Search NASA⌕ Search

SEARCH · Search NASA

Results for “material response”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Materials response under hypersonic flow conditions probed by multi-modal diagnostics in a benchtop wind tunnel

In this LDRD “Materials response under hypersonic flow conditions probed by multi-modal diagnostics in a benchtop wind tunnel” a peer-reviewed lab-scale hypersonic wind tunnel (WT) was planned to be assembled in-house, along with time and space resolved and related flow and materials diagnostics to derive high quality measurements and the science that is able to inform the development of our modeling and simulation codes for the hypersonic regime. The baseline capability to achieve Mach 3 flow was scheduled to be completed in Q4 2020, in the first year of the LDRD. However due to the COVID-19 delays and travel restrictions starting in March, 2020 this task could not be completed to carry out the materials response studies in-house, or those planned with external partners that were engaged during this LDRD (NASA Langley, NASA Ames, Texas A&M university, and Virginia Tech). Still, using our hypersonic computational fluid simulation codes, many of the hypersonic components have been designed (for Mach 3, 5, and 7) and procured (or in procurement phase), and a new dedicated hypersonic laboratory was facilitized, 2 WT test sections have been manufactured, and a Mach 3 nozzle was 3D printed for prototyping. In parallel, unique materials diagnostics have been tested under static conditions and fully specified and awaiting validation in our partner facilities. Due to the new hypersonic initiative announced in January, 2020 we proposed a related scope increase in hypersonics research requiring energy interactions and new diagnostics well beyond what could be supported by an LDRD ER. A decision was made to end the current LDRD ER and formally propose a new LDRD SI that leverages the current effort, which will be starting in FY21. As a result of the uniqueness of this LDRD work, our early efforts have been encouraged and well received in the hypersonic research community, and is now part of multiple unsolicited internal and external project proposals expected to be funded in the coming years, which is encouraging to make LLNL a leader in experimentally probing extreme physics of local energetics critical to hypersonics.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Characterization of Solid Materials Responsible for the Partial Blockage of the 3H Evaporator-to-Mercury Removal Tank Drain Line

In April 2015, part of the solid wet cake material responsible for partially obstructing of the drain line from the Mercury Removal Tank (MRT) on the 3H Evaporator was delivered to SRNL for analysis. The desired analytical goal was to identify the chemical components of the material responsible for the partial blockage and if possible, infer possible formation mechanisms and the best way of removing the consolidated clogging solid material from the drain line.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Uncertainty Quantification Framework for Predicting Material Response with Large Number of Parameters: Application to Creep Prediction in Ferritic-Martensitic Steels Using Combined Crystal Plasticity and Grain Boundary Models

This paper presents an uncertainty quantification (UQ) framework for the physics-based model prediction of material response with a large number of parameters. The application problem presented in this work is that of predicting creep in Grade 91 steel at 600°C. The material response is defined with a physically based microstructural model with constitutive equations emulating several observed phenomena in Grade 91 and embodied into an explicit geometry mesoscale finite element model for prior austenite grains and grain boundaries. Creep within the grains and in grain boundaries are represented by crystal plasticity for dislocation motion and a physics-based model for cavity growth and nucleation, respectively. The creep behavior of this material is influenced by several parameters, some of which have a wide range of variation based on experimental data. UQ combined with microstructural modeling can discover the core microstructural causes of experimental variability, leading to improved materials with lower variability in critical long-term material properties. In this study, we investigate the model's uncertainty to identify material properties that may be modified during production to increase creep life and analyze different components of the crystal plasticity model for improvements. For this purpose, a quantity of interest is defined as time to minimum creep rate, which correlates well to the creep failure of the material. A deep neural network model was trained and validated to be used as a surrogate for the finite element model. Then, a variance-based sensitivity analysis is performed on the surrogate model to find the Sobol indices of the input parameters in respect to the output quantity of interest. The Sobol indices are used to reduce the dimensionality of the model. Generalized polynomial chaos expansion is used on the reduced basis models to propagate the uncertainty from the input parameters to the quantity of interest using the deep neural network surrogate model. These results are benchmarked against uncertainty propagation using Monte Carlo simulations. In conclusion, the UQ performed through the reduced basis model captures almost all the uncertainty in the model with significantly fewer simulations, making it possible to perform the UQ directly via simulations with the finite element model rather than surrogate machine-learned models.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hydration and Restructuring of Polar Polymer Interfaces: Implications in Antifouling and Responsive Materials

Manipulating polymer interfaces is crucial for understanding how structure influences function in applications spanning biofouling prevention to energy storage. Moreover, observing how polymers adapt their microscopic structure to changes in their local environment can reveal essential properties that govern their performance in such applications, providing key insights into how to design more effective interfaces. Here, in this study, a series of “grafting-from” polymer brushes with side chains varying in charge, are probed by sum frequency generation (SFG) and modeled using all-atom molecular dynamics (MD) simulations to elucidate how chemical makeup and charge mediate interfacial restructuring in dry versus hydrated states. Results show that charge, in progressing from nonpolar to cationic to zwitterionic, results in dramatic changes in interfacial structure and overall hydration. While net neutral systems, regardless of bulk phase polarity, show minimal interfacial water structuring, the cationic species exhibits strong bulk water signals from the surface potential. Meanwhile, the polymer brushes themselves restructure in water differently independent of charge, impacting the functional groups that are presented to the aqueous phase. Nonpolar and cationic species for instance undergo a change in alkyl group orientations to accommodate hydrating water molecules, whereas the zwitterionic polymer becomes completely disordered in water. Overall, the structure-based behavior trends presented herein have implications in antifouling applications and responsive material interfaces.

biointerface↗
DOE OSTI2015

The development of criticality response materials - 14282

The Sellafield nuclear facility in the UK comprises a highly complex suite of plants and processes. This in turn demands a consistent and high performance from Emergency Response teams and management in order to demonstrate readiness to respond and combat any nuclear emergency. In order to continue to improve such readiness, a comprehensive programme of development has been undertaken by the Licensee. The programme spans the totality of the emergency response cycle which is resolved into three broad areas: Preparedness; Response; Building Specific File. Within these broad categories the focus of the materials changes from broad and general materials in the preparedness section to actual scenario specific materials in the Building Specific Files Sellafield Ltd. provided the scope of work for the totality of the criticality response materials, known collectively as Criticality Accident Response Data (CARD). The UK National Nuclear Laboratory (NNL) was challenged to technically underpin, develop and present the information in a format and layout that would satisfy the requirements of consistency, brevity, simplicity and relevance. One of the key areas targeted for improvement, and the focus of this paper, was the criticality accident response information that sits within the Building Specific File. At this level of the emergency response cycle by necessity the information must be detailed and specific and enable the emergency responder to understand the problem and assist in formulating a recovery plan. One of the key challenges faced by NNL and discussed in this paper was how to provide the emergency responder with the greatest amount of relevant information in the simplest form. NNL solved this problem by presenting the information in a 'four-block' format which includes a common set of information in textual and diagrammatic form. This paper presents on overview of the criticality accident specific four-blocker, highlights the problems encountered and focuses on the new and innovative materials developed. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Partitioning of Ionization and Displacement Kerma in Material Response Functions

Calculations of total dose (relatable to heating) and ionizing dose (relatable to electron - hole pair formation) typically rely upon material kerma response functions and an assumption of charged particle equilibrium. Traditionally, kerma functions designed for use with the Sandia ASC NuGET code were created via the HEATR module of the NJOY code system, in which a simplifying monoatomic assumption in made. The purpose of this study is to relax that approximation through the use of binary collision simulation techniques, which can take into account the co - existence of multiple elements in a material. Specifically, the total, ionization, and displacement components of kerma are evaluated in silicon, gallium arsenide, gallium nitride, and indium phosphide using the TRIM and MARLOWE codes, and are compared against the equivalent NJOY - based functions. Based on the results, a binary collision - based methodology is proposed for extracting the partial kerma components of high - importance materials.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Systematic Studies in Dynamic Material Response—Early-Career Postdoctoral Research LAO-065-16, Year 2 of 2

Our method (developed under Brandon La Lone’s strategic SDRD) for making low-pressure shock Hugoniot measurements has been improved. It holds great promise for making better low pressure Hugoniot measurements and contributing to the shock physics community. We have refined our method for obtaining information on strength properties of materials, including copper, aluminum, and iron, to a potentially workable technique. Looking at materials other than aluminum with greater strength would likely produce relevant data. Our work with pure iron has yielded interesting results that complement other work on various steel alloys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Theoretical prediction of a highly responsive material: Spin fluctuations and superconductivity in FeNiB 2 system

By analyzing the Fe-Ni-B compositional diagram, we predict an energetically and dynamically stable FeNiB 2 compound. This system belongs to the class of highly responsive state of materials, as it is very sensitive to the external perturbations. This state is also characterized by a high level of spin fluctuations, which strongly influence possible magnetic long- and short-range orders. Furthermore, we demonstrate that these antiferromagnetically dominating fluctuations could lead to the appearance of spin mediated superconductivity. The obtained results suggest a promising avenue for the search of strong spin fluctuation systems and related superconductors. Spin fluctuations (SFs) in itinerant electron magnets play an important role in many metallic systems including weak itinerant magnets, heavy fermion compounds, actinides, Invar alloys, and many magnetoresistive materials. SFs also have been identified in high-temperature superconductors and recently discovered Fe-based superconductors with a clear suggestion about their crucial influence on the mechanisms of unconventional superconductivity. In the majority of cases, superconductivity appears near the magnetic quantum critical point, where magnetism has a pure itinerant character with no local moments involved. This is exactly a case when quantum SFs (including spin zero-point motion) are strong and provide a dominating contribution to many observable physical properties. However, as a typical example, in a case of superconductivity, the direct calculations and prediction of critical temperature from first principles are still not possible. In this situation, one can focus on searching for materials with a strong level of SF, leading to the possible development of promising physical properties. In this paper, we will introduce qualitatively the concept of a highly responsive state (HRS) (see Fig. 1). This term is used here to indicate that a physical system is in a state characterized by an order parameter, which is very sensitive to the external perturbations (pressure, magnetic fields, etc.). The HRS is naturally related to closeness to the instability and, as usual in such situations, one can expect that fluctuations are very important.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

High speed synchrotron x-ray phase contrast imaging of dynamic material response to split Hopkinson bar loading

The successful process of amalgamating both the time-resolved imaging capabilities present at the Advanced Photon Source beamline 32ID-B and the proficiency of high-rate loading offered by the split Hopkinson or Kolsky compression/tension bar apparatus is discussed and verification of system effectiveness is expressed via dynamic experiments on various material systems. Single particle sand interaction along with glass cracking during dynamic compression, and fiber-epoxy interfacial failure, ligament-bone debonding, and single-crystal silicon fragmentation due to dynamic tension, were imaged with 0.5 {mu}s temporal resolution and {mu}m-level spatial resolution. Synchrotron x-ray phase contrast imaging of said material systems being loaded with the Kolsky bar apparatus demonstratively depicts the effectiveness of the novel union between these two powerful techniques, thereby allowing for in situ analysis of the interior of the material system during high-rate loading for a variety of applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Peridynamic neural operators: A data-driven nonlocal constitutive model for complex material responses

Neural operators, which can act as implicit solution operators of hidden governing equations, have recently become popular tools for learning the responses of complex real-world physical systems. Nevertheless, most neural operator applications have thus far been data-driven and neglect the intrinsic preservation of fundamental physical laws in data. Here, in this work, we introduce a novel integral neural operator architecture called the Peridynamic Neural Operator (PNO) that learns a nonlocal constitutive law from data. This neural operator provides a forward model in the form of state-based peridynamics, with objectivity and momentum balance laws automatically guaranteed. As applications, we demonstrate the expressivity and efficacy of our model in learning complex material behaviors from both synthetic and experimental data sets. We also compare the performances with baseline models that use predefined constitutive laws. We show that, owing to its ability to capture complex responses, our learned neural operator achieves improved accuracy and efficiency. Moreover, by preserving the essential physical laws within the neural network architecture, the PNO is robust in treating noisy data. The method shows generalizability to different domain configurations, external loadings, and discretizations.

42 ENGINEERING↗