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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effect of Fatigue on the Capacity and Performance of Structural Concrete

The goal of this project was to enhance the understanding of the fatigue behavior of concrete structures for the purpose of improving the design and assessment of towers and foundations that support wind turbines, which must endure repeated loadings from wind, waves, operations, and other dynamic effects that cause material degradation. This was achieved through physical experiments, a review of the technical literature, and collaboration with experts in key subject areas. The project produced a comprehensive database of publicly available fatigue data, several technical papers presenting the research findings, and two Technotes to be published by the American Concrete Institute that advance best practices in fatigue testing and enable the development of concrete-specific fatigue (S-N) (stress-life) curves. These contributions are expected to enhance the durability and cost-effectiveness of wind turbine support structures.

17 WIND ENERGY↗
DOE OSTI2022

Transient Phase-Driven Cyclic Deformation in Additively Manufactured 15-5 PH Steel

The present work extends the examination of selective laser melting (SLM)-fabricated 15-5 PH steel with the 8%-transient-austenite-phase towards fully-reversed strain-controlled low-cycle fatigue (LCF) test. The cyclic-deformation response and microstructural evolution were investigated via in-situ neutron-diffraction measurements. The transient-austenite-phase rapidly transformed into the martensite phase in the initial cyclic-hardening stage, followed by an almost complete martensitic transformation in the cyclic-softening and steady stage. The compressive stress was much greater than the tensile stress at the same strain amplitude. The enhanced martensitic transformation associated with lower dislocation densities under compression predominantly governed such a striking tension-compression asymmetry in the SLM-built 15-5 PH.

15-5 PH stainless steel↗
DOE OSTI2020

Compact Diffusion Bonded Heat Exchanger Fatigue Life Simulations (Final Report)

Compact diffusion bonded heat exchangers are essential for high pressure heat exchange, but they are subject to thermal fatigue and ramp rate limitations. Simulation of these geometries is challenging with a large range of length and time scales from thousands of mm-sized microchannels inside a m-sized heat exchanger. Multi-physics simulations including thermal, fluid, and solid mechanics components are being used to predict stress within the heat exchangers under these conditions. These predictions can then be used to understand thermal ramp rate limitations while keeping maximum stresses low as well as fatigue life predictions from well-known empirical models.

42 ENGINEERING↗
DOE OSTI2022

A System-Level Model for Estimating Residual Strain and Life of Nuclear Reactor Coolant System Components Under Connected-System-Thermal–Mechanical Boundary Conditions

Background: Environmental-assisted fatigue (EAF) is a major issue for the long-term survival of nuclear power plant fleets in the U.S. and worldwide. Multi-material welded regions (e.g., nozzles) and other high-stress regions of reactor coolant system (RCS) components are prone to EAF-related damage. Objective: The discussed work describes a system-level finite element (FE) model of RCS components of a pressurized water reactor (PWR). This is with the goal of predicting the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Methods: Herein, the FE model was developed considering system-level loading conditions (under connected system thermal-mechanical boundary conditions). Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the FE model results, the strain residuals, strain amplitudes and resulting fatigue lives of RCS components were predicted. Results: The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. Higher residual strain can lead to accelerated cyclic hardening of material and the associated effect of EAF. The simulated component-level strain profile (under realistic multi-axial-multi-physics loading cycle) can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests, which is a focus of future works. Conclusions: Despite similar geometry and material the RCS component can have significantly different strain profiles and resulting fatigue lives. The discussed approach can help to identify and prioritize the RCS components for conducting expensive nondestructive evaluation (NDE) inspections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

High Power Solid Target for Positron Source at CEBAF

The progress in the development of a polarized positron injector for the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is presented. The polarized positron beam is generated by a high current polarized electron beam (>1 mA @ 120 MeV) via bremsstrahlung radiation and e+e- pair production in the tungsten target. The simulations show that using an optimized target and positron beamline, the positron injector can provide a cw positron beam with a current larger than 50 nA and a polarization as large as 60%. Injected into the North Linac of CEBAF at an energy of 123 MeV, the positron beam can reach a maximum energy of 12 GeV to perform a rich experimental program. The results of the thermal and structural FEA analysis of the heat load in the target are presented, as well as the simulation results of radiation damage in the target. The performed and planned target material fatigue and radiation damage tests are discussed. This work is supported by the U.S. DOE, Office of Science, Office of Nuclear Physics, Contract No. DE-AC05-06OR23177 and the European Union?s Horizon 2020 research and innovation program under grant agreement No. 824093.

Ushakov, Andriy↗
DOE OSTI2021

Strong tough hydrogels via the synergy of freeze-casting and salting out

Natural load-bearing materials like tendons possess high water content of ~70% but14 are still strong and tough even when used for over 1 million cycles per year, which is owed to the hierarchical assembly of anisotropic structures across multi-length-scales . In imitation of natural systems, various hydrogels have been created via methods like electro-spinning, extrusion, compositing, freeze casting, self-assembly, and mechanical stretching for improved mechanical performance. However, in contrast to tendons, many hydrogels with the same high water content do not show high strength, large toughness or high fatigue resistance. In this work, we present a strategy to produce strong, tough and fatigue resistant hydrogels with multi-length-scale hierarchical architecture using a freezing-assisted salting-out treatment. The produced exemplary poly(vinyl alcohol) hydrogels are highly anisotropic, comprising micrometer-scale honeycomb-like pore walls, which in turn comprise interconnected nanofibrils meshes, entirely physically assembled from polymer chains. These hydrogels are made of 70-95% water but can exhibit ultra-high ultimate stress (23.5 ± 2.7 MPa) and strain (2900 ± 450%), giant 32226 toughness (210 ± 13 MJ/m , 175 ± 8 kJ/m) and remarkable fatigue threshold (10.5 ± 1.3 kJ/m), which are 10 times tougher than natural tendon. The presented strategy could expand the applicability of weak polymeric material, like hydrogels, in practical applications that requires long-term services with high-loads and abrupt-impacts and extend the development of structural hydrogels.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A digital twin solution for floating offshore wind turbines validated using a full-scale prototype

Abstract. In this work, we implement, verify, and validate a physics-based digital twin solution applied to a floating offshore wind turbine. The digital twin is validated using measurement data from the full-scale TetraSpar prototype. We focus on the estimation of the aerodynamic loads, wind speed, and section loads along the tower, with the aim of estimating the fatigue lifetime of the tower. Our digital twin solution integrates (1) a Kalman filter to estimate the structural states based on a linear model of the structure and measurements from the turbine, (2) an aerodynamic estimator, and (3) a physics-based virtual sensing procedure to obtain the loads along the tower. The digital twin relies on a set of measurements that are expected to be available on any existing wind turbine (power, pitch, rotor speed, and tower acceleration) and motion sensors that are likely to be standard measurements for a floating platform (inclinometers and GPS sensors). We explore two different pathways to obtain physics-based models: a suite of dedicated Python tools implemented as part of this work and the OpenFAST linearization feature. In our final version of the digital twin, we use components from both approaches. We perform different numerical experiments to verify the individual models of the digital twin. In this simulation realm, we obtain estimated damage equivalent loads of the tower fore–aft bending moment with an accuracy of approximately 5 % to 10 %. When comparing the digital twin estimations with the measurements from the TetraSpar prototype, the errors increased to 10 %–15 % on average. Overall, the accuracy of the results is promising and demonstrates the possibility of using digital twin solutions to estimate fatigue loads on floating offshore wind turbines. A natural continuation of this work would be to implement the monitoring and diagnostics aspect of the digital twin to inform operation and maintenance decisions. The digital twin solution is provided with examples as part of an open-source repository.

17 WIND ENERGY↗
DOE OSTI2020

Fatigue-Crack Detection and Monitoring through the Scattered-Wave Two-Dimensional Cross-Correlation Imaging Method Using Piezoelectric Transducers

Piezoelectric transducers are convenient enablers for generating and receiving Lamb waves for damage detection. Fatigue cracks are one of the most common causes for the failure of metallic structures. Increasing emphasis on the integrity of critical structures creates an urgent need to monitor structures and to detect cracks at an early stage to prevent catastrophic failures. This paper presents a two-dimensional (2D) cross-correlation imaging technique that can not only detect a fatigue crack but can also precisely image the fatigue cracks in metallic structures. The imaging method was based on the cross-correlation algorithm that uses incident waves and the crack-scattered waves of all directions to generate the crack image. Fatigue testing for crack generation was then conducted in both an aluminum plate and a stainless-steel plate. Piezoelectric wafer transducer was used to actuate the interrogating Lamb wave. To obtain the scattered waves as well as the incident waves, a scanning laser Doppler vibrometer was adopted for acquiring time-space multidimensional wavefield, followed with frequency-wavenumber processing. The proof-of-concept study was conducted in an aluminum plate with a hairline fatigue crack. A frequency-wavenumber filtering method was used to obtain the incident wave and the scattered wave wavefields for the cross-correlation imaging. After this, the imaging method was applied to evaluate cracks on a stainless-steel plate generated during fatigue loading tests. The presented imaging method showed successful inspection and quantification results of the crack and its growth.

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

wtDigiTwin (Wind Turbine Digital Twin) [SWR-21-15]

This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.

Branlard, Emmanuel↗
DOE OSTI2024

High-Power Targetry R&D for Next-Generation Accelerator Target Facilities

Beam-intercepting devices such as beam windows and particle-production targets are critical components of accelerator target facilities for High Energy Physics (HEP) experiments. The high-power, pulsed structure of the particle beams used for these experiments leads to thermal shock and high-cycle fatigue in addition to radiation damage resulting from the accumulated particle fluence. This can lead to degradation of the target system s mechanical and thermal properties; considerably reducing their lifetimes and presenting substantial challenges to reliable operation of multi-MW class facilities. Recently several major accelerator facilities have been forced to operate at reduced power levels due to target survivability concerns. Furthermore, at Fermilab it is planned to increase the neutrino production beam power up to 2.4 MW in coming years. Therefore, timely R&D on the irradiated behavior of target system materials is critical to efficient operation of accelerator facilities and full utilization of recent accelerator power upgrades for HEP research. This talk will begin with an overview of high-power targetry, and the significant challenges presented by beam power increases expected for future HEP experiments. We will then cover several past materials irradiation studies that have been completed by the High-Power Targetry R&D group at Fermilab and its collaborators on common accelerator and target materials such as graphite, beryllium, titanium, and tungsten. Finally, we will conclude with a discussion of two novel materials investigations under way within the group; high-entropy alloys for beam window applications, and electrospun nanofibers to serve as particle production targets.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Micropolar deep material network

This study extends the Deep Material Network (DMN), a physics-informed machine learning framework, to predict the homogenized mechanical response of composite materials with micropolar (Cosserat-type) constitutive behavior. This extension incorporates microstructure-dependent size effects, enabling accurate, efficient, and size-aware predictions for composites with complex internal architectures. While traditional, direct numerical simulation micropolar models effectively capture size effects by introducing extra local degrees of freedom, they bring significant computational challenges, particularly for multiscale analyses relevant to engineering applications. The micropolar DMN developed in this paper achieves high accuracy while significantly reducing computation time compared to micropolar direct numerical simulations. This advancement enables multiscale analyses and parameter studies that were previously impractical, such as high-cycle fatigue simulations and comprehensive investigations of internal length scale effects notably in size-dependent plastic response and the optimization of lattice structures. By uniting microstructure-sensitive modeling, physics-driven learning, and scalable surrogate modeling, the micropolar DMN paves the way for accelerated material design, large-scale parametric studies, and the reliable incorporation of size-dependent effects across a wide range of engineering applications, including optimization and next-generation composite design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Challenges and Optimization of Mu2e Proton Target Design with Radiative Cooling

Mu2e, the Muon-to-Electron Conversion Experiment, aims to identify physics beyond the Standard Model, namely, the conversion of muons to electrons without the emission of neutrinos. The muons are produced from pions generated in a production target when it is hit by an 8 GeV proton beam from the Fermilab Booster/Main Injector. The proton target design space is strongly constrained by a one-year operating lifetime and the need for radiative cooling in a vacuum environment. Uncertainties in the lifetime of the existing baseline design – a monolithic, segmented tungsten target – are large, particularly due to unknown impacts of radiation damage at the very high proton fluences expected in the experiment. We have begun evaluation of a new design utilizing Inconel 718 over the WL10 used in the existing target design. As a result, the structural design of the target has evolved significantly. This evolution focuses on lowering the target temperature, minimizing obstruction to muons, increasing structural stability, maximizing fatigue lifetime, simplifying the fabrication process, and more. The thermal management, structural stability and fatigue lifetime are emphasized here. These optimizations have led to a promising new target design for the Mu2e experiment.

Liu, Z. [Fermilab]↗
DOE OSTI2023

Physics-informed Data-driven Degradation and Prognostic For Hydropower System

The hydropower system is a cyber-physical system, and the industry is experiencing high operation and maintenance (O&M) costs along with increasing unplanned outages, primarily due to aging equipment and new asset loading patterns. Current (O&M) practices in asset management are predominantly reactive rather than predictive and systematic. To address these challenges, a proposed physics-informed data-driven degradation model aims to simulate the health of components in various environments. Its purpose is to accurately characterize wear and fatigue in the pilot components of hydropower systems. Additionally, the model provides informed confidence in prognostic predictions concerning asset degradation and remaining life.

13 HYDRO ENERGY↗
DOE OSTI2022

Load Mitigating Feedback Control of WECs

This report outlines the development of load-mitigating feedback control for wave energy converters. A simple, self-tuning multi-objective controller is demonstrated in simulation for a 3-DOF (surge, heave, pitch) point absorber. In previous work, the proposed control architecture has been shown to be effective in experiment for a variety of device archetypes for the single objective of the maximization of electrical power capture: here this architecture is extended to reduce device loading as well. In particular, PTO actuation forces and the minimization of fatigue damage (determined from the sum of wave-exerted and PTO forces) are considered as additional objectives for the self-tuning controller. This controller is demonstrated for two similar, but distinct systems: one described by the identified linear models from physical testing of the WaveBot device, and another based upon a WEC-Sim simulation that expands upon boundary element method data from the WaveBot device. In both cases, because the power surface is consistently fairly flat in the vicinity of control parameters that maximize power capture in contrasting sea-states, it is found to be generally possible to mitigate either fatigue damage or PTO load. However, PTO load is found to conflict with fatigue damage in some sea-states, limiting the efficacy of control objectives that attempt to mitigate both simultaneously. Additionally, coupling between the surge and pitch DOFs also limits the extent to which fatigue damage can be mitigated for both DOFs in some sea-states. Because control objectives can be considered a function of the sea-state (e.g., load mitigation may not be a concern until the sea is sufficiently large) a simple transition strategy is proposed and demonstrated. This transition strategy is found to be effective with some caveats: firstly, it cannot circumvent the aforementioned objective contradictions. Secondly, this objective transition is too slow to act as a system constraint, and objective thresholds must thus be considered quite conservatively. Improvement of the adjustment strategy is demonstrated through the addition of an integral term. Selection of well-performing transition parameters can be a function of sea-state. While a simple selection procedure is proposed, it is non-optimal, and a more robust selection procedure is suggested for future work.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Highly accelerated life testing (HALT): A review from a statistical perspective

Despite its use in one form or another for at least four decades, HALT and related techniques [e.g., highly accelerated-stress screening (HASS) and stress audits (HASA)] are not well understood within the statistical community and remain controversial. This largely reflects a conflict in motivation between engineers, testing under harsh conditions to discover and eliminate failure modes, and statisticians, taking a more cautious approach to develop quantitative estimates of parameters such as mean time between failures (MTBF). Here, this review article will clarify HALT concepts and methods and explain where it fits within the universe of methods that involve the application of accelerating factors to compress the time required to evaluate or enhance product reliability. A major distinction is between methods such as HALT, a high-stress test-analyze-fix-test iterative process directed at improving reliability by discovering and fixing weak points in a design, and quantitative accelerated life testing (QALT), whose goal is the estimation of product life for a fixed design. We discuss methods such as physics of failure that offer some hope of bridging the gap between the qualitative nature of HALT, and purely quantitative statistical methods. We present a variety of engineering applications of HALT including metal fatigue, piping and pressure vessels, structural damage, radiation damage, and rotating machinery. We also discuss potential synergies between HALT and QALT, such as rapid identification, through HALT, of failure modes requiring quantitative analysis. For further study, extensive references to the applicable literature are provided as well as an appendix that describes related methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Microstructural, Corrosion and Mechanical Characterization of Friction-Stir Welded Joints Between Aluminum and Magnesium Alloys

Friction Stir Welding (FSW) of Aluminum-Magnesium (Al-Mg) alloys has garnered increasing attention due to its wide-ranging applications in the automotive and aerospace industries. The microstructural, corrosion, and mechanical properties of FSW Al-Mg welds under selected conditions are critical factors that must be well-investigated to ensure their durability and performance. In this study, electrochemical tests, including Open Circuit Potential (OCP), Linear Polarization Resistance (LPR), Potentiodynamic Polarization Scan (PD), and Electrochemical Impedance Spectroscopy (EIS), have been used to analyze the corrosion resistance of these welds, along with weight loss measurements through cyclic corrosion testing (CCT) and surface evolution via SEM over an 8-week period. Mechanical properties are evaluated through microindentation, nanoindentation, fatigue, and lap-shear tests. The results of the electrochemical tests reveal that the corrosion properties of the center weld zone differ from those of the two base alloys. Indentation tests indicate that the weld zone behaves differently from the base alloys. Surprisingly, the lap shear strength did not decrease significantly even after 8 weeks of cyclic corrosion testing, indicating that the joint prevented any ingress of the electrolyte. Fatigue testing showed that applying an adhesive between the Al and Mg joint improved the fatigue life to some extent, although the corrosion resistance reduced due to the discontinuous bonding of the adhesive layer. Overall, these findings highlight the importance of investigating the corrosion and mechanical properties of FSW Al-Mg welds and provide valuable insights for future modeling works.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗
DOE OSTI2026

Validation Data for Benchmarking Wire Arc Additive Manufacturing Process Simulations

Residual stresses cause geometric distortion and affect mechanical performance of additively manufactured structures, yet they are notoriously difficult to assess and predict. Distortion (warpage) can drive parts outside dimensional tolerance limits, leading to part rejection or rework. For parts that meet tolerance, locked-in residual stress fields can affect structural integrity during operation, particularly subcritical cracking by fatigue, creep, or corrosion. This work develops benchmark data for a common additive manufacturing process (Wire Arc Additive Manufacturing) that can be applied for calibration and validation of physical process models that predict residual stress fields. The work includes design of two different samples of differing geometry, detailed manufacturing records for a set of physical samples, and an extensive set of residual stress measurement data developed using two diverse techniques (the contour method and neutron diffraction). An initial application of the work is also reported, where a modeling challenge was issued to secure residual stress model predictions from two independent laboratories that were blind to residual stress measurement data. These initial blind residual stress predictions show significant discrepancies relative to the measurement data, illustrating the potential value of the underlying validation data. An open repository for this work, including the sample designs, manufacturing process records, and the residual stress data, is also provided for future application in non-blind validation efforts.

36 MATERIALS SCIENCE↗