoder to encode the structure–property map of the stochastic volume elements making up the statistical description of the part. In this paradigm the autoencoder can be used to directly encode the microstructure or, alternatively, its latent space can be sampled to provide likely realizations. Furthermore, we demonstrate the method on three examples using the common additively manufactured material AlSi10Mg in: (a) a comparison with direct numerical simulation of the part microstructure, (b) a push forward of microstructural uncertainty to performance quantities of interest, and (c) a simulation of functional gradation of a part with stochastic microstructure.

Elastoplasticity↗
DOE OSTI2020

Numerical study of advanced compression ignition and combustion in a gasoline direct injection engine

Multi-mode combustion strategies may provide a considerable thermal efficiency improvement targeted at part-load operating conditions for light-duty spark-ignition (SI) engines. The extension from boosted SI mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing compression ratio and utilizing intake air heating. In order to enable an accurate control of intake charge condition for ACI control and rapid mode-switches, it is essential to gain fundamental insight into the autoignition process with regard to thermal and fuel-air mixture stratification in the combustion chamber. In this work, a computational fluid dynamics (CFD) study is carried out to reveal some degrees of correlation between the mixture and thermal stratifications induced by the cylinder wall temperature and combustion-phasing across varying engine load conditions. The computational analysis begins with a calibrated simulation setup best matching the engine experiments, and subsequently evaluates the baseline setup for an extended range of engine load conditions for two excess-air ratio cases. The present study emphasizes the dominance of thermal stratifications for autoignition process due to wall temperature effects depending on the engine load conditions of interest. In addition, this study also aims to provide insight into the impact of mixture stratification on cyclic variability, especially at colder wall engine conditions (e.g., cold start). Observations herein provide highlight of the propensity of autoignition in correlation with mixture reactivity space.

Advanced Compression Ignition (ACI) engine↗
DOE OSTI2022

Evaluation of dynamic testing of full-scale wind turbine drivetrains with hardware-in-the-loop

Dynamometer testing of full-scale wind turbine drivetrains involves subjecting integrated components to extreme static loads, fatigue loads, or dynamic loads to replicate field conditions. This paper provides a detailed evaluation of the uncertainty and errors in applied loads and measured responses, and their magnitude relative to established repeatability bounds for a drivetrain subjected to static and dynamic loads on the 7.5 MW test bench at the Clemson University Wind Turbine Drivetrain Testing Facility. An ideal drivetrain simulation model is utilized to isolate the influence of load tracking errors on test article responses. It is shown that the test article response variations are mainly driven by run out and clearances inherent to the drivetrain. For the dynamic profiles, the load tracking errors are within acceptable limits. Furthermore, a frequency analysis is used to show that the test bench controller tracking performance is acceptable for profiles with frequency content up to 1.5 Hz.

17 WIND ENERGY↗
DOE OSTI2026

Demonstration of thermal fracture limits of gas-cooled Nd:APG-1 and Tm:YLF slabs

High-energy short-pulse laser systems demonstrated to date have been limited to low repetition rates due to significant thermal management challenges associated with scaling these systems to high average power, including the need to understand the thermal fracture limits of laser gain media. In this paper, we demonstrate the thermal fracture limits of two high-average-power gain media in a realistic diode-pumped amplifier geometry: a 5 mm thick Nd:APG-1 slab and a 2 mm thick Tm:YLF slab, both cooled by room-temperature helium gas. Finite element analysis revealed maximum tensile stress at fracture of 25 ± 3 MPa for Nd:APG-1 and 30 ± 3 MPa for Tm:YLF. These stress levels correspond to average volumetric heat loads of 13 ± 1 W/cm 3 in Nd:APG-1 and 247 ± 12 W/cm 3 in Tm:YLF. Additional simulations show geometric scaling: thinner slabs tolerate higher heat loads before fracture, while larger pump spots reach the fracture stress at lower heat loads.

Lasers↗
DOE OSTI2025

Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output

A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on Fe(8–9)%Cr are the most promising candidates for some fusion reactor structures. Although there are indications that RAFM steel could be viable for fusion applications at temperatures up to 600°C, the maximum operating temperature will be determined by the creep properties of the structural material and the breeder material compatibility with the structural material. Due to the relative paucity of available creep data on F82H steel compared to other alloys such as Grade 91 steel, micromechanical models are sought for simulating creep based on relevant deformation mechanisms. As a point of departure, this work recalibrates a model form that was previously proposed for Grade 91 steel to match creep curves for F82H steel. Due to the large number of parameters (9) and cost of the nonlinear simulations, an automated approach for tuning the parameters is pursued using a recently developed Bayesian optimization for functional output (BOFO) framework (Huang et al., 2021, “Bayesian optimization of functional output in inverse problems,” Optim. Eng., 22, pp. 2553–2574). Incorporating extensions such as batch sequencing and weighted experimental load cases into BOFO, a reasonably small error between experimental and simulated creep curves at two load levels is achieved in a reasonable number of iterations. In conclusion, validation with an additional creep curve provides confidence in the fitted parameters obtained from the automated calibration procedure to describe the creep behavior of F82H steel.

42 ENGINEERING↗
DOE OSTI2022

Maximum power point tracking for a multi-layered piezoelectric heel charger with a levered mechanism toward impact-based energy harvesting

The piezoelectric footstep energy harvester does not always work at its maximum power point when the external load is fixed, as the optimal load changes when the walking excitation alters. Thus, the harvesting efficiency is downgraded largely in real-life scenarios compared to in-lab experiments and theoretical or numerical predictions due to the mismatch between the actual load and the optimal load. To address this issue, the concept of Maximum Power Point Tracking (MPPT) is investigated in this paper and the circuit design is implemented for a multi-layered levered piezoelectric footstep energy harvester (heel charger). The proposed event-driven MPPT circuit interface with a customized buck converter aims to maximize the power gained from daily walking using the heel charger to power a fixed load, such as smart insole or shoes. The MPPT circuit design is conceptually simulated and then tested with the heel charger to further validate if it works at its maximum power point when the frequency of the input excitation alters. Results show that the extracted power from the heel charger connected to a fixed resistance load with MPPT implementation is improved up to 300% compared to the one without MPPT implementation in simulation and up to 180% in the experiment when connected to a fixed load. The difference between simulation and experimental results is due to the optimization of using voltage sources as the heel charger and the control signals (pulse width modulation) from the microcontroller in the simulation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Structural and Spectroscopic Properties of Butanediol-Modified Boehmite Materials

Glycoboehmite (GB) materials are synthesized by a solvothermal reaction to form layered aluminum oxyhydroxide (boehmite) modified by intercalated butanediol molecules. These hybrid materials offer a platform to design materials with potentially novel sorption, wetting, and catalytic properties. Several synthetic methods have been used, resulting in different structural and spectroscopic properties, but atomistic detail is needed to determine the interlayer structure to explore the synthetic control of GB materials. Here, in this study, we use classical molecular dynamics (MD) simulations to compare the structural properties of GB interlayers containing chemisorbed butanediol molecules as a function of diol loading. Accompanying quantum (density functional theory, DFT) static calculations and MD simulations are used to validate the classical model and compute the infrared spectra of various models. Classical MD results reveal the existence of two unique interlayer environments at higher butanediol loading, corresponding to smaller (cross-linked) and expanded interlayers. DFT-computed infrared spectra reveal the sensitivity of the aluminol O–H stretch frequencies to the interlayer environment, consistent with the spectrum of the synthesized material. Insight from these simulations will aid in the characterization of the newly synthesized GB materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Bayesian optimal experimental design for constitutive model calibration

Computational simulation is increasingly relied upon for high/consequence engineering decisions, which necessitates a high confidence in the calibration of and predictions from complex material models. However, the calibration and validation of material models is often a discrete, multi-stage process that is decoupled from material characterization activities, which means the data collected does not always align with the data that is needed. To address this issue, an integrated workflow for delivering an enhanced characterization and calibration procedure—Interlaced Characterization and Calibration (ICC)—is introduced and demonstrated. Further, this framework leverages Bayesian optimal experimental design (BOED), which creates a line of communication between model calibration needs and data collection capabilities in order to optimize the information content gathered from the experiments for model calibration. Eventually, the ICC framework will be used in quasi real-time to actively control experiments of complex specimens for the calibration of a high-fidelity material model. This work presents the critical first piece of algorithm development and a demonstration in determining the optimal load path of a cruciform specimen with simulated data. Calibration results, obtained via Bayesian inference, from the integrated ICC approach are compared to calibrations performed by choosing the load path a priori based on human intuition, as is traditionally done. The calibration results are communicated through parameter uncertainties which are propagated to the model output space (i.e. stress–strain). In these exemplar problems, data generated within the ICC framework resulted in calibrated model parameters with reduced measures of uncertainty compared to the traditional approaches.

42 ENGINEERING↗
DOE OSTI2022

Hybrid-RL-MPC4CLR (Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids)

Hybrid-RL-MPC4CLR was developed as a hybrid controller for active distribution grid critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. The RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while the MPC models grid operations incorporating the RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. The developers formulated the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The software is developed using various software packages in Python. The MPC's optimal power flow (OPF) model is implemented using the Pyomo package, the RL simulation environment is implemented using the MPC simulation with various scenarios of renewable energy and load demand profiles and power outage beginning times, based on the OpenAI Gym framework. The RL agent training is performed using the RLlib Ray package. The RL algorithm is trained offline using historical forecasts of renewable generation and load demand profiles. Simulation analysis and performance tests are conducted using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery.

Eseye, Abinet Tesfaye↗
DOE OSTI2026

Roadrunner

SAND2026-17073O Roadrunner software provides a comprehensive platform for simulating the mechanical behavior of crystalline materials under various loading conditions, allowing users to investigate the effects of dislocation slip hardening and damage evolution. Developed as a fork of the Multiphysics Object Oriented Simulation Environment (MOOSE) software from Idaho National Laboratory, Roadrunner is optimized for high-performance computing and can simulate large-scale problems, enabling researchers to explore complex scenarios. Its applications include material design and optimization in aerospace and automotive industries, investigation of failure mechanisms in structural materials, and development of predictive models for crystalline materials under various loading conditions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Lim, Hojun [Sandia National Lab. (SNL-CA), Livermo↗
DOE OSTI2021

First Annual Report on Development of Microwave Resonant Cavity Transducer for Fluid Flow Sensing: Development of Sensor Performance Model of Microwave Cavity Flow Meter for Advanced Reactor High Temperature Fluids

We are investigating a microwave cavity-based transducer for in-core high-temperature fluid flow sensing in molten salt cooled reactors (MSCR) and sodium fast reactors (SFR). This sensor is a hollow metallic cylindrical cavity, which can be fabricated from stainless steel, and as such is expected to be resilient to radiation, high temperature and corrosive environment of MSCR and SFR. The principle of sensing consists of making one wall of the cylindrical cavity flexible enough so that dynamic pressure, which is proportional to fluid velocity, will cause membrane deflection. Membrane deflection causes cavity volume change, which leads to a shift in the resonant frequency. Feasibility of the sensor was initially investigated with analytical derivations and with COMSOL RF Module computer simulations of resonant frequency spectral shift due to uniform load. We also investigated the mechanical integrity of the flowmeter’s membrane through analytical modelling and COMSOL Structural Mechanics Module computer simulations. Both the analytic model and COMSOL model showed that maximum stresses on the plate, which are at the radial boundary of the plate, are three orders of magnitude smaller than the material’s yield strength and ultimate tensile strength. This indicates that the sensor is at a low risk of mechanical failure. Using results from models, we have developed an initial design for a microwave K-band sensor. A cylindrical resonator prototype was fabricated from brass for the initial tests. The external dimensions of the cavity are matched to the flange of a standard WR-42 waveguide. Microwave field is coupled into the resonant cavity through a subwavelength-size aperture. A test article was developed consisting of a piping Tee with a bulkhead WR-42 microwave waveguide installed in a leak-proof assembly. A microwave waveguide circulator was installed in the setup to suppress the effect of reflections at the cavity entrance by increasing the isolation between the input and the output port. Preliminary spectral characterization of cavity spectral response was performed with a portable PXIe chassis microwave VNA with a custom GUI. Preliminary dry tests of the transducer response were conducted with a set of calibrated weights. Transducer frequency shift was shown to be monotonically increasing with increasing pressure. The next steps will involve investigation of the transducer performance for water flow sensing.

42 ENGINEERING↗
DOE OSTI2020

Effects of Photovoltaic Module Materials and Design on Module Deformation Under Load

Quasi-static structural finite-element models of an aluminum-framed crystalline silicon photovoltaic module and a glass-glass thin-film module were constructed and validated against experimental measurements of deflection under uniform pressure loading. Specific practices in the computational representation of module assembly were identified as influential to matching experimental deflection observations. Additionally, parametric analyses using Latin hypercube sampling were performed to propagate input uncertainties related to module materials, dimensions, and tolerances into uncertainties in simulated deflection. Sensitivity analyses were performed on the uncertainty quantification datasets using linear correlation coefficients and variance-based sensitivity indices to elucidate key parameters influencing module deformation. Results identified edge tape and adhesive material properties as being strongly correlated to module deflection, suggesting that optimization of these materials could yield module stiffness gains at par with the conventionally structural parameters, such as glass thickness. This exercise verifies the applicability of finite-element models for accurately predicting mechanical behavior of solar modules and demonstrates a workflow for model-based parametric uncertainty quantification and sensitivity analysis. Finally, applications of this capability include the assessment of field environment loads, derivation of representative loading conditions for reduced-scale testing, and module design optimization, among others.

42 ENGINEERING↗
DOE OSTI2023

Preliminary Nuclear Containment Vessel Modeling for Multi-Hazard Probabilistic Risk Assessment under Seismic Hazards and Concrete Degradation

The current practice for natural phenomena hazards (NPH) risk assessment of nuclear facilities is to compute the risk for each hazard independently and then compound the total risk as a combination of single hazard risks. This state of practice does not consider correlations between hazards and the cascading impacts to structures, systems, and components (SSCs), and could thus underestimate the NPH risk or overestimate the nuclear facility safety. Events such as the Fukushima Daiichi accident have highlighted the importance of multi-hazard risk considerations to nuclear power plants (NPPs) that quantify the cascading damage effects to SSCs in the risk models. Moreover, the current fleet of NPPs in the United States is aging; these NPPs are now expected to operate well beyond their initially planned design life. Aging-related deterioration can potentially decrease the capacity of critical structures such as containment vessels to withstand NPH. Such aging considerations may not be adequately accounted for by the current NPH risk assessment guidelines. This paper presents a preliminary modeling and simulation of a representative reinforced concrete containment vessel subjected to seismic mainshock and aftershock considering concrete degradation due to alkali silica reaction. The broader aim is to develop multi-hazard time-dependent fragility functions that could be subsequently used in the probabilistic risk assessment (PRA) model. The multi-hazard component comes into play due to the consideration of damage to the containment vessel under seismic loads and concrete degradation. Consideration of concrete degradation also brings into play the time-dependent nature of the containment vessel response. The response of the containment vessel under varying degrees of concrete degradation to seismic loads is investigated. The results presented are simulated using the Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) software for seismic analysis and the Blackbear software for concrete degradation and damage modeling. Both software are open source and developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE).

42 ENGINEERING↗
DOE OSTI2023

Recent Beam Stability Analysis for the EIC

This document summarizes work done in WBS 6.02.02 during FY23. Additional details can be found in the EIC overview paper presented at IPAC’23 [1], and the references therein. Progress has been made in the ESR and HSR lattice design, dynamic aperture optimization, and the RCS lattice design. The impedance and Collective effects are progressing and include the impedance optimization process of the vacuum systems for RCS, HSR, and ESR; collective effects studies; collective effects and beam-beam interaction; coupled bunch instabilities and the crab cavities; low-level RF feedback system design and beam-ion instability. The reversed phasing RF system has been numerically studied for the ESR to mitigate Robinson instability and demonstrate reliable stable beam operation. Various codes, including C++, SPACE [2], ELEGANT [3], and Mbtrack2 [4] have been employed to benchmark the results. The simulation of HSR bunch splitting with beam loading has been performed at 275 GeV energy. The evaluation of Beam Position Monitors aimed to validate their expected performance, with the primary objective being to verify their accuracy. Calculations of Electron Polarization in the ESR, RCS, and HSR are showing good progress. In the RCS, preliminary studies indicate excellent polarization transmission over intrinsic spin resonances, achieving over 90% transmission with improved performance compared to the previous lattice. Preliminary simulations in the ESR indicate encouraging results in minimizing depolarization and improving equilibrium polarization.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

QUOKKA-based understanding of outflows (QED) – III. Outflow loading and phase structure as a function of galactic environment

ABSTRACT We present results from a suite of 3D high-resolution hydrodynamic simulations of supernova-driven outflows from galactic disc regions with a range of gas surface density, metallicity, and supernova scale height. We use this suite to quantify how outflow properties – particularly the loading factors for mass, metallicity, and energy – vary with these parameters. We find that the winds fall into three broad categories: steady and hot, multiphase and moderately bursty, and cool and highly bursty. The first of these is characterized by efficient metal and energy loading but weak mass loading, the second by moderate loading of mass, metals, and energy, and the third by negligible metal and energy loading but substantial mass loading. The most important factor in determining the kind of wind a galaxy will produce is the ratio of supernova to gas scale heights, with the latter set by a combination of supernova rate, metallicity-dependent cooling rate, and the gravitational potential. These often combine in counterintuitive ways – for example increased cooling causes cold clouds to sink into the galactic midplane more rapidly, lowering the volume-filling factor of dense gas and making the environment more favourable for strong winds. Our findings suggest that the nature of galactic winds is likely highly sensitive to phenomena such as runaway stars occurring at a large height and dense gas and are poorly captured in most simulations, and that metal loading factors for type Ia supernovae may be substantially larger than those for type II, with important implications for galactic chemical evolution.

Vijayan, Aditi (ORCID:0000000277142379)↗