Electric field-assisted embedding of fiber optic sensors in structural materials for structural health monitoring
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The myriad detectors and instruments now available for materials characterization provide researchers with an ever-growing suite of tools to probe material behavior. Progress in the development of instrumentation and workflows that enable the collection, and leverage the potential, of various data modalities have provided novel insights into material behavior. Using data across multiple length scales, or performing complementary analyses of in situ and ex situ data, can help reveal a more complete picture of dynamic processes or material structure. However, the accurate combination, or fusion, of these disparate data modalities presents new challenges. Differences in resolution, as well as the varying length scales at which physical phenomena are exploited to generate these data, necessitate novel approaches to accurately interpret and combine these data. Furthermore, the papers within this special topic focus on the collection and fusion of multimodal data to better understand structural materials. From new frameworks and workflows for data segmentation and analysis, process monitoring, enhancing simulations, or interrogating mechanical response, these papers reveal the potential benefits of utilizing multimodal data.
Lightweight structural materials are required to increase the mobility of fission batteries. The materials must feature a robust combination of mechanical properties to demonstrate structural resilience. The primary objective of this project is to produce lightweight structural materials whose strength-to-weight ratios exceed those of the current widely used structural materials such as 316L stainless steels (316L SS). To achieve this, advanced modeling and simulation tools were employed to design lattice structures with different lattice parameters and different lattice types. A process was successfully developed for transforming lattice-structures models into Multiphysics Object Oriented Simulation Environment (MOOSE) inputs. Finite element modeling (FEM) was used to simulate the uniaxial tensile testing of the lattice-structured parts to investigate the stress distribution at a given displacement. The preliminary results showed that the lattice-structured sample displayed a lower Young’s modulus in comparison with the solid material and that the unit cell size of the lattice had a minimal effect. The novelty here is to apply up-front modeling to determine the best structure for the application before actually producing the sample. The approach of using modeling as a guiding tool for preliminary material design can significantly save time and cost for material development.
Soft structural textiles, or softgoods, are used within the space industry for inflatable habitats, parachutes and decelerator systems. Evaluating the safety and structural integrity of these systems occurs through structural health monitoring systems (SHM), which integrate non-invasive/non-destructive testing methods to detect, diagnose, and locate damage. Strain/load monitoring of these systems is limited while utilizing traditional strain gauges as these gauges are typically stiff, operate at low temperatures, and fail when subjected to high strain that is a result of high loading classifying them as unsuitable for SHM of soft structural textiles. For this work, a capacitance based strain gauge (CSG) was fabricated via aerosol jet printing (AJP) using silver nanoparticle ink on a flexible polymer substrate. Printed strain gauges were then compared to a commercially available high elongation resistance-based strain gauge (HE-RSG) for their ability to monitor strained Kevlar straps having a 26.7?kN (6?klbf) load. Dynamic, static and cyclic loads were used to characterize both types of strain monitoring devices. Printed CSGs demonstrated superior performance for high elongation strain measurements when compared to commonly used HE-RSGs, and were observed to operate with a gauge factor of 5.2 when the electrode arrangement was perpendicular to the direction of strain.
The development of lightweight structural materials is crucial for enhancing the performance and deployment feasibility of fission batteries. This study aims to produce lightweight structural materials whose strength-to-weight ratios exceed those of current widely used structural materials. To achieve this, advanced modeling and simulation tools were employed to design lattice structures with different lattice parameters and different lattice types. A process was successfully developed for transforming lattice-structured models into Multiphysics Object Oriented Simulation Environment (MOOSE) inputs. Finite element modeling (FEM) was used to simulate the uniaxial tensile testing of the lattice-structured parts to investigate the stress distribution at a given displacement. The modeling results showed that the lattice-structured sample displayed a lower Young’s modulus in comparison to the solid material; the increase in solid shell thickness and blend radius enhances the mechanical performance; and the effect of unit cell size on macro scale stress is minimal. Tensile testing was conducted on the solid and lattice-structured materials fabricated by laser powder bed fusion (LPBF) additive manufacturing. The experimental results agreed well with the model prediction. The approach of using modeling as a guiding tool for preliminary material design can significantly save time and cost for new material development.
Resonant meta-material structures are defined by metallic, dielectric or other materials that form nanoshells or nanomeshes that can be situated proximate to ionizing-radiation-sensitive layers so as to provide ionizing-radiation-dose-dependent optical properties. Such meta-material structures can also define aligned or periodic, semi-random, or other arrangements of nanostructures that are coupled to or include stressed layers. Detection of optical radiation from such structures is used to determine gamma radiation dose or to detect a disturbance of the nanostructure indicating tampering.
Fission batteries require lightweight structural materials that demonstrate structural resilience when subjected to repeated shutdown, transportation, startup cycles, and certain external conditions, including rare events such as seismic vibrations and tsunamis. The objectives of this project are (1) to produce lightweight structural materials whose strength-to-weight ratios and fatigue resistance exceed those of current widely used structural materials such as 316 stainless steels (SS316), and (2) to enhance radiation tolerance of structural materials over a suitable service temperature range. To achieve these, (1) a lattice structure will be produced, (2) advanced modeling and simulation tools will be employed to design lattice structures (e.g., a gyroid structure) that reduce stress concentrations and thus increase fatigue resistance, and (3) one-dimensional (1-D) carbon nanotubes will be added to enhance radiation resistance. To validate our solution, high-temperature tensile and fatigue testing, in combination with microstructure characterization, will be conducted on wrought materials, additively manufactured solid materials, and the designed lightweight lattice structure material. Ion irradiation, microstructure characterization, and nanoindentation will be carried out to investigate the effect of 1-D carbon nanotubes on radiation tolerance. Successful completion of this project will deliver a material to serve as a substitute for current SS316 using the same chemistry but with lighter weight and improved mechanical properties. In addition, a material with carbon nanotubes can be designed for improved radiation tolerance over a suitable service temperature range. This project will establish new techniques in innovative materials/lattice design, advanced macroscale properties prediction, and the application of state-of-the-art processes.
Abstract Civilian fusion demands structural materials that can withstand the harsh environments imposed inside fusion plasma reactors. The structural materials often transmute under 14.1 MeV fast neutrons, producing helium (He), which embrittles the grain boundary (GB) network. Here, it is shown that neutron‐friendly and mechanically strong nano‐phases with atomic‐scale free volume can have low He‐embedding energy and >10 at.% He‐absorbing capacity, and can be especially advantageous for soaking up He on top of resisting radiation damage and creep, provided they have thermodynamic compatibility with the matrix phase, satisfactory equilibrium wetting angle, as well as a high enough melting point. The preliminary experimental demonstration proves that is a good ab initio predictor of He shielding potency in nano‐heterophase materials, and thus, is used as a key feature for computational screening. In this context, a list of viable compounds expected to be good He‐absorbing nano‐phases is presented, taking into account , the neutron absorption and activation cross‐sections, the elastic moduli, melting temperature, the thermodynamic compatibility, and the equilbrium wetting angle of the nano‐phases with the Fe matrix as an example.
Understanding structural properties of materials and how they relate to its atomic structure, while extremely challenging, is a key scientific quest that has dominated the landscape of materials research for decades. Neutron and X-ray scattering is a state-of-the-art method to investigate material structure on the atomic scale. Traditional methods of processing neutron scattering data to decipher the structure of target materials have relied on computing scattering patterns using physics-based forward models and comparing them with experimentally gathered scattering profiles within a computationally expensive optimization loop. Here, we report an initial design of a data-driven machine learning pipeline for material structure prediction that is computationally faster (once trained) and potentially more accurate. We describe the architecture of the ML pipeline and a preliminary benchmarking study of shallow machine learning models in terms of their prediction accuracy and limitations. We show that material structure prediction from neutron scattering data using shallow learning models is feasible to within 90% prediction accuracy for certain classes of materials but deeper models are required for more general material structure predictions.
This report summarizes work performed during Fiscal Year (FY) 2020 at Idaho National Laboratory (INL) for the U.S. Department of Energy?s Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program for the Structural Materials and Chemistry Technical Area in the work package entitled "MS- 20IN050104 - Structural Materials - INL." The Structural Materials and Chemistry Technical Area is a relatively new component of the NEAMS program, and is currently focusing on developing simulation capabilities to support the deployment of nuclear energy in the areas of molten salt reactor chemistry, light water reactor (LWR) structural material degradation, and structural material behavior for advanced reactor applications. INL performed work for to advance capabilities for simulation of structural material behavior in both LWR and advanced reactor applications in the work described here.
Structural Materials Characterization Test Rig Development Project Summary
Design, fabrication, and usage of a reactor are presented for synthesis of structured materials from a liquid-phase precursor by heating. The structured materials are particles, membranes or films of micro-porous molecular sieve crystals such as zeolite and meso-porous materials. The precursor solution and structured materials in the reactor are uniformly heated by a planar heater with characteristic heat transfer dimension in the range of 3 mm to 10 cm. A planar heater having width and length at least three times of the characteristic heat transfer dimension provides at least one surface of uniform temperature distribution for heating purposes. Heating is conducted over a temperature range of 20 to 300° C. The planar heater can be heated by electrical power of by thermal fluid.
Fundamentals of Structural Materials for Nuclear Energy
This chapter presents an overview of the conditions that structural materials being developed for fusion power reactor applications would encounter. We begin by briefly describing the relevant plasma physics conditions that dictate the fusion environment, which determines the loads driving microstructure evolution of fusion structural alloys. The fundamentals of radiation damage in the fusion environment are discussed, but the reader is referred to a much more detailed treatment of this topic given in Chapter 5. Our intent is to highlight the most important degradation mechanisms operating in the fusion environment. We compare and contrast the fusion environment with that found in existing and proposed advanced fission energy systems, highlighting in particular the role that gaseous and solid transmutation products have on property evolution. The majority of the chapter is devoted to a presentation of the principal structural material choices for major subsystems of a fusion power reactor such as the first-wall/blanket, divertor, and vacuum vessel. Our aim is to highlight the essential features of the material choices for each subsystem, and not to delve into the details, since later chapters address each class of structural material in greater depth. The emphasis is on the implication of the environment to the basic physical and mechanical properties requirements of these materials and challenges they face specific to the fusion environment.
The Nuclear Energy Agency (NEA) Expert Group on Innovative Structural Materials (EGISM) was established in 2008 under the guidance of the Nuclear Science Committee (NSC). Its objectives are to conduct joint and comparative studies to support the development, selection and characterisation of innovative structural materials that can be implemented in advanced nuclear fuel cycles, under long service lifetime and extreme conditions, such as high temperature, high dose/dose rate and corrosive chemical environments. In this context of growing interest and initiatives, the EGISM initiated at the beginning of 2018 an activity among its members to: Identify, in a non-exhaustive way, the currently existing programs on innovative materials and fabrication processes in NEA member countries and China; Establish a first cartography of the activities that are underway on these topics and identify common subjects and thematic; Propose a Technology Readiness Level scale to estimate the maturity of both innovative materials and fabrication processes; Carry out a reflection on what the enablers are to quickly climb this TRL scale, as well as the obstacles, in order to identify solutions to overcome them. This paper first gives definitions shared between the EGISM members on what are considered as advanced structural materials solutions. Next, some international initiatives for the accelerated development of high performance materials are presented both in non-nuclear and nuclear fields. Then, the methodology adopted for technology readiness assessment is explained. A non-exhaustive synthesis of the projects identified among the EGISM members on innovative structural materials and advanced manufacturing solutions such as additive manufacturing is presented. The TRL level of these projects is evaluated. A focus is also made on some of these projects to illustrate and explain the TRLs chosen as well as highlighting enablers or obstacles identified to climbing up the TRL scale.
In response to the needs of a rapidly growing private fusion industry, the U.S. Fusion Materials Coordinating Committee (FMCC) and the broader U.S. fusion materials research community undertook an extensive effort to create a comprehensive roadmap for fusion materials development. The result of this effort was the U.S. Fusion Materials Community Roadmap (US-FMCR), which describes the steps needed to advance the technical maturity of leading candidates for plasma-facing materials and structural materials for fusion power plants from laboratory-scale experiments to a point of sufficient technological readiness for industrial adoption and implementation. However, researchers face significant resource constraints as well as very aggressive pilot plant development timelines. Thus, the research strategies detailed in the US-FMCR require further assessment to downselect the specific tasks that must be prioritized within the next two to three years, in order to make the most efficient use of funding, human resources, and experimental facilities. This paper presents an overview of the US-FMCR and its development process. We also present the subset of research objectives that the FMCC identified as the most urgent research priorities for the U.S. fusion materials research community. The state-of-the-art of materials research is also highlighted for each class of materials considered in the US-FMCR. The recommendations presented here integrate an extensive evaluation of the current status of fusion materials research with a broad cross-section of opinion from the wider U.S. fusion community.
To address the need for physics-based models to predict corrosion behavior of materials in molten salts, here we propose potential methods to aid in selection of optimum materials for structural components in molten salt powered technologies. In the present work, the role of alloy thermodynamics and kinetics on governing corrosion rates of Ni-based alloys will be discussed combining experimental and computational methods. A few strategies are presented to quantify corrosion rates of Ni-based materials isothermally exposed in purified KCl-MgCl 2 salts at 600° C-800° C. The influence of capsule material, potential corrosion products and role of alloy composition on the observed corrosion rates was discussed with coupled thermodynamic-kinetic models. Larger depths of corrosion attack were observed in alloy 230 specimens compared to other alloys under similar conditions was attributed to the much higher chemical activity of Cr in the alloy that results in a larger Cr chemical potential gradient.
Fusion power plant designs feature extreme material performance requirements for structural material candidates. In addition to conventional alloys, more advanced composites and oxide dispersion strengthened (ODS) alloys are being explored, however, achieving the desired microstructures to maximize performance using traditional manufacturing methods can be challenging. The advanced manufacturing (AM) electric field-assisted sintering (EFAS) technique offers improved control over the final microstructure through higher heating and cooling rates and moderate pressures. Modeling and simulation tools show promise in elucidating the process-structure-property-performance (PSPP) correlation for AM-produced parts, including the EFAS process. An inherently multiscale process, the EFAS technique aligns well with the multiscale modeling capability of the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE)[cite]. We present here an electro-thermo-mechanical approach to modeling the EFAS process using the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) code. Prediction of the field and gradient distributions across the EFAS tooling is required to accurately describe the conditions for the lower-scale microstructural evolution models. In this work we present the MALAMUTE model developed to predict the electrical potential, temperature, and mechanical stress distribution across the EFAS graphite tooling and part at the larger engineering-scale. Validation of the MALAMUTE engineering-scale model is completed using data from experimental densification and pre-densified runs of iron powder via EFAS at 1000oC. These runs were conducted using a Thermal Technology DCS-5 EFAS system. Data collected during the experiment runs include the direct current (DC) supplied to the graphite tooling, the temperature of the graphite tooling as measured with a pyrometer, and the force applied to the top of the graphite tooling stack, and the data were recorded every 10 seconds. Our validation approach used the current and force data from the EFAS run as boundary condition inputs to the MAMALUTE simulation; the temperature data were used to evaluate the MALAMUTE EFAS model prediction. Results of the MALAMUTE simulations are employed to connect the external pyrometer temperature measurement to the temperature profile across the part undergoing consolidation. We investigate the impact of material property variation and mesh deformation on the temperature profile as predicted by MALAMUTE. We conclude by highlighting projects where the MALAMUTE EFAS modeling and simulation capabilities will be used to assist experimental design.