While recent research has greatly improved our ability to test and model nonlinear dynamic systems, it is rare that these studies quantify the effect that the nonlinearity would have on failure of the structure of interest. While several very notable exceptions certainly exist, such as the work of Hollkamp et al. on the failure of geometrically nonlinear skin panels for high speed vehicles (see, e.g., Gordon and Hollkamp, Reduced-order models for acoustic response prediction. Technical Report AFRL-RB-WP-TR-2011-3040, Air Force Research Laboratory, AFRL-RB-WP-TR-2011-3040, Dayton, 2011. Issue: AFRL-RB-WP-TR-2011-3040AFRL-RB-WP-TR-2011-3040), other studies have given little consideration to failure. This work studies the effect of common nonlinearities on the failure (and failure margins) of components that undergo durability testing in dynamic environments. This context differs from many engineering applications because one usually assumes that any nonlinearities have been fully exercised during the test.
Battery energy storage systems (BESSs) are crucial for modernizing the power grid but are monitored by sensors that are susceptible to anomalies like failures, faults, or cyberattacks that could affect BESS functionality. Much work has been done to detect sensor anomalies, but a research gap persists in responding to anomalies. An approach is proposed to mitigate the damage caused by additive bias anomalies by employing one-of-three estimators based on the anomalies present. A tuned cumulative sum (CUSUM) algorithm is used to identify anomalies, and a set of rules are proposed to select an estimator that will isolate the effect of the anomaly. The proposed approach is evaluated using two simulated studies, one in which an anomaly impacts the input and one where an anomaly impacts an output sensor.
Diesel generators (gensets) are often the lowest-cost electric generation for reliable supply in remote microgrids. The development of converter-dominated diesel-backed microgrids requires accurate dynamic modeling to ensure power quality and system stability. Dynamic response derived using original genset system models often does not match those observed in field experiments. This paper presents the experimental system identification of a frequency dynamics model for a 400 kVA diesel genset. The genset is perturbed via active power load changes and a linearized dynamics model is fit based on power and frequency measurements using moving horizon estimation (MHE). The method is first simulated using a detailed genset model developed in MATLAB/Simulink. The simulation model is then validated against the frequency response obtained from a real 400 kVA genset system at the Power System Integration (PSI) Lab at the University of Alaska Fairbanks (UAF). The simulation and experimental results had model errors of 3.17% and 11.65%, respectively. The resulting genset model can then be used in microgrid frequency dynamic studies, such as for the integration of renewable energy sources.
Accuracy-optimized convolutional neural networks (CNNs) have emerged as highly effective models at predicting neural responses in brain areas along the primate ventral stream, but it is largely unknown whether they effectively model neurons in the complementary primate dorsal stream. We explored how well CNNs model the optic flow tuning properties of neurons in dorsal area MSTd and we compared our results with the Non-Negative Matrix Factorization (NNMF) model, which successfully models many tuning properties of MSTd neurons. To better understand the role of computational properties in the NNMF model that give rise to optic flow tuning that resembles that of MSTd neurons, we created additional CNN model variants that implement key NNMF constraints – non-negative weights and sparse coding of optic flow. While the CNNs and NNMF models both accurately estimate the observer's self-motion from purely translational or rotational optic flow, NNMF and the CNNs with nonnegative weights yield substantially less accurate estimates than the other CNNs when tested on more complex optic flow that combines observer translation and rotation. Despite its poor accuracy, NNMF gives rise to tuning properties that align more closely with those observed in primate MSTd than any of the accuracy-optimized CNNs. This work offers a step toward a deeper understanding of the computational properties and constraints that describe the optic flow tuning of primate area MSTd.
Conceptual models of smectite hydration include planar (flat) clay layers that undergo stepwise expansion as successive monolayers of water molecules fill the interlayer regions. However, X-ray diffraction (XRD) studies indicate the presence of interstratified hydration states, suggesting non-uniform interlayer hydration in smectites. Additionally, recent theoretical studies have shown that clay layers can adopt bent configurations over nanometer-scale lateral dimensions with minimal effect on mechanical properties. Therefore, in this study we used molecular simulations to evaluate structural properties and water adsorption isotherms for montmorillonite models composed of bent clay layers in mixed hydration states. Results are compared with models consisting of planar clay layers with interstratified hydration states (e.g. 1W–2W). The small degree of bending in these models (up to 1.5 Å of vertical displacement over a 1.3 nm lateral dimension) had little or no effect on bond lengths and angle distributions within the clay layers. Except for models that included dry states, porosities and simulated water adsorption isotherms were nearly identical for bent or flat clay layers with the same averaged layer spacing. Similar agreement was seen with Na- and Ca-exchanged clays. While the small bent models did not retain their configurations during unconstrained molecular dynamics simulation with flexible clay layers, we show that bent structures are stable at much larger length scales by simulating a 41.6×7.1 nm2 system that included dehydrated and hydrated regions in the same interlayer.
Sandia National Laboratories (SNL) has completed a comparative evaluation of three design assessment approaches for a 2-liter (2L) capacity containment vessel (CV) of a novel plutonium air transport (PAT) package designed to survive the hypothetical accident condition (HAC) test sequence defined in Title 10 of the United States (US) Code of Federal Regulations (CFR) Part 71.74(a), which includes a 129 meter per second (m/s) impact of the package into an essentially unyielding target. CVs for hazardous materials transportation packages certified in the US are typically designed per the requirements defined in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (B&PVC) Section III Division 3 Subsection WB “Class TC Transportation Containments.” For accident conditions, the level D service limits and analysis approaches specified in paragraph WB-3224 are applicable. Data derived from finite element analyses of the 129 m/s impact of the 2L-PAT package were utilized to assess the adequacy of the CV design. Three different CV assessment approaches were investigated and compared, one based on stress intensity limits defined in subparagraph WB-3224.2 for plastic analyses (the stress-based approach), a second based on strain limits defined in subparagraph WB-3224.3, subarticle WB-3700, and Section III Nonmandatory Appendix FF for the alternate strain-based acceptance criteria approach (the strain-based approach), and a third based on failure strain limits derived from a ductile fracture model with dependencies on the stress and strain state of the material, and their histories (the Xue-Wierzbicki (X-W) failure-integral-based approach). This paper gives a brief overview of the 2L-PAT package design, describes the finite element model used to determine stresses and strains in the CV generated by the 129 m/s impact HAC, summarizes the three assessment approaches investigated, discusses the analyses that were performed and the results of those analyses, and provides a comparison between the outcomes of the three assessment approaches.
Determining the thermal response of energetic materials at high densities can be difficult when pressure dependent reactions occur within the interior of the material. At high temperatures, reactive components such as hexahydro-l,3,5-tri-nitro-l,3,5-triazine (RDX), ammonium perchlorate (AP), and hydroxyl-terminated polybutadiene (HTPB) decompose and interact. The decomposition products accumulate near defects where internal pressure ultimately causes mechanical damage with closed pores transitioning into open pores. Gases are no longer confined locally; instead, they freely migrate between open pores and ultimately escape into the surrounding headspace or vent. Recently we have developed a universal cookoff model (UCM) coupled to a micromechanics pressurization (MMP) model to address pressure-dependent reactions that occur within the interior of explosives. Parameters for the UCM/MMP model are presented for an explosive and two propellants that contain similar portions of both aluminum (Al) and a binder. The explosive contains RDX and the propellants contain AP with no RDX. One of the propellants contains small amounts of curing catalysts and a burn modifier whereas the other propellant does not. We found that the cookoff behavior of the two propellants behave similarly leading and conclude that small amounts of catalysts or burn modifiers do not influence cookoff behavior appreciably. Kinetic parameters for the UCM/MMP models were obtained from the Sandia Instrumented Thermal Ignition (SITI) experiment. Validation is done with data from other laboratories.
Dendrites enable neurons to perform nonlinear operations. Existing silicon dendrite circuits sufficiently model passive and active characteristics, but do not exploit shunting inhibition as an active mechanism. We present a dendrite circuit implemented on a reconfigurable analog platform that uses active inhibitory conductance signals to modulate the circuit's membrane potential. We explore the potential use of this circuit for direction selectivity by emulating recent observations demonstrating a role for shunting inhibition in a directionally-selective Drosophila (Fruit Fly) neuron.
Explosives exposed to conditions above the Chapman-Jouget (CJ) state exhibit an overdriven response that is transient. Reactive flow models are often fit to the CJ conditions, and they transition to detonation based on inputs lower than or near CJ, but these models may also be used to predict explosive behavior in the overdriven regime. One scenario that can create a strongly overdriven state is a Mach stem shock interaction. These interactions can drive an already detonating or transitioning explosive to an overdriven state, and they can also cause detonation at the interaction location where the separate shocks may be insufficient to detonate the material. In this study, the reactive flow model XHVRB utilizing a Mie-Grüneisen equation of state (EOS) for the unreacted explosive, and a Sesame table for the reacted products, will be used to examine Mach stem interactions from multi-point detonation schemes in CTH. The effect of the overdriven response driven by PETN-based explosive pellets will be tracked to determine the transient detonation behavior, and the predicted states from the burn model will be compared to previously published data.
Uncertainty quantification (UQ) plays a vital role in addressing the challenges and limitations encountered in full-waveform inversion (FWI). Most UQ methods require parameter sampling which requires many forward and adjoint solves. This often results in very high computational overhead compared to traditional FWI, which hinders the practicality of the UQ for FWI. In this work, we develop an efficient UQ-FWI framework based on unsupervised variational autoencoder (VAE) to assess the uncertainty of single and multi-parameter FWI. The inversion operator is modeled using an encoder-decoder network. The input to the network is seismic shot gathers and the output are samples (distribution) of model parameters. We then use these samples to estimate the mean and standard deviation of each parameter population, which provide insights on the uncertainty in the inversion process. To speed up the UQ process, we carried out the reconstruction in an unsupervised learning approach. Moreover, we physics-constrained the network by injecting the FWI gradients during the backpropagation process, leading to better reconstruction. The computational cost of the proposed approach is comparable to the traditional autoencoder full-waveform inversion (AE-FWI), which is encouraging to be used to get further insight on the quality of the inversion. We apply this idea for synthetic data to show its potential in assessing uncertainty in multi-parameter FWI.
To decarbonize the energy sector, there are international efforts to displace carbon-based fuels with renewable alternatives, such as hydrogen. Storage and transportation of gaseous hydrogen are key components of large-scale deployment of carbon-neutral energy technologies, especially storage at scale and transportation over long distances. Due to the high cost of deploying large-scale infrastructure, the existing pipeline network is a potential means of transporting blended natural gas-hydrogen fuels in the near term and carbon-free hydrogen in the future. Much of the existing infrastructure in North America was deployed prior to 1970 when greater variability existed in steel processing and joining techniques often leading to microstructural inhomogeneities and hard spots, which are local regions of elevated hardness relative to the pipe or weld. Hard spots, particularly in older pipes and welds, are a known threat to structural integrity in the presence of hydrogen. High-strength materials are susceptible to hydrogen-assisted fracture, but the susceptibility of hard spots in otherwise low-strength materials (such as vintage pipelines) has not been systematically examined. Assessment of fracture performance of pipeline steels in gaseous hydrogen is a necessary step to establish an approach for structural integrity assessment of pipeline infrastructure for hydrogen service. This approach must include comprehensive understanding of microstructural anomalies (such as hard spots), especially in vintage materials. In this study, fracture resistance of pipeline steels is measured in gaseous hydrogen with a focus on high strength materials and hardness limits established in common practice and in current pipeline codes (such as ASME B31.12). Elastic-plastic fracture toughness measurements were compared for several steel grades to identify the relationship between hardness and fracture resistance in gaseous hydrogen.
Geogenic gases often reside in intergranular pore space, fluid inclusions, and within mineral grains. In particular, helium-4 (4He) is generated by alpha decay of uranium and thorium in rocks. The emitted 4He nuclei can be trapped in the rock matrix or in fluid inclusions. Recent work has shown that releases of helium occur during plastic deformation of crustal rocks above atmospheric concentrations that are detectable in the field. However, it is unclear how rock type and deformation modalities affect the cumulative gas released. This work seeks to address how different deformation modalities observed in several rock types affect release of helium. Axial compression tests with granite, rhyolite, tuff, dolostone, and sandstone - under vacuum conditions - were conducted to measure the transient release of helium from each sample during crushing. It was found that, when crushed up to 97500 N, each rock type released helium at a rate quantifiable using a helium mass spectrometer leak detector. For plutonic rock like granite, helium flow rate spikes with the application of force as the samples elastically deform until fracture, then decays slowly until grain breakdown comminution begins to occur. Both the rhyolite and tuff do not experience such large spikes in helium flow rate, with the rhyolites fracturing at much lower force and the tuffs compacting instead of fracturing due to their high porosity. Both rhyolite and tuff instead experience a lesser but steady helium release as they are crushed. The cumulative helium release for the volcanic tuffs varies as much as two orders of magnitude but is fairly consistent for the denser rhyolite and granite tested. The results indicate that there is a large degassing of helium as rocks are elastically and inelastically deformed prior to fracturing. For more porous and less brittle rocks, the cumulative release will depend more on the degree of deformation applied. These results are compared with known U/Th radioisotopes in the rocks to relate the trapped helium as either produced in the rock or from secondary migration of 4He.
Multiple-input/multiple-output (MIMO) vibration control often relies on a least-squares solution utilizing a matrix pseudo-inverse. While this is simple and effective for many cases, it lacks flexibility in assigning preference to specific control channels or degrees of freedom (DOFs). For example, the user may have some DOFs where accuracy is very important and other DOFs where accuracy is less important. This chapter shows a method for assigning weighting to control channels in the MIMO vibration control process. These weights can be constant or frequency-dependent functions depending on the application. An algorithm is presented for automatically selecting DOF weights based on a frequency-dependent data quality metric to ensure the control solution is only using the best, linear data. An example problem is presented to demonstrate the effectiveness of the weighted solution.
Hargis, Joshua W.; Egeln, Anthony; Houim, Ryan; Guildenbecher, Daniel R.
Visualization of flow structures within post-detonation fireballs has been performed for benchmark validation of numerical simulations. Custom pressed PETN explosives with a 12-mm diameter hemispherical form factor were used to produce a spherically symmetric post-detonation flow with low soot yield. Hydroxyl-radical planar laser induce fluorescence (OH-PLIF) was employed to visualize the structure ranging from approximately 10μs to 35μs after shock breakout from the explosive pellet. Fireball simulations were performed using the HyBurn Computational Fluid Dynamics (CFD) package. Experimental OH-PLIF results were compared to synthetic OH-PLIF from post-processing of CFD simulations. From the comparison of experimental and synthetic OH-PLIF images, CFD is shown to replicate much of the flow structure observed in the experiments, revealing potential differences in turbulent length scales and OH kinetics. Results provide significant advancement in experimental resolution of these harsh turbulent combustion environments and validate physical models thereof.
The importance of user-accessible multiple-input/multiple-output (MIMO) control methods has been highlighted in recent years. Several user-created control laws have been integrated into Rattlesnake, an open-source MIMO vibration controller developed at Sandia National Laboratories. Much of the effort to date has focused on stationary random vibration control. However, there are many field environments which are not well captured by stationary random vibration testing, for example shock, sine, or arbitrary waveform environments. This work details a time waveform replication technique that uses frequency domain deconvolution, including a theoretical overview and implementation details. Example usage is demonstrated using a simple structural dynamics system and complicated control waveforms at multiple degrees of freedom.
A new Adaptive Mesh Refinement (AMR) keyword was added to the CTH1 hydrocode developed at Sandia National Laboratories (SNL). The new indicator keyword, "ratec*ycle", allows the user to specify the minimum number of computational cycles before an AMR block is allowed to be un-refined. This option is designed to allow the analyst to control how quickly a block is un-refined to avoid introducing anomalous waves in their solution due to information propagating across mesh resolution changes. For example, in reactive flow simulations it is often desirable to accurately capture the expansion region behind the reaction front. The effect of this new option was examined using the XHVRB2, 3 model for XTX8003 to model the propagation of the detonation wave in explosives in small channels, and also for a simpler explosive model driving a steel case. The effect on computational cost as a function of this new option was also examined.
Underground caverns in salt formations are promising geologic features to store hydrogen (H2) because of salt's extremely low permeability and self-healing behavior.Successful salt-cavern H2 storage schemes must maximize the efficiency of cyclic injection-production while minimizing H2 loss through adjacent damaged salt.The salt cavern storage community, however, has not fully understood the geomechanical behaviors of salt rocks driven by quick operation cycles of H2 injection-production, which may significantly impact the cost-effective storage-recovery performance.Our field-scale generic model captures the impact of combined drag and back stressing on the salt creep behavior corresponding to cycles of compression and extension, which may lead to substantial loss of cavern volumes over time and diminish the cavern performance for H2 storage.Our preliminary findings address that it is essential to develop a new salt constitutive model based on geomechanical tests of site-specific salt rock to probe the cyclic behaviors of salt both beneath and above the dilatancy boundary, including reverse (inverse transient) creep, the Bauschinger effect and fatigue.
Numerical simulations were performed in 3D Cartesian coordinates to examine the post-detonation processes produced by the detonation of a 12 mm-diameter hemispherical PETN explosive charge in air. The simulations captured air dissociation by the Mach 20+ shock, chemical equilibration, and afterburning using finite-rate chemical kinetics with a skeletal chemical reaction mechanism. The Becker-Kistiakowsky-Wilson real-gas equation of state is used for the gas-phase. A simplified programmed burn model is used to seamlessly couple the detonation propagation through the explosive charge to the post-detonation reaction processes inside the fireball. Four charge sizes were considered, including diameters of 12 mm, 38 mm, 120 mm, and 1200 mm. The computed blast, shock structures, and chemical composition within the fireball agree with literature. The evolution of the flow at early times is shown to be gas dynamic driven and nearly self-similar when the time and space was scaled. The flow fields were azimuthally averaged and a mixing layer analysis was performed. The results show differences in the temperature and chemical composition with increasing charge size, implying a transition from a chemical kinetic-limited to a mixing-limited regime.
Multifidelity emulators have found wide-ranging applications in both forward and inverse problems within the computational sciences. Thanks to recent advancements in neural architectures, they provide significant flexibility for integrating information from multiple models, all while retaining substantial efficiency advantages over single-fidelity methods. In this context, existing neural multifidelity emulators operate by separately resolving the linear and nonlinear correlation between equally parameterized high-and low-fidelity approximants. However, many complex models ensembles in science and engineering applications only exhibit a limited degree of linear correlation between models. In such a case, the effectiveness of these approaches is impeded, i.e., larger datasets are needed to obtain satisfactory predictions. In this work, we present a general strategy that seeks to maximize the linear correlation between two models through input encoding. We showcase the effectiveness of our approach through six numerical test problems, and we show the ability of the proposed multifidelity emulator to accurately recover the high-fidelity model response under an increasing number of quasi-random samples. In our experiments, we show that input encoding produces in many cases emulators with significantly simpler nonlinear correlations. Finally, we demonstrate how the input encoding can be leveraged to facilitate the fusion of information between low-and high-fidelity models with dissimilar parametrization, i.e., situations in which the number of inputs is different between low-and high-fidelity models.
Multi-axis testing has become a popular test method because it provides a more realistic simulation of a field environment when compared to traditional vibration testing. However, field data may not be available to derive the multi-axis environment. This means that methods are needed to generate “virtual field data” that can be used in place of measured field data. Transfer path analysis (TPA) has been suggested as a method to do this since it can be used to estimate the excitation forces on a legacy system and then apply these forces to a new system to generate virtual field data. This chapter will provide a review of using TPA methods to do this. It will include a brief background on TPA, discuss the benefits of using TPA to compute virtual field data, and delve into the areas for future work that could make TPA more useful in this application.
Photovoltaic modules undergoing laboratory hail tests were observed using high speed video to analyze the key characteristics of impact-induced glass fracture, including crack onset time, initiation location relative to the impact site, and propagation trends. Fifteen commercially representative glass-glass thin-film modules were recorded at 300,000 frames per second during hail impacts which happened to cause glass fracture. Images were processed to identify the time between impact and first plausible glass crack appearance (average 126 μs, standard deviation 59 μs) along with the time to a confirmed crack (average 158 μs, standard deviation 77μs), during the ice ball impacts which had a median kinetic energy of 47 J delivered by 55 mm diameter balls. Limiting factors for identifying glass crack timings were ice ball fragmentation obscuring the impact site and indistinct initial crack appearance, which were inherent to the images and not improved with processing. Computational simulations corresponding to each impact event showed that glass stresses were still localized to the impact site during times with definitively identifiable fracture, and even impacts which did not induce failure created local stress magnitudes exceeding stress levels associated with static glass fracture. These observations confirm that impact-induced glass failure is a time-and rate-dependent phenomena. Results from this study provide baseline metrics for developing a glass fracture criterion to predict module damage during hail impact events, which in turn allows for analysis of design features that may affect damage susceptibility.
Vapor-deposited PETN films undergo significant microstructure evolution when exposed to elevated temperatures, even for short periods of time. This accelerated aging impacts initiation behavior and can lead to chemical changes as well. In this study, as-deposited and aged PETN films are characterized using scanning electron microscopy and ultra-high performance liquid chromatography and compared with changes in initiation behavior measured via a high-throughput experimental platform that uses laser-driven flyers to sequentially impact an array of small explosive samples. Accelerated aging leads to rapid coarsening of the grain structure. At longer times, little additional coarsening is evident, but the distribution of porosity continues to evolve. These changes in microstructure correspond to shifts in the initiation threshold and onset of reactions to higher flyer impact velocities.
For an Energy System to be truly equitable, it should provide affordable and reliable energy services to disadvantaged and underserved populations. Disadvantaged communities often face a combination of economic, social, health, and environmental burdens and may be geographically isolated (e.g., rural communities), which systematically limits their opportunity to fully participate in aspects of economic, social, and civic life.