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At least 19 records

Reliability Implications of Solder in Multiwire Modules under Dynamic Mechanical Loading

Two generations of multiwire modules were studied under dynamic mechanical loading (DML) with in-situ differential conductance (dG) and electroluminescence (EL) imaging. Energy-dispersive x-ray spectroscopy (EDS) was used to identity the solder alloys. The earlier generation module was found to use an In-based solder alloy, and the current generation a Bi-based alloy. The earlier generation module degraded significantly under DML with increasing resistance, while the current generation module did not demonstrate degradation under DML. Atomic force microscopy scratch testing was used to probe the wear resistance of each solder alloy. These results indicate that current multiwire designs may have higher mechanical durability than earlier generations.

atomic force microscopy↗

Reliability Implications of Solder in Multiwire Modules under Dynamic Mechanical Loading: Preprint

Two generations of multiwire modules were studied under dynamic mechanical loading (DML). The earlier generation module was found to use an In-based solder alloy, and the current generation a Bi-based alloy. The earlier generation module degraded significantly under DML with increasing resistance, while the state-of-the-art module did not demonstrate degradation under DML. The degradation in the earlier module was attributed to damage at the solder-gridline interfaces. Atomic force microscopy scratch testing estimated the wear resistance of each solder alloy to assess susceptibility to degradation. Bi-based alloys appear to be more wear resistant than In-based alloys, consistent with the DML results. These results indicate that current multiwire designs may have higher mechanical durability than earlier generations.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Rapid activation of non-oriented mechanophores via shock loading and spallation

Mechanophores (MPs), stimuli-responsive molecules that respond chromatically to mechanochemical reactions, are important for understanding the coupling between mechanics and chemistry as well as in engineering applications. However, the atomic-level understanding of their activation originates from gas phase studies or under simple linear elongation forces directly on molecules or polymer chains containing MPs. The effect of many-body distortions, pervasive in condensed-phase applications, is not understood. Therefore, we performed large-scale molecular dynamics (MD) simulations of a poly(methyl methacrylate)-spiropyran copolymer under dynamic mechanical loading and studied the activation of the MP under various conditions from dynamical compression to tension during unloading. Detailed analysis of the all-atom MD trajectories shows that the MP blocks experience significant many-body intramolecular distortion that can significantly decrease the activation barrier as compared with when deformation rates are slow relative to molecular relaxation time scales. Here we find that the reactivity of MPs under material compression states is governed by many-body effects of intramolecular torsions, whereas under tension, the reactions are governed by tensile stresses.

36 MATERIALS SCIENCE↗

Effects of particle size, shape and loading rate on the normal compaction of an advanced granular ceramic

Compaction behavior of granular materials is influenced by strain rate, particle size, and shape. In this report, boron carbide powders with different particle sizes under uni-axial strain conditions are studied using quasi-static compression, dynamic Kolsky bar experiments and normal plate impact. A rounded powder is compacted to investigate the effect of particle shape. The normal plate impact technique is an excellent tool in characterization of powder compaction behavior up to strain rates of ~10 5 s -1 . From our experiments, granular boron carbide shows a highly compressible behavior with significant volume compaction. Constitutive responses are obtained for four powders. Particle fracture is identified as key deformation mechanism. Dynamic loading introduces more particle fragmentation than quasi-static loading. Morphological characterization of particle shapes shows that the deformation from powder compaction alters the particle shape distribution, which is also rate-dependent. Particle size, shape and strain rate effects on the normal stress are discussed accordingly.

36 MATERIALS SCIENCE↗

Millions of Small Pressure Cycles Drive Damage in Cracked Solar Cells

Here, we applied time-varying air pressure to a PV module containing newly cracked cells. The test used a new dynamic mechanical acceleration (DMX) apparatus. We applied pressure cycles similar to natural, wind-driven cycles. Compared to standard dynamic mechanical load (DML) tests, we applied much lower pressure (10 Pa to 300 Pa RMS) and many more cycles (one million at each of four pressure levels). We present a case study on a single cell in a commercial module. We monitored electrical continuity loss across cracks using electroluminescence (EL) imaging. 10 Pa pressure cycles caused negligible change. 30 Pa pressure cycles caused permanent damage that continued worsening even after tens of thousands of cycles. After one million 30 Pa cycles, a series of 100 Pa cycles still caused new, permanent damage to existing cracks. 300 Pa cycles caused further worsening and introduced new cracks.

14 SOLAR ENERGY↗

Characterization of Interconnects

Combined-accelerated stress testing (C-AST) simultaneously combines stress factors of the natural environment (including UV radiation, temperature, humidity, electrical current, and external mechanical force) into a single test that requires fewer modules, fewer chambers, and makes it possible to discover weaknesses in new designs that are not known a-priori. C-AST reduces risk, accelerates time to market, and improves bankability by reducing costly overdesign using test levels not exceeding those seen in the natural environment. This project seeks to evaluate strengths and weaknesses of modern cell interconnect designs with combined-accelerated stress testing (C-AST) to screen multiple climates along with finite element and failure analysis to determine the potential for a 50-year life. Supporting this, we seek to develop methods of characterization to assess the degradation of interconnects, enable predictive rate models with material forensics and FEA and show C-AST's ability to find interconnect failures and benchmark it relative to other accelerated stress test methods like temperature cycling and cyclic dynamic mechanical loading. Examples of modern interconnect designs covered are Canadian Solar Hetero Technology ribbon enabling closer cell interconnections, SmartWire (eg. Meyer-Berger technology), and shingled cells with new interconnect materials.

C-AST↗

High-bandwidth Dynamic Load Emulation of Mechanical Systems using Electric Drives

Machine drives are versatile systems that can be programmed to emulate a variety of mechanical loads. In this paper, we walk through the modeling and control framework of a shaft-coupled dual-motor drive system that is programmed to emulate a fictitious mechanical system. We quantitatively evaluate the control performance of such a system and derive a theoretical limit that explains its inaccuracy at high operating frequencies. To overcome this problem, we propose an alternate control structure that achieves the same control objective at high frequencies as well. After suitable adjustments are made to the controller, we validate its performance using simulation results.

machine drives ,load emulation, speed-torque chara↗

Controlling dendrite propagation in solid-state batteries with engineered stress

Metal-dendrite penetration is a mode of electrolyte failure that threatens the viability of metal-anode-based solid-state batteries. Whether dendrites are driven by mechanical failure or electrochemical degradation of solid electrolytes remains an open question. If internal mechanical forces drive failure, superimposing a compressive load that counters internal stress may mitigate dendrite penetration. Here, we investigate this hypothesis by dynamically applying mechanical loads to growing dendrites in Li 6.6 La 3 Zr 1.6 Ta 0.4 O 12 solid electrolytes. Operando microscopy reveals marked deflection in the dendrite growth trajectory at the onset of compressive loading. For sufficient loading, this deflection averts cell failure. Using fracture mechanics, we quantify the impact of stack pressure and in-plane stresses on dendrite trajectory, chart the residual stresses required to prevent short-circuit failure, and propose design approaches to achieve such stresses. For the materials studied here, we show that dendrite propagation is dictated by electrolyte fracture, with electronic leakage playing a negligible role.

25 ENERGY STORAGE↗

A MEMS dynamic mechanical analyzer for in situ viscoelastic characterization of 3D printed nanostructures

Cellular metamaterial structures with sub-micron features have shown the ability to become excellent energy absorbing materials for impact mitigation due to the enhanced mechanical properties of materials at the nanoscale. However, in order to optimize the design of these energy absorbing metamaterial structures we need to be able to measure the dynamic properties of the sub-micron features such as storage and loss moduli and the loss factor. Therefore, at scale testing is required to capture the scale, temperature, and strain rate dependent material properties of these nanoscale materials. This study presents the design, fabrication, and calibration of a MEMS-based dynamic mechanical analyzer (DMA) that can be directly integrated with the two photon lithography (TPL) process commonly used to fabricate metamaterial structures with nanoscale features. The MEMS-based DMA consists of a chevron style thermal actuator used to generate a tensile load on the structure and two differential capacitive sensors on each side of the structure used to measure load and displacement. This design demonstrated 1.5 ± 0.75 nm displacement resolution and 104 ± 52 nN load resolution, respectively. Dynamic mechanical analysis was successfully conducted on a single nanowire feature printed between the load and displacement stages of the MEMS device with testing frequencies ranging between 0.01–10 Hz and testing temperatures ranging between 22 °C–47 °C. These initial tests on an exemplar TPL part demonstrate that the printed nanowire behaves as a viscoelastic material wherein the transition from glassy to viscous behavior has already set in at the room temperature.

42 ENGINEERING↗

Iodine capture with mechanically robust heat-treated Ag-Al-Si-O xerogel sorbents

Silver-loaded heat-treated aluminosilicate xerogels (Ag-HTX) were evaluated as sorbents for iodine [I2(g)] capture. The heat treatment step was performed to help increase the mechanical integrity of the gels. The synthesized xerogels were characterized using powder X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, transmission electron microscopy, Brunauer-Emmett-Teller analysis, gravimetric iodine loading, nanoindentation, and dynamic mechanical analysis. The structural and chemical analyses of Ag-HTX showed uniform distribution of Ag throughout the gel network after Ag-exchange. After I2(g) capture, the AgI crystallites were observed in the sorbent verifying chemisorption as the iodine capture mechanism. Iodine loading of this xerogel was 0.43 g g-1 at 150°C over 1 d and 0.52 g g-1 at 22°C over 33 d. The specific surface area of Ag-HTX was 202 m2 g-1 and decreased to 87 m2 g-1 after iodine loading. The hardness of the heat-treated xerogel was 160 times higher than heat-treated aerogel of the same composition. The heat-treatment process increased the modulus value to 40.77 MPa from 6.99 MPa of as-made xerogel, demonstrating the need for this added step in the synthesis process. These results show that Ag-HTX is a promising sorbent for I2(g) capture with good loading capacity and mechanical stability.

xerogels, aerogels, iodine capture, hardness testi↗

Bayesian blacksmithing: discovering thermomechanical properties and deformation mechanisms in high-entropy refractory alloys

Finding alloys with specific design properties is challenging due to the large number of possible compositions and the complex interactions between elements. This study introduces a multi-objective Bayesian optimization approach guiding molecular dynamics simulations for discovering high-performance refractory alloys with both targeted intrinsic static thermomechanical properties and also deformation mechanisms occurring during dynamic loading. The objective functions are aiming for excellent thermomechanical stability via a high bulk modulus, a low thermal expansion, a high heat capacity, and for a resilient deformation mechanism maximizing the retention of the BCC phase after shock loading. Contrasting two optimization procedures, we show that the Pareto-optimal solutions are confined to a small performance space when the property objectives display a cooperative relationship. Conversely, the Pareto front is much broader in the performance space when these properties have antagonistic relationships. Density functional theory simulations validate these findings and unveil underlying atomic-bond changes driving property improvements.

36 MATERIALS SCIENCE↗

High strain-rate compression behavior of polymeric rod and plate Kelvin lattice structures

The compressive high strain-rate behavior of polymeric Kelvin lattice structures with rod-based or plate-based unit cells was investigated through experimental techniques and finite element simulations. Polymeric lattice structures with 5x5x5 unit cell geometries were manufactured on the millimeter scale using vat polymerization additive manufacturing and tested at low (0.001/s) and high (1000/s) strain-rates. High strain-rate experiments were performed and validated for a viscoelastic split-Hopkinson (Kolsky) pressure bar system (SHPB) coupled with high-speed imaging and digital image correlation (DIC). Experimental results at both low and high strain-rates show the formation of a localized deformation band which was more prevalent in low relative density specimens and low strain-rate experiments. Strain-rate effects of lattice specimens strongly correlate with effects of the base polymer material; both bulk polymer and lattice specimen demonstrated strain-rate hardening, strain-rate stiffening, and decreased fracture strain under dynamic loading. Results show mechanical failure properties and energy absorption depended strongly on the relative density of the lattice specimen and exhibited distinct scaling between relative density and geometry type (rod, plate) and loading rate. High relative density plate-lattices demonstrated inferior mechanical properties to rod-lattices; however, there exists a critical relative density for a given mechanical property (17%- 28%) below which plate-lattices outperform rod-lattices of similar mass. As a result, high strain-rate explicit finite element simulations were performed and showed good agreement with the mechanical failure trends and deformation modes observed in the experiments.

36 MATERIALS SCIENCE↗

In-situ X-ray Evaluation of Traumatic Brain Injury Dynamic Impacts (Final Report)

The goal of this project was to create an in-situ model of traumatic brain injury that allows for analysis of chronic traumatic encephalopathy (CTE) development. CTE is a neurodegenerative disease that occurs as a result of traumatic brain injuries. The resulting neurodegeneration and atrophying of cortical brain tissue develop as tau proteins build-up around small blood vessels and at the base of cortical sulci. Aggregation of tau proteins results in blood vessel damage and neurological function loss, leading to cortical tissue atrophy. This occurs only at some neuronal junctions in the brain after trauma. It has been conjectured that the geometrical distribution of force along neurons is responsible for initiation of tau deposition. However, to assess the validity of this proposition, it is necessary to analyze the mechanical response under dynamic loading associated with brain trauma in-situ

42 ENGINEERING↗

Effect of Mechanical Deformation on the Dielectric Electric Field in Dynamic Umbilical Cables

Wave energy converter (WEC) systems have unique umbilical cable design requirements compared to conventional marine designs. Due to their dynamic nature, WEC umbilical cables are required to handle increased loads and larger motions over longer deployment scenarios. However, the life expectancy of dynamic umbilical cables is predominantly analyzed for mechanical fatigue, with little consideration given to the effect of mechanical stress on the response of the dielectric as it has been previously assumed that the non-polymeric components will fail prior to the polymeric components. In this work, we explore the effects of mechanical bending on the concentration of the electric field in the insulation of a conceptual three-core dynamic umbilical cable to determine the limiting requirements for life expectancy. A conceptual industrial schematic of a medium voltage dynamic umbilical cable was used as the basis for the WEC system under study. Simulations on the dynamic umbilical cable were performed using COMSOL Multiphysics®. Mechanical loads up to the calculated limit (2.64 m minimum bend radius or 388 kN transverse load) were applied to the dynamic umbilical in a step-wise fashion with one end of the umbilical cable fixed. One-way coupling in three-dimensions was conducted by first determining the engineering strains, then using the engineering strains as the initial condition for determination of the Green-Lagrange strains, and lastly calculating the electric field in the deformed dielectric. Based upon the input load, deformation of the dielectric at the minimum bend radius produced an increase in the electric field of more than 12% when compared to the undeformed umbilical cable, which may lead to dielectric breakdown of the insulation prior to mechanical failure of the umbilical cable.

Spencer, Mychal P.↗

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗

Field Validation of Dynamic Mechanical Torque Measurements for Geared Wind Turbines

Accurate knowledge of the mechanical loads of wind turbine gearboxes has become essential in modern, highly loaded gearbox designs, as maintaining or even improving gearbox reliability with increasing torque density demands is proving to be challenging. Unfortunately, the traditional method of measuring dynamic mechanical torque using strain gauges placed on the outer surface of a rotating shaft and transmitting the resulting signal is unsuitable for serial deployment due to technical and economic constraints. An alternative method based on fiber-optic strain sensors placed on the stationary outer surface of the gearbox ring gear has been proposed. Like shaft torsion, the radial deformation of the ring gear is proportionate to the rotor torque. Placing the sensors on a stationary component is a cost-effective alternative for serial implementation because the need for complex and expensive data transfer via wireless transmission or a slip ring is eliminated. In this paper, we present the results of an extensive field experiment conducted to evaluate the torque measurement accuracy of this novel sensing solution installed on the gearbox of a Gamesa G97 2-MW wind turbine at the National Renewable Energy Laboratory's Flatirons Campus. Torque measurements derived from fiber-optic strain sensors placed on the ring gear of the planetary stage are compared to conventional torque measurements from strain gauges placed on the main shaft. Two different torque estimation data processing methods were evaluated, with the method based on operational deflection shapes providing the most accurate results with an average normalized root mean square error below 0.7% for a load revolution distribution analysis. The effect of operating conditions on the torque estimate was also investigated, and the third planet-passing operational deflection shape was found to be the least sensitive to nontorque load-related effects. The fiber-optic strain sensors' successful operation during the complete test campaign has demonstrated a robust and accurate solution for fleet-wide enhanced gearbox remaining useful life estimation.

17 WIND ENERGY↗

Modeling and Detection of Future Cyber-Enabled DSM Data Attacks

Demand-Side Management (DSM) is an essential tool to ensure power system reliability and stability. In future smart grids, certain portions of a customer’s load usage could be under the automatic control of a cyber-enabled DSM program, which selectively schedules loads as a function of electricity prices to improve power balance and grid stability. In this scenario, the security of DSM cyberinfrastructure will be critical as advanced metering infrastructure and communication systems are susceptible to cyber-attacks. Such attacks, in the form of false data injections, can manipulate customer load profiles and cause metering chaos and energy losses in the grid. The feedback mechanism between load management on the consumer side and dynamic price schemes employed by independent system operators can further exacerbate attacks. To study how this feedback mechanism may worsen attacks in future cyber-enabled DSM programs, we propose a novel mathematical framework for (i) modeling the nonlinear relationship between load management and real-time pricing, (ii) simulating residential load data and prices, (iii) creating cyber-attacks, and (iv) detecting said attacks. In this framework, we first develop time-series forecasts to model load demand and use them as inputs to an elasticity model for the price-demand relationship in the DSM loop. This work then investigates the behavior of such a feedback loop under intentional cyber-attacks. We simulate and examine load-price data under different DSM-participation levels with three types of random additive attacks: ramp, sudden, and point attacks. We conduct two investigations for the detection of DSM attacks. The first studies a supervised learning approach, with various classification models, and the second studies the performance of parametric and nonparametric change point detectors. Results conclude that higher amounts of DSM participation can exacerbate ramp and sudden attacks leading to better detection of such attacks, especially with supervised learning classifiers. We also find that nonparametric detection outperforms parametric for smaller user pools, and random point attacks are the hardest to detect with any method.

97 MATHEMATICS AND COMPUTING↗