Evolution of pore size distribution of sandstone under dynamic loading [Slides]
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Impedance testing devices, circuits, systems, and related methods are disclosed. A method may include exciting a device coupled to a load, and capturing a response of the device. The method may further include adjusting the response based on an estimated load response of the device, and estimating an impedance of the device based on the adjusted response.
Distribution systems of the future smart grid require enhancements to the reliability of distribution system state estimation (DSSE) in the face of low measurement redundancy, unsynchronized measurements, and dynamic load profiles. Micro phasor measurement units (µPMUs) facilitate co-synchronized measurements with high granularity, albeit at an often prohibitively expensive installation cost. Supervisory control and data acquisition (SCADA) measurements can supplement µPMU data, although they are received at a slower sampling rate. Further complicating matters is the uncertainty associated with load dynamics and unsynchronized measurements–not only are the SCADA and µPMU measurements not synchronized with each other, but the SCADA measurements themselves are received at different time intervals with respect to one another. This paper proposes a non-linear state estimation framework which models dynamic load uncertainty error by updating the variances of the unsynchronized measurements, leading to a time-varying system of weights in the weighted least squares state estimator. Case studies are performed on the 33-Bus Distribution System in MATPOWER, using Ornstein–Uhlenbeck stochastic processes to simulate dynamic load conditions.
Cross-flow turbines (CFTs) are inherently unsteady devices with regards to operating principle and loading. By improving our understanding of the dynamic loading on these turbines, we hope to better inform CFT design, improve survivability, and reduce overall costs. The University of New Hampshire (UNH) and the National Renewable Energy Laboratory (NREL) collaborated on a project to instrument and test a four-bladed New Energy Corp. vertical axis cross-flow turbine in a real tidal flow. One blade from the 3.2 m diameter x 1.7 m height turbine was instrumented with eight full-bridge strain gauges along the span of the blade. The turbine was then deployed at the UNH-Atlantic Marine Energy Center (AMEC) Tidal Energy Test Site in Portsmouth, NH. Time-synchronized measurements of blade strain, inflow, thrust, rotational speed, and electrical output were obtained to characterize blade loading under various conditions. The blade strain was examined to assess the dynamic loading and conduct a fatigue analysis on the device.
Concentrating Solar Power (CSP) is a promising solar technology for electricity generation with thermal energy storage and with the additional benefit of industrial heat production. Wind loading on CSP collector structures, such as parabolic troughs or heliostats, is one of the primary drivers of their structural design costs. In particular, dynamic wind loading is a major source of uncertainty in the collector design process, which heavily relies on wind tunnel testing. In the field, the turbulent nature of the incoming wind creates fluctuating loads (support structure loads and resulting mirror deflections) on the collectors, with impacts on fatigue lifetime and optical performance. As is well known, wind tunnel tests cannot entirely reproduce the complex turbulent wind conditions typically observed at full-scale plants. To shed light on this topic, NREL initiated a field campaign at the operational Nevada Solar One (NSO) powerplant that uses parabolic troughs as solar collectors. The aim of the project is a detailed characterization of prevailing wind and turbulence conditions and resulting operational loads on parabolic troughs. We use the published 2-year dataset of high-resolution combined wind and structural loads measurements [1] to characterize the dynamic structural wind response. For quantifying dynamic wind loading, we apply the concept of admittance functions, which are spectral transfer functions that couple the turbulent wind to resulting structural loads (aerodynamic admittance), and to the structural response (mechanical admittance). In practice, aerodynamic admittance describes which turbulent eddy sizes are effective in creating structural loads. The mechanical admittance describes in which frequency ranges these loads are reinforced or dampened by the structure. While these functions are an established concept in civil engineering, their recent application to a single full-scale heliostat [2] proved their broader applicability to CSP collectors. Here, we present a characterization of admittance functions for full-scale parabolic trough collectors and show how wind characteristics (mean wind speed and direction, turbulent kinetic energy, turbulent length scales), the sun-tracking trough angle, and row position alter the admittance functions. Further, we study to which extent the admittance functions are universal for a specific trough geometry and how our findings compare to reported heliostat results. References [1] https://data.openei.org/submissions/5938. [2] Blume, K., Roger, M., and Pitz-Paal, R. 2023b. "Simplified analytical model to describe wind loads and wind-induced tracking deviations of heliostats." Solar Energy, 256, 96-109. https://doi.org/10.1016/j.solener.2023.03.055.
Dynamic networks composed of constituents that break and reform bonds reversibly are ubiquitous in nature owing to their modular architectures that enable functions like energy dissipation, self-healing, and even activity. While bond breaking depends only on the current configuration of attachment in these networks, reattachment depends also on the proximity of constituents. Therefore, dynamic networks composed of macroscale constituents (not benefited by the secondary interactions cohering analogous networks composed of molecular-scale constituents) must rely on primary bonds for cohesion and self-repair. Toward understanding how such macroscale networks might adaptively achieve this, we explore the uniaxial tensile response of 2D rafts composed of interlinked fire ants ( S. invicta ). Through experiments and discrete numerical modeling, we find that ant rafts adaptively stabilize their bonded ant-to-ant interactions in response to tensile strains, indicating catch bond dynamics. Consequently, low-strain rates that should theoretically induce creep mechanics of these rafts instead induce elastic-like response. Our results suggest that this force-stabilization delays dissolution of the rafts and improves toughness. Nevertheless, above 35 % strain low cohesion and stress localization cause nucleation and growth of voids whose coalescence patterns result from force-stabilization. These voids mitigate structural repair until initial raft densities are restored and ants can reconnect across defects. However mechanical recovery of ant rafts during cyclic loading suggests that—even upon reinstatement of initial densities—ants exhibit slower repair kinetics if they were recently loaded at faster strain rates. These results exemplify fire ants’ status as active agents capable of memory-driven, stimuli-response for potential inspiration of adaptive structural materials.
The complex relationship between photovoltaic (PV) hardware configurations, overall system dynamics, and turbulent aerodynamic phenomena generates highly unsteady, non-uniform loads that can lead to damaging instabilities. These effects may result in glass breakage, cell cracking, and structural failures in frames and mounting systems, even under moderate wind conditions. Addressing industry concerns about premature system failures in field conditions deemed survivable, our research aims to develop a fast and accurate predictive model for system damage. This model integrates configurable hardware choices with advanced simulation tools to represent the overall system-specific dynamics effectively. Using this model, we predict responses under varying weather conditions and hardware setups, translating these predictions into pre-trained surrogate models capable of accurately identifying failure risks and rapidly testing new system hardening measures. In this presentation, we will showcase preliminary results in capturing system dynamics through our customizable library of PV hardware configurations. Additionally, we will highlight how these new tools build upon PVade's established wind load modeling capabilities and foster the development of advanced AI/ML surrogates for improving system robustness.
The Materials Dynamics area of leadership focuses on understanding process-structure-properties-performance (PSPP) relationships for the extreme conditions of dynamic loading. This research encompasses controlled synthesis of materials to meet dynamic performance requirements and entails computational coupling across length and time scales for three-dimensional microstructure modeling. For this leadership area, we define dynamic loading as strain rates ≥ 10 3 /s and often, high pressures. A key grand challenge of this area is to predict and measure the evolution of microstructural phases, defect structures, and electronic structure under dynamic conditions while also measuring local temperature to understand transition states. Solving this challenge will require agile, multi-dimensional data analysis and interpretation capability.
Under dynamic loading conditions and the associated extreme conditions many metals will undergo phase transformations. The change in crystal structure associated with solid–solid phase transformations can significantly alter the subsequent mechanical response of the material. For the interpretation of experiments involving dynamic loading it is beneficial to have a modeling framework that captures key features of the material response while remaining relatively simple. We introduce a candidate framework and apply it to the metal tin to highlight a range of behaviors that are captured by the model. We also discuss potential extensions to capture additional behaviors that could be important for certain materials and loading scenarios. The model is useful for analysis of results from dynamic experiments and offers a point of departure for more complex model formulations.
Owing to their ability to provide tunable mechanical responses, lattice materials are frequently studied to elucidate their response to static and dynamic loads. However, these roles are typically in opposition: static loads must be supported sufficiently far away from the onset of buckling or yielding, whereas dynamic loads are typically ameliorated by crushing of the lattice, which provides excellent energy-absorption due to the large plastic deformation accompanying densification. In contrast, this work considers the octet truss as an exemplar topology, in a structural role where it must simultaneously support static loads while enduring high-amplitude impulsive loads. This study focuses on the ability to withstand impulsive loads without yielding, an essential prerequisite to enduring dual loading. Computational studies using the ALE3D hydrocode were performed to examine the response of the octet truss under a short temporal width impulse shape associated with laser-driven shocks. A key finding was that covering the lattice with a solid face sheet and treating this face sheet thickness as a design variable allows the Taylor-like pulse to be attenuated prior to entering the weaker lattice, at the cost of added mass up front. Experimental validation was accomplished by laser-driven shock testing, using octet trusses printed out of Ti-5Al-5V-5Mo-3Cr. The results show that for a given quantity of mass, the attenuation is maximized when as much mass as possible is moved into the face sheet, leaving a more slender lattice structure. The effect of placing mass in the face sheet rather than lattice beams dominates the effect of relative density, to the point where a low-mass structure with most of the mass concentrated in the face sheet can outperform a high-mass structure with most of the mass in the lattice. Finally, by further understanding the propagation of short pulse width waves within under-dense structures, this study expand the domain of applicability of such structures, including lattice materials, to challenging dual-loading regimes spanning decades of strain rates.
Metal cutting is a highly dynamic process that generates continuously varying forces. Measurement of these forces is essential to characterizing a cutting process and to fully utilize the machine tool. A force dynamometer is often used to measure these varying forces; however, it is limited by the natural frequency of the sensor and can sometimes be hard to set up on a machine. Therefore, this study aims to estimate the dynamic component of the cutting force using an accelerometer placed directly below the cutting edge. The placement of the sensor helps achieving better signal to noise ratio (S/N). The cutting tool is modelled as a single degree of freedom (SDOF) system relative to the workpiece and dynamic loads are experimentally simulated on it. The measured acceleration is numerically integrated to obtain velocity and deflection, which along with the natural frequency (ω n ) and damping ratio (ζ), is used to predict the dynamic load using the system equation. The dynamic forces tested over a wide range of frequencies, show good agreement with the data from simultaneous dynamometer measurement and the force estimated using the proposed method. The study shows the feasibility of this method in a real cutting scenario and the capability to apply it to a multi DOF system. One major limitation is the inability to capture the static or quasi-static component of the cutting force.
PV panels are subjected to wind loads during normal outdoor operation, where th wind speed, wind direction, panel angle, and array layout play a large role in the overall loading magnitude. For floating PV systems, where panels are installed on floating rafts, these forces can lead to a dynamic displacement of the raft and mounted PV hardware. The Contractor and Participant will perform fluid-structure interaction simulations of this phenomenon for a variety of wind speeds, directions, and panel angles to characterize these forces and help design mooring/tethering lines to resist and anchor raft movement.
We report successful coupling of dynamic loading in a diamond anvil cell and stable laser heating, which enables compression rates up to 500 GPa/s along high-temperature isotherms. Dynamic loading in a diamond-anvil cell allows exploration of a wider range of pathways in the pressure-temperature space compared to conventional dynamic compression techniques. By x-ray diffraction, we are able to characterize and monitor the structural transitions with the appropriate time resolution i.e., millisecond timescales. Using this method, we investigate the γ − ε phase transition of iron under dynamic compression, reaching compression rates of hundreds of GPa/s and temperatures of 2000 K. Our results demonstrate a distinct response of the γ − ε and α − ε transitions to the high compression rates achieved, possibly due to the different transition mechanisms. These findings open up new avenues to study tailored dynamic compression pathways in the pressure-temperature space and highlight the potential of this platform to capture kinetic effects (over ms time scales) in a diamond anvil cell. Published by the American Physical Society 2024
Virtual-inertia and droop control methods are commonly used for grid-forming inverters. While the virtual inertia is used to emulate the equation of motion/frequency, if the inverter output voltage is emulated as in synchronous generators, then the method is known as the virtual synchronous generator. An inductive pulse-load, e.g., a relatively large induction motor, connection to a microgrid fed only by grid-forming inverters may lead to blackout due to high inrush currents. This article presents virtual reactance techniques to mitigate the inrush current effects and enhance the inverter’s robustness for the safe connection of inductive and dynamic loads. This article also compares the virtual inertia and droop control methods under switching inductive-dynamic loads while the proposed techniques are implemented. Experimental tests are performed considering the linear and nonlinear virtual reactance techniques, and the findings are discussed. The mitigation significantly suppresses the inrush currents while the inverters can perform a normal operation. Furthermore, the frequency and power response of the virtual inertia control with different inertia settings to a sudden change in the load is analyzed. The virtual reactance technique is tested in a laboratory-scale hardware setup of a 208V microgrid fed by 5kVA and 10kVA inverters, and the results are presented in this article.