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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 1,495 records · Page 83

Development of a Neural Network Simulator for Studying the Constitutive Behavior of Structural Composite Materials

This paper introduces a recent development and application of a noncommercial artificial neural network (ANN) simulator with graphical user interface (GUI) to assist in rapid data modeling and analysis in the engineering diffraction field. The real-time network training/simulation monitoring tool has been customized for the study of constitutive behavior of engineering materials, and it has improved data mining and forecasting capabilities of neural networks. This software has been used to train and simulate the finite element modeling (FEM) data for a fiber composite system, both forward and inverse. The forward neural network simulation precisely reduplicates FEM results several orders of magnitude faster than the slow original FEM. The inverse simulation is more challenging; yet, material parameters can be meaningfully determined with the aid of parameter sensitivity information. The simulator GUI also reveals that output node size for materials parameter and input normalization method for strain data are critical train conditions in inverse network. The successful use of ANN modeling and simulator GUI has been validated through engineering neutron diffraction experimental data by determining constitutive laws of the real fiber composite materials via a mathematically rigorous and physically meaningful parameter search process, once the networks are successfully trained from the FEM database.

Na, Hyuntae↗

Degradation of ILW Drums Due to Internal Metallic Corrosion - 18036

Within the British nuclear inventory, metallic Intermediate Level Waste (ILW) is encapsulated in grout and stored in stainless steel drums. Based on recent inspections held in the relevant storage facilities (Sellafield, Cumbria), a proportion of these drums have exhibited considerable distortion, raising concerns about the long-term safety of the packages. Distortion may be caused by the generation of voluminous and potentially flammable substances resulting from metallic corrosion occurring within the drums' core. Potential oxygen influx in the event of steel fracture and consequently drum's failure could potentially cause release or even ignition of the encapsulated radioactive material. The mechanical degradation of the encapsulants (stainless steel and grout) induced from the progressive corrosion of the encapsulated metallic components (and the associated volume expansion) was investigated using both Finite Element Modelling (FEM) techniques as well as experimental trials. A parametric study using simplified 3D FE models was performed to determine their structural integrity under different scenarios. Synchrotron X-Ray tomography (XRT) was used to monitor the behaviour of miniaturized ILW drum-simulants, whilst the latter were subjected to controlled accelerated corrosion in situ. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Population of 224 realistic human subject-based computational breast phantoms

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.

61 RADIATION PROTECTION AND DOSIMETRY↗

Transient Chemo‐Mechanical Model of Lithium Plating Impacted by External Pressure

Abstract Lithium anodes show great promise in commercial applications, but are hindered by lithium plating and dendrite growth which cause safety concerns during long‐term cell operation. Stack pressure is experimentally observed to improve cell lifetime; however, the relationship between stress and lithium deposition has remained difficult to elucidate. In this work, a transient, 3D, finite‐element model of the evolution of a lithium anode due to stripping and plating is developed. The evolution of a microscale protrusion on the anode surface is tracked over one charge‐discharge cycle with respect to stack pressure and lithium yield strength. Lithium plastic deformation, nonconformal anode‐separator contact, and separator porosity effects are accounted for. Over the course of several hours of stripping/plating, the anode surface evolves to a similar morphology under pressure regardless of the initial conditions due to lithium plastic deformation and hardening. The rate of this evolution highly depends on the applied pressure and assumed lithium yield strength.

25 ENERGY STORAGE↗

A Novel RFID-Based Strain Sensor for Wireless Structural Health Monitoring

Conventional tools for deformation measurement are widely used for structural health monitoring—i.e. strain gauges and fiber optic sensors—due to their relative low cost and efficiency. However, these techniques still present some drawbacks particularly in limited access locations, since their usage requires some sort of cabling or battery-driven electronics. Thus, in a few situations there may be room for new technologies for deformation monitoring of structures. One of the options are passive radio frequency identification (RFID)-based sensors. In synthesis, like conventional methods, these sensors are attached to the surface a test-piece, but are then remotely interrogated and powered by a transmitter. The solidarity of the sensor to the underlying material means that the detected signal is modified in a way that can be correlated to sample strain in a given direction. This paper encompasses the project of a wireless deformation sensor based on an inverted-F antenna focusing on its miniaturization and performance optimization. For this purpose, such an antenna was designed with the help of finite element modelling tools for operation on a 2.0 mm-thick aluminium sheet, and then experimentally validated through static loading tests. Finally, even though sensors of this kind are still in early developments, results show that RFID sensors represents a promising method for remote deformation assessment in components.

42 ENGINEERING↗

Determining failure properties of as-received and hydrided unirradiated Zircaloy-4 from ring compression tests

An integrated experimental and computational approach was developed to determine the plastic strain at fracture and to investigate the fracture energy of as-received and hydrided unirradiated Zircaloy-4 nuclear cladding tubes in the hoop direction at room temperature from ring compression testing (RCT). This work builds on previous methods in the literature that were developed to obtain the mechanical properties of nuclear cladding before fracture (Young’s modulus, yield stress, and strain-hardening parameters) from experimental RCT results and extends the characterization of this material class to include material failure properties. Furthermore, a ductile damage approach was developed and implemented in a validated finite element model to predict material failure, evaluate fracture energy, and quantify the plastic strain at fracture initiation. The hydrogen content of the Zircaloy-4 specimens was varied up to 610 wppm when the failure became brittle. As expected, increasing hydrogen content caused embrittlement of the Zircaloy-4 samples tested and the plastic strain at fracture and fracture energy to decrease.

36 MATERIALS SCIENCE↗

Microscale modeling of effective mechanical and electrical properties of textiles

Here, a computational framework for assisting in the development of novel textiles is presented. Electronic textiles are key in the rapidly growing field of wearable electronics for both consumer and military uses. There are two main challenges to the modeling of electronic textiles: the discretization of the textile microstructure and the interaction between electromagnetic and mechanical fields. A director-based beam formulation with an assumed electrical current is used to discretize the fabric at the level of individual fibrils. The open-source package FEniCS was used to implement the finite element model. Contact integrals were added into the FEniCS framework so that multiphysics contact laws can be incorporated in the same framework, leveraging the code generation and automated differentiation capabilities of FEniCS to produce the tangents needed by the implicit solution method. The computational model is used to construct and determine the mechanical, thermal, and electrical properties of a representative volume elements of a plain woven textile. Dynamic relaxation to solve the mechanical fields and the electrical and thermal fields is solved statically for a given mechanical state. The simulated electrical responses are fit to a simplified Kirchhoff network model to determine effective resistances of the textile.

36 MATERIALS SCIENCE↗

Computationally efficient models for aqueous organic redox flow batteries

The rising usage of intermittent energy has garnered the need for large scale energy storage systems. Redox flow batteries (RFB) based energy storage system shows promising potential. Numerical simulations and machine learning approaches have been widely used to study RFB performance. The development of autonomous material discovery framework and digital twin of energy storage system usually needs to query cell performance through fast response models. In this study, two computationally efficient models are introduced: a physics-based analytical flow battery model (EZBattery), and a machine learning operator model (Deep Operator Network, denoted by DeepONet). Both models can provide cell performance near instantly, and prediction accuracy was systematically examined on an application of evaluating the performances of a 780 cm 2 aqueous organic redox flow battery (AORFB), using potential anolyte candidates in dihydroxyphenazine (DHP)-based family of organic materials. A validated computationally expansive 3-dimensional multi-physics finite element model by COMSOL was used as the ground truth and provided the training data set for the DeepONet. 1280 samples were generated with 10 properties to mimic the different possible anolyte candidates, and the cell performances were evaluated under 10 different combined operating conditions. The accuracy comparisons for the two computationally efficient models show that both models can provide comparable accuracy in predicting cell charging/discharging voltage curves. DeepONet can provide slightly higher overall accuracy than EZBattery with faster calculation speed, but highly relies on the training dataset. EZBattery does not need a training dataset and can provide interpretable physics-based explanations of the results, while being more flexible to adjust to adapt any different cell designs, flow battery architectures, and electrolyte materials.

Analytical model↗

Grain2Mesh: Mesh Generation for Grain-Scale Nonlinear Elasticity Modeling

The nonlinear hysteretic behavior of rocks under cyclic loading is a crucial area of study in geomechanics. The macroscopic response of a variety of materials has been found to be contingent upon the behavior of the micro-scale structure. This project aims to develop a functional and maintainable software package for generating a multi-phase numerical mesh and accompanying simulation files for finite element modeling used in computational mechanics solvers. Meshes generated from images often lack key preprocessing that reduces noise and prevents mesh element distortion that can increase computational cost. By incorporating user feedback throughout, grain2mesh ensures a high-fidelity mesh that can be used to model grain-scale interactions such as shearing, crack propagation, and interfacial material contrast. Scientific applications of this software include material fracturing, stress-strain analysis for natural and engineered materials, and nonlinear meso-scale analysis.

54 ENVIRONMENTAL SCIENCES↗

Damage detection using experimentally measured mass and stiffness matrices

A method is presented for locating physical damage or change in a structure using experimentally measured mass and stiffness matrices. The approach uses a recently developed algorithm for transforming a state-space realization into a second order structural model with physical displacements as the generalized coordinates. This is accomplished by first rotating a state-space model of the identified structural dynamics into modal coordinates and approximating the mass normalized modal vectors for the output measurement set. Next, the physical mass, damping and stiffness matrices are synthesized directly from the measured modal parameters. This yields experimental mass and stiffness matrices for the structure without the use of a finite element model or a numerical search. The computed mass and stiffness are asymptotically equivalent to a static condensation of the global physical coordinate model. Techniques for solving the inverse connectivity problem are then developed whereby it is possible to assess the stiffness in a region of the structure bounded by several sensors. Applications to both simulated data and experimental data are used to discuss the effectiveness of the approach.

Peterson, L. D.↗

Thermomechanical Real-Time Hybrid Simulation: Conceptual Framework and Control Requirements

Real-time hybrid simulation (RTHS) is an enabling technology that has transformed engineering experimentation and helped researchers expand modeling capabilities. However, breakthroughs are necessary to expand the range of hybrid simulation methods and, thus, enable experiments with loading conditions representing multiple hazards. This paper discusses the development of a new thermomechanical RTHS framework and a systematic approach to determining RTHS control requirements. First, the framework is established using a representative finite element model of a layered structural system subjected to thermal loading. A complete two-layer system model serves as the reference system, and it is then partitioned into a numerical layer and an experimental layer that share interface conditions. Next, a thermal actuator is introduced to impose dynamic thermal loading on the experimental subsystem, serving as a transfer system. Finally, control and performance metrics are defined to evaluate the realization of interface boundary conditions and map this to the RTHS execution. Through an illustrative example considering the influence of temperature on a lunar habitat, we demonstrate how to establish controller requirements for RTHS and demonstrate that this approach can be used to conduct RTHS on structures with thermomechanical loading.

Herta Montoya↗

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗

Carbon nanotube biconvex microcavities

Developing highly efficient microcavities with predictive narrow-band resonance frequencies using the least amount of material will allow the applications in nonlinear photonic devices. We have developed a microcavity array that comprised multi-walled carbon nanotubes (MWCNT) organized in a biconvex pattern. The finite element model allowed designing microcavity arrays with predictive transmission properties and assessing the effects of the microarray geometry. The microcavity array demonstrated negative index and produced high Q factors. 2–3 μm tall MWCNTs were patterned as biconvex microcavities, which were separated by 10 μm in an array. The microcavity was iridescent and had optical control over the diffracted elliptical patterns with a far-field pattern, whose properties were predicted by the model. It is anticipated that the MWCNT biconvex microcavities will have implications for the development of highly efficient lenses, metamaterial antennas, and photonic circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Assembly Tests of the First Nb 3 Sn Low-Beta Quadrupole Short Model for the Hi-Lumi LHC

In preparation for the high-luminosity upgrade of the Large Hadron Collider (LHC), the LHC Accelerator Research Program (LARP) in collaboration with CERN is pursuing the development of MQXF: a 150-mm-aperture high-field Nb3Sn quadrupole magnet. Moreover, the development phase starts with the fabrication and test of several short models (1.2-m magnetic length) and will continue with the development of several long prototypes. All of them are mechanically supported using a shell-based support structure, which has been extensively demonstrated on several R&D models within LARP. The first short model MQXFS-AT has been assembled at LBNL with coils fabricated by LARP and CERN. In our paper, we summarize the assembly process and show how it relies strongly on experience acquired during the LARP 120-mm-aperture HQ magnet series. We also present comparison between strain gauges data and finite-element model analysis. Finally, we present the implication of the MQXFS-AT experience on the design of the long prototype support structure.

43 PARTICLE ACCELERATORS↗

Modal Test/Analysis Correlation of Space Station Structures Using Nonlinear Sensitivity

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlation. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Gupta, Viney K.↗

Modal test/analysis correlation of Space Station structures using nonlinear sensitivity

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlations. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Gupta, Viney K.↗

Modeling of elastically mounted vertical rotor

The evaluation of the dynamic behavior of a rotating system is possible by means of modal parameters (Eigenvalues and Eigenvectors). A mixed analytical and experimetal approach is used to identify the modal parameters of a specially designed test rig. The modal identification is done both for nonrotating as well as rotating systems. These modal parameters are used to validate a developed Finite Element Model.

Dana, S. S.↗

Development and Qualification of the Primary Structure of the Orion European Service Module

This paper presents an overview of the development and qualification test campaign for the primary structure of the European Service Module of ORION, the NASA spacecraft which will serve the future human exploration missions to the Moon, Mars and beyond. Under an agreement between NASA and ESA, the ORION will be powered by a European Service Module (ESM), providing also water and oxygen for astronauts' life sustainability. The development and qualification of the European Service Module (ESM) is under ESA responsibility with Airbus Defense and Space as the prime contractor. Thales Alenia Space Italia is responsible for design development, manufacturing, assembly and qualification of the Structure subsystem. The European Service Module, installed onto the launch adapter, shall support the crew module with its adapter and a launch abort system. It shall sustain: - A combination of global and local launch loads during lift off and ascent phases, - On orbit loads induced by engine firing for orbital transfers and attitude control. The ESM structure is based on a core made of Composite Fiber Reinforced Polymer (CFRP) sandwich panels complemented by aluminum alloy platforms, longerons and secondary structures. A development campaign has been implemented in order to define and validate composite parts' strength allowable values for design: coupon tests at material level, test at component level up to breadboards tests performed on main structural components (composite to metallic joints, and at panels' discontinuities). An incremental approach as defined in [1] has been followed. A qualification static test campaign at primary structure assembly level has been implemented in order to validate the design against static stiffness and ultimate strength as well as to correlate the structural Finite Element Model (FEM) used for sizing and confirm the margins of safety. The tests have been performed successfully by Thales Alenia Space Italia (TAS-I) on two flight representative structural models (STA1, STA2), in Turin facilities (Italy) between August 2015 and March 2017, with engineering support of technical representatives from Airbus, ESA, NASA and LMCO. The main development and qualification test activities and associated results are presented and discussed in the paper

Structural Testing↗