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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

New XDM-corrected potential energy surfaces for Ar–NO(X{sup 2}Π): A comparison with CCSD(T) calculations and experiments

We report new potential energy surfaces for the ground state Ar–NO(X{sup 2}Π) van der Waals system calculated using the unrestricted Hartree-Fock (UHF) method with the addition of the Becke-Roussel correlation functional and exchange-hole dipole moment dispersion correction (XDM). We compare UHFBR-XDM surfaces and those previously reported by Alexander from coupled cluster CCSD(T) calculations [J. Chem. Phys. 111, 7426 (1999)]. The bound states of Ar–NO have been investigated with these new UHFBR-XDM surfaces, including relative energy-level spacing, adiabatic bender states and wave functions, and spectroscopic data. These results have been found to be in good agreement with calculations based on the CCSD(T) PESs. These new PESs are used to investigate the inelastic scattering of NO(X) by Ar. Full close-coupling integral cross sections at collision energies of 442 cm{sup −1}, 1774 cm{sup −1} and differential cross sections at collision energy of 530 cm{sup −1} were determined for transitions out of the lowest NO(X) rotational level (j = ω = 1/2,f). These cross sections are in good agreement with those calculated with CCSD(T) and accordingly in good agreement with the most recent initial and final state resolved experimental data. The UHFBR-XDM scheme yields high-quality potential surfaces with computational cost comparable to the Hartree-Fock method and our results may serve as a benchmark for application of this scheme to collisions between larger molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Variational Nodal 2D/1D Transport/Diffusion Solutions of the C5G7 Benchmark Problems

This work is the continuation of our effort to generalize the variational nodal method (VNM) for application to pin-resolved whole-core PWR problems. To this end, a 2D/1D VNM method without spatial homogenization is formulated and implemented in the PANX code. We employ diffusion theory in the axial direction combined with two-dimensional transport in the x-y plane. In our initial work, we employed the standard spherical harmonics method. To increase accuracy and reduce computational effort, we present two refinements: First, the even-parity integral method within the nodes reduces the computational effort required to form the response matrices. Second, the use of quasi-reflected interface conditions reduces the dimension of the resulting response matrices and therefore the CPU time required to solve the equations. We apply the method to the three-dimensional, un-rodded C5G7 benchmark problem. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Defect Engineering of Chalcogen-Tailored Oxygen Electrocatalysts for Rechargeable Quasi-Solid-State Zinc-Air Batteries

A critical bottleneck limiting the performance of rechargeable zinc-air batteries lies in the inefficient bifunctional electrocatalysts for the oxygen reduction and evolution reactions at the air electrodes. Hybridizing transition-metal oxides with functional graphene materials has shown great advantages due to their catalytic synergism. However, both the mediocre catalytic activity of metal oxides and the restricted 2D mass/charge transfer of graphene render these hybrid catalysts inefficient. Here, an effective strategy combining anion substitution, defect engineering, and the dopant effect to address the above two critical issues is shown. This strategy is demonstrated on a hybrid catalyst consisting of sulfur-deficient cobalt oxysulfide single crystals and nitrogen-doped graphene nanomeshes (CoO 0.87 S 0.13 /GN). The defect chemistries of both oxygen-vacancy-rich, nonstoichiometric cobalt oxysulfides and edge-nitrogen-rich graphene nanomeshes lead to a remarkable improvement in electrocatalytic performance, where CoO 0.87 S 0.13 /GN exhibits strongly comparable catalytic activity to and much better stability than the best-known benchmark noble-metal catalysts. In application to quasi-solid-state zinc-air batteries, CoO 0.87 S 0.13 /GN as a freestanding catalyst assembly benefits from both structural integrity and enhanced charge transfer to achieve efficient and very stable cycling operation over 300 cycles with a low discharge-charge voltage gap of 0.77 V at 20 mA cm(-2) under ambient conditions.

bifunctional electrocatalysts↗
DOE OSTI2019

Update on the Thermal Hydraulic Investigations of a Horizontal Dry Cask Simulator

The thermal performance of commercial spent nuclear fuel dry storage casks is evaluated through detailed numerical analysis. These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission (NRC). Canistered dry storage cask systems rely on ventilation between the inner canister and the overpack to convect heat away from the canister to the surrounding environment for both horizontal and vertical configurations. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a canister in part by increasing the efficiency of internal conduction pathways and by increasing the internal convection through greater canister helium pressure. Carefully measured data sets generated from testing of full-sized casks or smaller cask analogs are widely recognized as vital for validating these models. While several testing programs have been previously conducted, these earlier validation studies did not integrate all the physics or components important in a modern, horizontal dry cask system. The purpose of the present investigation is to produce data sets that can be used to benchmark the codes and best practices presently used to determine cladding temperatures and induced cooling air flows in modern horizontal dry storage systems. The horizontal dry cask simulator (HDCS) has been designed to generate this benchmark data and add to the existing knowledge base. The objective of the HDCS investigation is to capture the dominant physics of a commercial dry storage system in a well-characterized test apparatus for any given set of operational parameters. The close coupling between the thermal response of the canister system and the resulting induced cooling air flow rate is of particular importance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Team Dynamics and Development in Chemical Emergency Response

This presentation is focused on Team Dynamics and Development in Chemical Emergency Response. While regulatory requirements focus on defining the performance requirements associated with this category of response team, there is very little information and guidance provided to team leaders on the criticality of team dynamics of development in performance. These elements are essential to achieving successfully integrated team operations. NREL has worked to expand chemical response team participation to include operational personnel from research, support operations, and various technical areas. Since this team expansion has encompassed integration from numerous levels and areas within the organization, a systematic approach was adopted to better understand how organization culture, dynamics, and diversity can be used to be more effective. Benchmarking other organizations and reviewing relevant literature assisted in laying the foundation to develop a strategy that incorporates team development principles, dynamics, and leadership practices to increase the effectiveness of emergency response operations. This presentation focuses on the valuable lessons learned and the team-based approaches that can be used to develop a successful response team.

emergency response↗
DOE OSTI2021

Momentum distribution of the uniform electron gas at finite temperature: Effects of spin polarization

We carry out extensive direct path integral Monte Carlo (PIMC) simulations of the uniform electron gas (UEG) at finite temperature for different values of the spin-polarization ξ. This allows us to unambiguously quantify the impact of spin effects on the momentum distribution function n(k) and related properties. We find that interesting physical effects like the interaction-induced increase in the occupation of the zero-momentum state n(0) substantially depend on ξ. Our results further advance the current understanding of the UEG as a fundamental model system, and are of practical relevance for the description of transport properties of warm dense matter in an external magnetic field. All PIMC results are freely available online and can be used as a benchmark for the development of methods and applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Updated status of the ART neutronic fast reactor tools integration to the NEAMS Workbench

The Workbench initiative was launched in FY-2017 within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Integration Product Line to facilitate the transition from conventional tools to high-fidelity tools. The Workbench provides a common user interface for model creation, real-time validation, execution, output processing, and visualization for integrated codes. The integration of the Argonne Reactor Computation (ARC) suite of codes into the NEAMS Workbench was initiated in FY-2017. The ARC codes contain both legacy codes like DIF3D and REBUS-3 that were developed with over 30 years of experience, and newer NEAMS additions like MC 2 -3 and PERSENT. The ARC integration into the NEAMS Workbench interface relies on the PyARC module which handles the pre- and post-processing of the native ARC codes input, and the runtime environment. The PyARC module together with the NEAMS Workbench interface are both released under Open Source Software licenses. This report describes the ARC capabilities available with the Workbench at the end of FY-2018, and a tutorial is provided together with the automatically-generated code documentation. Integrating the ARC codes into the Workbench benefits directly the Advanced Reactor Technology (ART) Campaign by providing a set of controlled, maintained and validated scripts to generate ARC inputs, which promotes best practices, reduces the learning curve, and facilitates project collaboration. The second benefit from this project is to improve the user experience with the ARC codes: the Workbench interface provides assistance for building an input through auto-completion, real-time validation, access to templates, and visualization. Finally, the ARC integration into the NEAMS Workbench enables new modeling capabilities, those will be extremely useful for advanced reactor design and analyses. The PyARC module facilitates and automatizes complex calculations and workflows for reactor analysis enabling geometrical perturbations, cross-section update through depletion, etc. The Dakota/PyARC coupling in the Workbench was also demonstrated to enable mathematical optimization and sensitivity analysis/uncertainty quantification (SA/UQ) techniques with ARC neutronic simulations. For demonstration purposes, the ARC codes were used through the Workbench for solving the Sodium-cooled Fast Reactor Uncertainty Analysis in Modelling (SFR-UAM) benchmark problems. The ARC codes are currently used at ANL through the Workbench by nuclear engineers for SFR core design analyses. Future efforts will focus on continuously adding modeling capabilities available with the ARC codes, training new users to continue building some experience, and on integrating high-fidelity codes such as PROTEUS into the Workbench.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Supporting Building Portfolio Investment and Policy Decision Making through an Integrated Building Utility Data Platform

The American Recovery and Reinvestment Act stimulus funding of 2009 for smart grid projects resulted in the tripling of smart meters deployment. In 2012, the Green Button initiative provided utility customers with access to their real-time1 energy usage. The availability of finely granular data provides an enormous potential for energy data analytics and energy benchmarking. The sheer volume of time-series utility data from a large number of buildings also poses challenges in data collection, quality control, and database management for rigorous and meaningful analyses. In this paper, we will describe a building portfolio-level data analytics tool for operational optimization, business investment and policy assessment using 15-minute to monthly intervals utility data. The analytics tool is developed on top of the U.S. Department of Energy’s Standard Energy Efficiency Data (SEED) platform, an open source software application that manages energy performance data of large groups of buildings. To support the significantly large volume of granular interval data, we integrated a parallel time-series database to the existing relational database. The time-series database improves on the current utility data input, focusing on real-time data collection, storage, analytics and data quality control. The fully integrated data platform supports APIs for utility apps development by third party software developers. These apps will provide actionable intelligence for building owners and facilities managers. Unlike a commercial system, this platform is an open source platform funded by the U.S. Government, accessible to the public, researchers and other developers, to support initiatives in reducing building energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Comprehensive assessment of deep reinforcement learning approaches for economic dispatch in nuclear-driven microgrids

As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2004

Structural Benchmark Testing of Superalloy Lattice Block Subelements Completed

Superalloy lattice block panels, which are produced directly by investment casting, are composed of thin ligaments arranged in three-dimensional triangulated trusslike structures (see the preceding figure). Optionally, solid panel face sheets can be formed integrally during casting. In either form, lattice block panels can easily be produced with weights less than 25 percent of the mass of a solid panel. Inconel 718 (IN 718) and MarM-247 superalloy lattice block panels have been developed under NASA's Ultra-Efficient Engine Technology Project and Higher Operating Temperature Propulsion Components Project to take advantage of the superalloys' high strength and elevated temperature capability with the inherent light weight and high stiffness of the lattice architecture (ref. 1). These characteristics are important in the future development of turbine engine components. Casting quality and structural efficiency were evaluated experimentally using small beam specimens machined from the cast and heat treated 140- by 300- by 11-mm panels. The matrix of specimens included samples of each superalloy in both open-celled and single-face-sheet configurations, machined from longitudinal, transverse, and diagonal panel orientations. Thirty-five beam subelements were tested in Glenn's Life Prediction Branch's material test machine at room temperature and 650 C under both static (see the following photograph) and cyclic load conditions. Surprisingly, test results exceeded initial linear elastic analytical predictions. This was likely a result of the formation of plastic hinges and redundancies inherent in lattice block geometry, which was not considered in the finite element models. The value of a single face sheet was demonstrated by increased bending moment capacity, where the face sheet simultaneously increased the gross section modulus and braced the compression ligaments against early buckling as seen in open-cell specimens. Preexisting flaws in specimens were not a discriminator in flexural, shear, or stiffness measurements, again because of redundant load paths available in the lattice block structure. Early test results are available in references 2 and 3; more complete analyses are scheduled for publication in 2004.

Source record↗
DOE OSTI2022

[Presentation Slides] Code-to-Code Benchmark Study for Thermal Stress Modeling and Preliminary Analysis of the High-temperature Single Heat-Pipe Experiment

In the heat-pipe-cooled microreactor, heat pipes remove heat from the reactor core as a passive heat-transfer device, so the fluid circulation is not required for cooling, which can substantially simplify the overall reactor design. However, given the extremely high temperatures in the core region and potentially large temperature gradients across the structure materials, thermal stresses need to be well-analyzed to ensure structural integrity during normal operations and accident scenarios. This presentation slides discuss finite element method-based thermal-stress analysis for the high-temperature single heat-pipe test article in the Single Primary Heat Extraction and Removal Emulator (SPHERE) facility at Idaho National Laboratory (INL), using two commercial software packages, Abaqus and Star-CCM+. A code-to-code benchmark study was performed to crosscheck the model setup and capability of each code and to gain preliminary insights into the potential thermal stress concerns from the current experimental setup. It is observed the significant thermal stresses happen at the inner surface of the heat pipe hole surrounded by electric heaters where the largest temperature gradients appear. The temperature fields have good agreements between Abaqus and Star-CCM+, while the induced thermal stresses show modest deviations probably due to differences of meshing engines used in these two codes. It is found that the local maximum thermal stresses may reach close to the ultimate tensile strength and yield strength of structural material depending on the heater power. Ultimately, the coupled thermal-structural analysis will help guide the current experimental plan and ensure the facility safety for future experimental study.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Crystalline materials for quantum computing: Semiconductor heterostructures and topological insulators exemplars

Abstract High-purity crystalline solid-state materials play an essential role in various technologies for quantum information processing, from qubits based on spins to topological states. New and improved crystalline materials emerge each year and continue to drive new results in experimental quantum science. This article summarizes the opportunities for a selected class of crystalline materials for qubit technologies based on spins and topological states and the challenges associated with their fabrication. We start by describing semiconductor heterostructures for spin qubits in gate-defined quantum dots and benchmark GaAs, Si, and Ge, the three platforms that demonstrated two-qubit logic. We then examine novel topologically nontrivial materials and structures that might be incorporated into superconducting devices to create topological qubits. We review topological insulator thin films and move onto topological crystalline materials, such as PbSnTe, and its integration with Josephson junctions. We discuss advances in novel and specialized fabrication and characterization techniques to enable these. We conclude by identifying the most promising directions where advances in these material systems will enable progress in qubit technology.

Scappucci, G. (ORCID:0000000325120079)↗
DOE OSTI2020

ddcMD: A fully GPU-accelerated molecular dynamics program for the Martini force field

We have implemented the Martini force field within Lawrence Livermore National Laboratory’s molecular dynamics program, ddcMD. The program is extended to a heterogeneous programming model so that it can exploit graphics processing unit (GPU) accelerators. In addition to the Martini force field being ported to the GPU, the entire integration step, including thermostat, barostat, and constraint solver, is ported as well, which speeds up the simulations to 278-fold using one GPU vs one central processing unit (CPU) core. A benchmark study is performed with several test cases, comparing ddcMD and GROMACS Martini simulations. The average performance of ddcMD for a protein–lipid simulation system of 136k particles achieves 1.04 µs/day on one NVIDIA V100 GPU and aggregates 6.19 µs/day on one Summit node with six GPUs. The GPU implementation in ddcMD offloads all computations to the GPU and only requires one CPU core per simulation to manage the inputs and outputs, freeing up remaining CPU resources on the compute node for alternative tasks often required in complex simulation campaigns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Superconducting qubits in a flip-chip architecture

Flip-chip architectures have recently enabled significant scaling-up of multi-qubit circuits and have been used to assemble hybrid quantum systems that combine different substrates, for example, for quantum acoustics experiments. The standard flip-chip method uses superconducting galvanic connections between two substrates, typically implemented using sophisticated indium wafer-bonding systems, which give highly reliable and temperature-cyclable assemblies, but are expensive, somewhat inflexible in design, and require robust substrates that can sustain the large compressive forces required to cold-weld the indium bonds. A much simpler method is to assemble dies using very low-force contacts and air-dried adhesives, although this does not provide a galvanic contact between the dies. In this work, we demonstrate that the latter technique can be used to reliably couple superconducting qubit circuits, in which the qubits are on separate dies, without the need for a galvanic connection. We demonstrate full vector qubit control of each qubit on each of the two dies, with high-fidelity single-shot readout, and further demonstrate entanglement-generating excitation swaps as well as benchmark a controlled-Z entangling gate between the two qubits on the two dies. This exemplifies a simple and inexpensive assembly method for two-plus-one-dimensional quantum circuit integration that supports the use of delicate or unusually shaped substrates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Assessing the Role of Hydrodynamics in Enhancing Height-Above-the-Nearest-Drainage Derived Synthetic Rating Curves: A Comparative Study in the Wu River Basin, Taiwan

The conventional approach to generating synthetic rating curves (SRC) using the Height-Above-the-Nearest-Drainage (HAND) method typically relies on the assumption of uniform flow, such as Manning's equation, to establish stage-discharge ratings. The zero-physics application of the uniform flow equation is insufficient for capturing detailed hydraulic features (e.g., backwater effect) and neglects the hydraulic effects from adjacent channels. This lack of hydrodynamic computation can impact the accuracy and effectiveness of riverine flood risk estimation and management. To reduce this foreseeable error, we introduce the HAND-hd workflow, which integrates sophisticated hydrodynamic computations in the production of HAND-based SRC with hydrodynamic features (SRC hd ). The results indicate that SRC hd demonstrates consistent agreement with both gauge observations and benchmark solutions. Additionally, the comparative analysis suggests that SRC hd provides notable improvements in stage-discharge ratings over conventional HAND-based SRCs, particularly in channels with mild bed gradients, where it reduces water stage prediction errors and percent biases. In steeper channel segments, SRC hd maintains comparable accuracy to conventional methods. The comprehensive evaluation in this study emphasizes the potential discrepancies and inaccuracies associated with the adoption of the uniform flow assumption in the conventional HAND-SRCs and addresses the necessity of including hydrodynamic physics in the application of HAND-based SRC (e.g., inundation map) in channels with mild gradients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes

A promising approach for scalable Gaussian processes (GPs) is the Karhunen-Loève (KL) decomposition, in which the GP kernel is represented by a set of basis functions which are the eigenfunctions of the kernel operator. Such decomposed kernels have the potential to be very fast, and do not depend on the selection of a reduced set of inducing points. However KL decompositions lead to high dimensionality, and variable selection thus becomes paramount. This paper reports a new method of forward variable selection, enabled by the ordered nature of the basis functions in the KL expansion of the Bayesian Smoothing Spline ANOVA kernel (BSS-ANOVA), coupled with fast Gibbs sampling in a fully Bayesian approach. It quickly and effectively limits the number of terms, yielding a method with competitive accuracies, training and inference times for tabular datasets of low feature set dimensionality. Theoretical computational complexities are O ( N P 2 ) in training and O ( P ) per point in inference, where N is the number of instances and P the number of expansion terms. The inference speed and accuracy makes the method especially useful for dynamic systems identification, by modeling the dynamics in the tangent space as a static problem, then integrating the learned dynamics using a high-order scheme. The methods are demonstrated on two dynamic datasets: a ‘Susceptible, Infected, Recovered’ (SIR) toy problem, along with the experimental ‘Cascaded Tanks’ benchmark dataset. Comparisons on the static prediction of time derivatives are made with a random forest (RF), a residual neural network (ResNet), and the Orthogonal Additive Kernel (OAK) inducing points scalable GP, while for the timeseries prediction comparisons are made with LSTM and GRU recurrent neural networks (RNNs) along with the SINDy package.

Hayes, Kyle↗
DOE OSTI2015

BWR Spent Nuclear Fuel Interfacial Bonding Efficiency Study

The objective of this project is to perform a systematic study of spent nuclear fuel (SNF, also known as “used nuclear fuel” [UNF]) integrity under simulated transportation environments using the Cyclic Integrated Reversible-Bending Fatigue Tester (CIRFT) hot-cell testing technology developed at Oak Ridge National Laboratory (ORNL) in August 2013. Under Nuclear Regulatory Commission (NRC) sponsorship, ORNL completed four benchmark tests, four static tests, and twelve dynamic or cycle tests on H. B. Robinson (HBR) high burn-up (HBU) fuel. The clad of the HBR fuels was made of Zircaloy-4. Testing was continued in fiscal year (FY) 2014 using Department of Energy (DOE) funds. Additional CIRFT testing was conducted on three HBR rods; two specimens failed, and one specimen was tested to over 2.23 × 10 7 cycles without failing. The data analysis on all the HBR SNF rods demonstrated that it is necessary to characterize the fatigue life of the SNF rods in terms of (1) the curvature amplitude and (2) the maximum absolute of curvature extremes. The maximum extremes are significant because they signify the maximum tensile stress for the outer fiber of the bending rod. CIRFT testing has also addressed a large variation in hydrogen content on the HBR rods. While the load amplitude is the dominant factor that controls the fatigue life of bending rods, the hydrogen content also has an important effect on the lifetime attained at each load range tested. In FY 15, eleven SNF rod segments from the Limerick BWR were tested using the ORNL CIRFT equipment; one test under static conditions and ten tests under dynamic loading conditions. Under static unidirectional loading, a moment of 85 N·m was obtained at a maximum curvature of 4.0 m -1 . The specimen did not show any sign of failure during three repeated loading cycles to a similar maximum curvature. Ten cyclic tests were conducted with amplitudes varying from 15.2 to 7.1 N·m. Failure was observed in nine of the tested rod specimens. The cycles-to-failure ranged from 1.22 × 10 5 to 4.70 × 10 6 , and the amplitudes varied from 15.2 to 7.6 N·m. The measurements at the interrupts indicated a range of flexural rigidity from 30 to 50 N·m 2 . Online monitoring revealed that the flexural rigidity was slightly lower due to the higher loading, from 25 to 42 N·m 2 . Generally, no substantial change of rigidity was observed based on the online monitoring during the cyclic fatigue testing process. Overall, the decreasing trend of sample lifetime with increasing amplitude is well defined.

interface bonding efficiency↗