Comparative Failure Analysis of Components Exposed to Multi-axis and Single-axis Vibration Testing .
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The Bree solution to the problem of a ratcheting cylinder under constant pressure and cyclic thermal load is a fundamental result in nuclear engineering and widely used as the technical basis for the ASME Boiler and Pressure Vessel Code and other design methods. However, because the loading conditions in the Bree problem are difficult to achieve experimentally there have been relatively few works experimentally examining the problem and extending it to other relevant design situations, for example cladded components. In contrast, 2-bar problems are widely studied experimentally and are relatively easy to setup. These 2-bar problems are thought to be representative of Bree-type geometries, but a formal connection has not been demonstrated. This work formally establishes the connection between the Bree cylinder and an n-bar problem a coupled bar experiment with, in general, more than two bars linked in parallel. The connection suggests that n-bar experiments using a fairly limited number of bars might be an experimentally-accessible setup that better represents ratcheting phenomenon in actual nuclear pressurized components. Such experiments could test surrogate cladded or multi-material components by using bars of different materials. Finally, this work suggests control schemes that yield optimally efficient n-bar experiments experiments that best replicates a Bree cylinder with a limited number of bars.
A multi-mode approach for real-time inspection of structural components may be applied to rapid, wide area measurement of thickness of thick plate-like structures using full-field multi-mode response measurement and analysis. The approach may allow estimation of thickness from full-field multi-mode response to single-tone ultrasonic excitation in thick plates. The approach may utilize wavenumber information across all available wave modes in order to make wavenumber spectroscopy sensitive to changes in thickness for a broader range of nominal initial thicknesses.
Abstract Aluminum castings are increasingly being used in automotive powertrain and structural applications for vehicle lightweighting. Cast aluminum parts often need to be machined and joined to steel components in multi-material systems. Bimetallic components produced by casting aluminum over steel substrate are advantageous due to the elimination of machining and traditional dissimilar material joining processes. However, forming a strong metallurgical bonding during overcasting process has been challenging. In this paper, the effects of processing conditions such as substrate surface preparation, pre-heating temperature, melt conditions as well as casting design were studied by investigating the bimetallic interfaces for aluminum A319 casting alloy and a high alloy steel substrate in a sand-casting process. Zn and Al-based substrate coatings were evaluated. The experimental results suggest a metallurgical bond between aluminum and steel can be formed during the sand-casting process via high temperature diffusion with or without coatings. Al-based substrate coating prior to overcasting results in the formation of a continuous layer of intermetallics at the bimetallic interface, with large Al–Si–Fe intermetallics penetrating the cast aluminum.
Additive manufacturing (AM) is a revolutionary technology. One of the key AM categories, metal powder-based fusion processes, has many advantages compared to conventional methods for fabricating structural materials, such as permitting increased geometric complexity. While single material metal powder AM has advanced significantly in the past decade, multi-material AM is gradually attracting more attention owing to the recent breakthrough in multi-material feedstock delivery and the growing interest of fabricating functionally graded components. Multi-material AM offers an alternative route for applications that require location dependent material properties and high geometrical complexity. The AM community has invented several ways to achieve compositional gradients and discrete boundaries in two and three dimensions using mechanical spreading, nozzle-based, electrophotographic, and hybrid techniques. This article reviews the current state of laser powder bed fusion based multi-material AM of metals with focuses on the characteristics of the material interface as well as the properties and performance of the AM built functionally graded materials. We show the common challenges and issues related to material transitions, such as defects, segregation, phase separation, and the efficacy of some potential solutions including material and process optimizations. Additionally, this study evaluates the applicability and limitations of the existing testing standards and methods for measuring mechanical performance of functionally graded materials. Finally, we discuss mechanical testing development opportunities, which can help multi-material AM move towards higher technological maturity. In general, we find that the link between gradient microstructure and mechanical properties is not well understood or studied and suggest several mechanical tests that may better inform this knowledge gap.
Here, we propose a consistent and conservative model for multiphase and multicomponent incompressible flows, where there can be arbitrary numbers of phases and components. Each phase has a background fluid called the pure phase, each pair of phases is immiscible, and components are dissolvable in some specific phases. The model is developed based on the multiphase Phase-Field model including the contact angle boundary condition, the diffuse domain approach, and the analyses on the proposed consistency conditions for multiphase and multicomponent flows. The model conserves the mass of individual pure phases, the amount of each component in its dissolvable region, and thus the mass of the fluid mixture, and the momentum of the flow. It ensures that no fictitious phases or components can be generated and that the summation of the volume fractions from the Phase-Field model is unity everywhere so that there is no local void or overfilling. It satisfies a physical energy law and it is Galilean invariant. A corresponding numerical scheme is developed for the proposed model, whose formal accuracy is 2nd-order in both time and space. It is shown to be consistent and conservative and its solution is demonstrated to preserve the Galilean invariance and energy law. Numerical tests indicate that the proposed model and scheme are effective and robust to study various challenging multiphase and multicomponent flows.
Robust fermentation of biomass-derived sugars into bioproducts demands the reliable microbial expression of metabolic pathways. Plasmid-based expression systems may suffer from instability and result in highly variable titers, rates, and yields. An established mitigation approach, Chemical Induced Chromosomal Expansion (CIChE), expands a singly integrated pathway to plasmid-like copy numbers, while maintaining stability in the absence of antibiotic selection pressure. Here, we report Parallel Integration and Chromosomal Expansion (PIACE), extensions to CIChE that enable independent expansions of pathway components across multiple loci, use suicide vectors to achieve high-efficiency site-specific integration of sequence-validated multi-gene components, and introduce a heat-curable plasmid to obviate recA deletion post pathway expansion. We applied PIACE to stabilize an isopentenol pathway across three loci in E. coli DH1, and to then generate libraries of pathway component copy-number variants to screen for improved titers. Furthermore, polynomial regressor statistical modeling of the production screening data suggests that increasing copy numbers of all isopentenol pathway components would further improve titers.
As offshore wind systems become more complex, the risk of human error or equipment malfunction increases during experimental testing. This study investigates a lab-scale incident involving a 1 : 50 scale 5 MW wind turbine, where a generator failure led to rotor overspeed and a blade–tower strike. To improve early fault detection, we propose a data-driven method based on multivariate long short-term memory (LSTM) models. High-frequency measurements are projected onto principal components, and anomalies are identified using reconstruction error and its time derivative. Two models are trained on different healthy datasets and tested using single- and multi-principal component (1PC and MPC) variations. Results show that combining both error and error derivative improves detection accuracy. The 1PC model detects faults faster, has a higher recall rate, and achieves a 43 % improvement in anomaly detection accuracy, while the MPC model yields higher precision. This approach provides a simple and effective tool for early anomaly detection in lab-scale experiments, helping to reduce the risk of future failures during the testing of new technologies.
Today’s energy infrastructure is undergoing a massive transformation across all generation, transmission, and distribution systems to provide reliability, efficiency, and sustainability to the power system network. During the past 10 years, there has been a remarkable enhancement in developing close-loop wide-area protection and control (WAPAC) applications, such as automatic generation control (AGC), wide-area protection scheme (WAPS), synchrophasor-based wide-area voltage control system (WAVCS), etc., in the energy management system (EMS) to provide an adequate situational awareness to control center operators during physical disturbances and natural events. The rapid digitalization, unencrypted communication, and numerous data-sharing devices have increased digital access points that have exposed the grid network to countless cyberattacks pertinent to the WAPAC cybersecurity. Given the amount of complex grid network coupled with legacy infrastructures, it is untrustworthy to completely rely on information technology (IT)-based conventional security measures to defend against evolving cyberattacks. Hence, there is a compelling need to go beyond the traditional paradigm of ‘security by obscurity’ and ‘bolt-on’ security measures, and develop a suite of innovative security solutions at multiple layers to transform the current “fault-resilient” grid into “fault and attack-resilient” grid of the future. This dissertation specifically focuses on developing application-specific attack-resilient solutions for critical WAPAC applications in the smart grid. The first part of the study, Attack-Resilient Wide-Area Protection Scheme, presents a cyber-physical attack-resilient system (CPARS) for WAPS, where two anomaly detection methods are proposed to detect multi-level cyberattacks followed by the rules-based intrusion mitigation system (RIMS) to initiate effective mitigation strategies, tailored to these attacks, to restore the normal grid operation after disturbances. The first anomaly detection component, Machine learning-based Anomaly Detection for Centralized WAPS, discusses a novel architecture and methodology for developing a machine-learning-based anomaly detection system (ADS) for the centralized wide-area protection system (CWAPS) by applying the variational mode decomposition (VMD) technique and decision tree (DT) algorithms using cyber logs and synchrophasor measurements. The second component, Multi-Agent-based Anomaly Detection for Decentralized WAPS, presents a two-level hierarchical multi-agent-based decentralized WAPS against the system-aware stealthy cyber-attacks. Finally, for the RIMS, the state transition diagram-based mitigation measures are defined based on the grid operation states and experimental testing and evaluation are presented in a cyber-physical testbed environment. The second part of the study, Attack-Resilient Wide-Area Voltage Control System, addresses the existing vulnerabilities in the wide-area voltage control system (WAVCS), presents the methodology for performing an impact analysis during data integrity attacks, and proposes a data-driven attackresilient system (DARS) by incorporating machine learning-based ADS and rules-based anomaly mitigation system (RAMS) to detect these attacks and provide necessary mitigation actions to maintain the transient voltage stability after disturbances. Finally, the third part, Networked Federation Testbed (NEFTSec) for Smart Grid Cybersecurity, focuses on developing an interconnected federated testbed through a common network like the internet, describes its conceptual architectures, and also presents its design components for experimental testing, validation, and evaluation. Further, it presents the co-simulation interface algorithm (CIA) to facilitate the geographically-dispersed real-time distributed simulation (GD-RTDS) during the cyber-physical federation. In general, this dissertation presents innovative attack-resilient solutions for WAPAC applications that are experimentally tested and evaluated using the PowerCyber testbed and NEFTSec platform to accelerate the transition of state-of-the-art research works to the real-field deployments.
The poster summarizes the main results for a LDRD focused on developing a arc-based additive manufacturing (AM) system capable of fabricating large components with a composition gradient otherwise known as functionally graded materials (FGMs). FGMs are capable of addressing local extreme conditions in an optimal and cost-effective manner. The AM system (referred to as multi-Wire Arc Additive Manufacturing or m-WAAM) consisted of modifying a standard automated gas tungsten arc welding system to deliver multiple welding wires to the weld pool at controlled rates to deposit desired alloy compositions at critical locations. Numerous shapes and composition gradients were fabricated with the system and the effect of various deposition parameters on the nature of the composition profile were evaluated. Additionally, heat treatment of the FGM was performed to develop graded microstructures which should enhance dynamic impact performance of inexpensive steels. The project highlights the potential of m-WAAM to efficiently fabricate FGMs. However, this project only explored the science behind the technique and additional development work will be required to develop a fully-functional system that can build more complex components.
A process for forming a solid product or products is disclosed. The process is provided with n desublimating exchangers. An exchanger E1 being associated with a first exchanger and an exchanger En being associated with an nth exchanger, n representing the number of exchangers. The n exchangers comprise at least one direct-contact exchanger comprising a contact fluid. A process fluid is passed through the n exchangers in order from E1 through En. The process fluid comprises a product component or components. The solid product or products form from the product component or components in the plurality of exchangers by desublimation. The solid product or products are separated from the process fluid. In this manner, a solid product or products is formed.
Additive Manufacturing (AM) is expected to play a large role in the labs-wide goals of accelerating innovation and leading in modern engineering. More specifically, AM is seen as a key enabling technology for increasing the agility of nuclear deterrence and other national security applications involving complex coupled environments. However, the impact of AM on these initiatives has not been as wide-ranging as hoped because – despite its unique qualities – the focus has mostly been on detailed qualification to force AM components into pre-existing performance envelopes. This paradigm fundamentally precludes the novel possibilities afforded by the geometric and material flexibility of AM. In particular, the engineering of small-scale features to undergo buckling and contact can cause large geometric and symmetry changes which provide responsiveness to different environments. Despite almost a decade of observing such behavior, there exists no way to systematically design for AM to exploit it. Our goal for this project was to connect material design to multi-environment component performance by reconceptualizing how to design for AM to exploit the buckling and contact of small-scale features.
Complex plasma mixtures with three or more components are often encountered in astrophysics or in inertial confinement fusion (ICF) experiments. For mixtures containing species with large differences in atomic number Z, the modeling needs to consider at the same time the kinetic theory for low-Z elements combined with the theory of strongly coupled plasma for high-Z elements, as well as all the intermediate situations that can appear in multi-component systems. For such cases, we study the pair distribution functions, self-diffusions, mutual diffusion and viscosity for ternary mixtures at extreme conditions. These quantities can be produced from first principles using orbital free molecular dynamics at the computational expense of very intensive simulations to reach good statistics. Utilizing the first-principles results as reference data, we assess the merit of a global analytic model for transport coefficients, "Pseudo-Ions in Jellium" (PIJ), based on an iso-electronic assumption (iso-n e ). With a multi-component hypernetted-chain integral equation, we verify the quality of the iso-n e prescription for describing the static structure of the mixtures. This semi-analytical modeling compares well with the simulation results and allows one to consider plasma mixtures not accessible to simulations. Further, applications are given for the mix of materials in ICF experiments. A reduction of a multicomponent mixture to an effective binary mixture is also established in the hydrodynamic limit and compared with PIJ estimations for ICF relevant mixtures.
Although significant progress has been made in the self-assembly of nanostructures, present successes heavily rely on precision in building block design, composition, and pair interactions. These requirements fundamentally limit our ability to synthesize macroscopic materials where the likelihood of impurity inclusion escalates and, more importantly, to access molecular-to-nanoscopic-to-microscopic-to-macroscopic hierarchies, since the types and compositions of building blocks vary at each stage. Inspired by biological blends and high-entropy alloys, we hypothesize that diversifying the blend’s composition can overcome these limitations. Increasing the number of components increases mixing entropy, leading to the dispersion of different components and, as a result, enhances interphase miscibility, weakens the dependence on specific pair interactions, and enables long-range cooperativity. This hypothesis is validated in complex blends containing small molecules, block copolymer-based supramolecules, and nanoparticles/colloidal particles. Hierarchically structured composites can be obtained with formulation flexibility in the filler selection and blend composition. It is worth noting that, by adding small molecules, we can solve the size constraint that plagues traditional block copolymer/nanoparticle blends. Detailed characterization and simulation further confirm that each component is distributed to locally mediate unfavorable interactions, cooperatively mitigate composition fluctuations, and retain structural fidelity. Furthermore, the blends have sufficient mobility to access tunable microstructures without compromising the order of the nanostructure. Besides establishing a kinetically viable pathway to release current constraints in the composite design and to navigate uncertainties during structure formation over multiple length scales, the present study demonstrates that entropy-driven behaviors can be realized in systems beyond high-entropy alloys despite inherent differences between metal alloys and organic/inorganic hybrids.
Hierarchical zeolites containing both micropores and mesopores are valuable catalysts for facilitating reactions of large molecules. Furan acylation by fatty acids is a promising reaction for valorizing biomass, and the self-pillared pentasil (SPP) zeolite was found to perform particularly well for this reaction. To better understand the distribution of molecules in hierarchical zeolites at the elevated temperature (T = 523 K) and the elevated pressure (p >1 bar) associated with typical reaction conditions, unary and binary adsorption were predicted using Monte Carlo simulations in the isothermal–isobaric Gibbs ensemble. Adsorption of six species (furan, hexanoic acid, -hexane, -decane, -tetradecane, and 3,6-diethyloctane) was investigated from vapor, liquid, and supercritical phases, and loadings into the micropores, onto the mesopore surface, and in the mesopore interior of SPP were obtained. As pressure increases, -alkanes fill the micropores before loading the surface and then the interior of the mesopore, while furan and hexanoic acid adsorb strongly to the mesopore surface due to hydrogen bonding interactions with surface silanols. Hydrogen bonding interactions also draw hexanoic acid molecules in the micropore region toward the pore mouths, so their carboxylic acid group forms H-bonds with silanols, while the alkyl tails interact with the micropore walls. Mesopore condensation is observed for molecules below their critical point, and occurs when the Gibbs free energy of transfer into the mesopore interior and onto the mesopore surface converge. When hexanoic acid adsorption occurs in the presence of alkane solvents, then the selectivity and spatial distribution of hexanoic acid in the micropores and on the surface can be tuned by adjusting the fluid pressure and the alkane length and/or branching.
A single phase, face-centered-cubic (FCC) Al 0.3 CoCrFeNi high entropy alloy usually has low yield strength. Here, a precipitate-strengthened Al 0.3 CoCrFeNi has been developed, exhibiting enhanced yield strength while retaining good ductility, which is attributed to a novel microstructure comprising a finely distributed, needle-like B2 phase within the grains of the FCC matrix and a granular σ phase along the grain boundaries. Such a microstructure was obtained by a two-step heat treatment of an as-cast Al 0.3 CoCrFeNi, whose parameters were determined by integrating CALPHAD-based thermodynamic calculations with microstructural characterization by atom probe tomography. In situ neutron diffraction, in conjunction with crystal-plasticity finite-element simulations, has revealed the strengthening effect owing to the load partitioning between the constituent phases. Here, this work has important implications for understanding phase stability and deformation mechanisms in multi-principal component alloys, and paves the way for developing novel microstructures in complex alloys using correlative techniques.
A 14-degree-of-freedom (14-DOF) flexible multibody dynamics model is developed and verified for a semi-submersible floating offshore wind turbine (FOWT). The model considers the coupled dynamics of the platform, tower, nacelle, blades, and mooring subjected to external wind and wave loads. The platform is simplified as a rigid body connected to the seabed by the mooring system. The tower and blade are modeled as flexible cantilever beams. The energy method is used to derive the governing equations of motion, where the kinetic energy, potential energy, and work done by external wind-wave forces are all deduced in a global coordinate system. The 5-MW baseline semi-submersible FOWT is used to verify the derived model against the results simulated from FAST developed by the US National Renewable Energy Laboratory (NREL) at two scenarios: free decay state and different wind-wave load cases. Results show that the established FOWT model can well reflect the vibration characteristics of FAST model. The application of the model to the control of platform pitch with a tuned mass damper is studied. Furthermore, the simplified model could provide a low-order method for the structural dynamics analysis and advanced vibration control design for the multi-body components of the semi-submersible FOWT in the future.