Results for “accelerated lifetime testing” — Page 7

NASA NTRS1981

Ion beam deposited protective films

Sputter deposition of adherent thin films on complex geometric surfaces by ion beam sources is examined in order to evaluate three different types of protective coatings for die materials. In the first experiment, a 30 cm diameter argon ion source was used to sputter deposit adherent metallic films up to eight microns thick on H-13 steel, and a thermal fatigue test specimen sputter deposited with metallic coatings one micron thick was immersed in liquid aluminum and cooled by water for 15,000 cycles to simulate operational environments. Results show that these materials do protect the steel by reducing thermal fatigue and thereby increasing die lifetime. The second experiment generated diamond-like carbon films using a dual beam ion source system that directed an eight cm argon ion source beam at the substrates. These films are still in the process of being evaluated for crystallinity, hardness and infrared absorption. The third experiment coated a fiber glass beam shield incorporated in the eight-cm diameter mercury ion thruster with molybdenum to ensure proper electrical and thermal properties. The coating maintained its integrity even under acceleration tests.

Mirtich, M. J.↗

DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler [National Renewable Energy Lab. (NR↗

DOE OSTI2024

Rapid assessment of the creep rupture life of metals: A model enabling experimental design

Prediction of the creep rupture life of engineering metals is critical for qualification and design of new materials. The use of long-term creep tests and the need to quantify the performance variability in a priori similar systems hinder the rapid creep assessment of a given material. Therefore, it is essential to develop methods that can extrapolate the long-term performance of alloys and the associated variability from short-term experiments. To this end, this study introduces a new model which enables the estimation of the rupture life of a material for a given stress and temperature. This model relies on two components. First, a new relation for the minimum creep rate (MCR) of materials is introduced. It includes a stress dependent stress exponent allowing the model to capture the variation of MCR across a wide range of temperatures and stresses. Second, employing the Monkman-Grant (MG) law, we establish a relation between stress, temperature and creep rupture life. Together, these two elements yield a new closed-form mathematical expression for the Larson Miller parameter as a function of stress and temperature. This expression captures the creep rupture time for many metals (Gr91, Copper, Gr122 and 347H) and compares favorably with alternate empirical approaches. The model is then used to assess the minimum duration of creep rates necessary to qualify the material up to 100000h. Furthermore, it is found that depending on the material system, creep tests as few as five limited to 5000 h for steels (Gr91, Gr122, 347H) and 100 h for copper are sufficient to model creep lifetimes. Finally, using a Bayesian inference-based approach to calibrate the model, we demonstrate that variability in rupture life can be captured via the quantification of the uncertainty in the model parameters and extrapolated from a limited number of short to moderately short creep tests; thereby paving the way for accelerated creep testing.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Diagnostics, Prognostics, and Optimization for Lithium-Ion Battery Systems

Health management of lithium-ion battery systems presents a host of challenges due to their complex physics, large numbers of components, and a wide variety of degradation behaviors across different battery types. Dr. Paul Gasper will present on research from the Electrochemical Energy Storage Group on Lithium-ion battery diagnostics, prognostics, and optimization. Diagnostics research, including state-estimation via machine-learning from electrochemical impedance spectroscopy and DC pulses as well as continuous state-estimation via Kalman filters, will highlight the ongoing challenges for accurately measuring the state of batteries without performing time-consuming characterization tests. NLR's industry-recognized battery prognostics work, which predicts real-world battery degradation by identifying degradation rate models from accelerated aging data using statistical modeling and machine-learning, will be used to demonstrate the critical impact of battery controls, thermal management, and operating strategy on durability and lifetime. Finally, the use of prognostic models for financial or lifetime optimization will be discussed.

25 ENERGY STORAGE↗

DOE OSTI2024

Bayesian optimization scheme for the design of a nanofibrous high power target

High Power Targetry (HPT) R&D is critical in the context of increasing beam intensity and energy for next generation accelerators. Many target concepts and novel materials are being developed and tested for their ability to withstand extreme beam environments; the HPT R&D Group at Fermilab is developing an electrospun nanofiber material for this purpose. The performance of these nanofiber targets is sensitive to their construction parameters, such as the packing density of the fibers. Lowering the density improves the survival of the target, but reduces the secondary particle yield. Optimizing the lifetime and production efficiency of the target poses an interesting design problem, and in this paper we study the applicability of Bayesian optimization to its solution. We first describe how to encode the nanofiber target design problem as the optimization of an objective function, and how to evaluate that function with computer simulations. We then explain the optimization loop setup. Thereafter, we present the optimal design parameters suggested by the algorithm, and close with discussions of limitations and future refinements.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Bayesian Optimization Scheme for the Design of a Nanofibrous High Power Target

High Power Targetry (HPT) R\&D is critical in the context of increasing beam intensity and energy for next generation accelerators. Many target concepts and novel materials are being developed and tested for their ability to withstand extreme beam environments; the HPT R\&D Group at Fermilab is developing an electrospun nanofiber material for this purpose. The performance of these nanofiber targets is sensitive to their construction parameters, such as the packing density of the fibers. Lowering the density improves the survival of the target, but reduces the secondary particle yield. Optimizing the lifetime and production efficiency of the target poses an interesting design problem, and in this paper we study the applicability of Bayesian optimization to its solution. We first describe how to encode the nanofiber target design problem as the optimization of an objective function, and how to evaluate that function with computer simulations. We then explain the optimization loop setup. Thereafter, we present the optimal design parameters suggested by the algorithm, and close with discussions of limitations and future refinements.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Performance and Durability of Heavy-Duty Fuel Cell Systems with an Advanced Ordered Intermetallic ORR Alloy Catalyst and Novel Support

Ordered PtCo intermetallic (OIM) catalyst (L1 0 -PtCo/C) is a promising candidate as the oxygen reduction reaction (ORR) catalyst in hybrid fuel cell systems (FCS) for class-8 heavy duty (HD) trucks. Compared to a baseline annealed Pt on high surface area carbon (a-Pt/HSC) catalyst, its mass activity (MA) is 71% higher initially and 144% higher after 90,000 potential cycles in an accelerated stress test (AST). Analysis of the AST data indicates that the ORR kinetic constants do not change with aging and the degradation in the OIM catalyst activity is linearly proportional to the loss in the electrochemically active surface area (ECSA). Several operational strategies are investigated to mitigate catalyst degradation and achieve 25,000-h electrode lifetime and 2.5 kW g −1 Pt utilization on a HD truck duty cycle including load sharing with the hybrid battery, regulating the radiator fan power to maintain the coolant temperature close to 60 °C, clipping the maximum cell voltage below 850 mV, limiting the ECSA loss to 55%, and oversizing the active area of the membrane electrode assemblies by 20%. Drive cycle simulations indicate that the lifetime average voltage degradation rate is about 1.8 μV h −1 and the integrated stack and FCS drive cycle efficiencies decrease by 3.5 to 3.9%.

25 ENERGY STORAGE↗

DOE OSTI2026

Challenges, Technological Pathways and Trade-Offs of Perovskite Solar Modules for Long-Term Operation

Perovskite solar modules (PSMs) have emerged as a promising photovoltaic technology due to their high efficiency, low fabrication cost and compatibility with lightweight and flexible applications. However, ensuring long-term reliable performance under real-world conditions remains a critical barrier to commercialization. PSMs degrade through mechanisms that differ substantially from those affecting established technologies such as silicon, particularly under environmental stressors like ultraviolet light, oxygen, temperature cycling and reverse bias. Here we provide an analysis of the degradation pathways specific to perovskite modules and discuss why standard accelerated tests often fail to predict outdoor performance. We conceptualize challenges across material, device and module levels and evaluate strategies to mitigate ion migration, interfacial breakdown and encapsulation failure. By highlighting the need for realistic testing protocols and durable materials, we propose a framework highlighting key challenges, technological pathways and the trade-offs required to extend perovskite module lifetimes towards long-term operation, aiming to guide the development of PSMs capable of a 30-year operational lifetime.

14 SOLAR ENERGY↗

NASA NTRS1981

Extended Performance 8-cm Mercury Ion Thruster

A slightly modified 8-cm Hg ion thruster demonstrated significant increase in performance. Thrust was increased by almost a factor of five over that of the baseline thruster. Thruster operation with various three grid ion optics configurations; thruster performance as a function of accelerator grid open area, cathode baffle, and cathode orifice size; and a life test of 614 hours at a beam current of 250 mA (17.5 mN thrust) are discussed. Highest thruster efficiency was obtained with the smallest open area accelerator grid. The benefits in efficiency from the low neutral loss grids were mitigated, however, by the limitation such grids place on attainable ion beam current densities. The thruster components suffered negligible weight losses during a life test, which indicated that operation of the 8-cm thruster at extended levels of thrust and power is possible with no significant loss of lifetime.

Mantenieks, M. A.↗

DOE OSTI2024

Effects of electron beam irradiation on CrMnV and CrMnTiV high entropy alloys: Nano-mechanical, structural, and thermodynamic perspectives

Beam exit windows are crucial components of any particle accelerator as they provide an interface between the beamline vacuum and target material at atmospheric media. For high beam power machines, special materials and designs are required to withstand high radiation and mechanical loads, while minimizing energy loss during transition and maximizing window lifetime. This research investigates the impact of electron beam exposure to bulk CrMnV and CrMnTiV high entropy alloys (HEAs) with the primary goal of identifying suitable candidate materials for the design of robust and durable exit window settings. The selection criteria include intrinsic characteristics, power dissipation, and mechanical responses. According to the thermodynamic calculations, both equiatomic CrMnV and the addition of 7% of Ti with equiatomic CrMnV yield solid-solutions phases. The structural and mechanical properties of CrMnV and CrMnTiV samples were tested using field emission scanning electron microscopy, atomic force microscopy, scanning electron microcopy with energy dispersive x-ray spectroscopy, x-ray diffraction, and nanoindentation before and after exposure to a dose of ~66 kGy from a 10 MeV e-beam accelerator. Despite exhibiting beam transmission characteristics comparable to Cr and V, the indentation hardness of HEAs exceeded that of the Cr and V samples by five to six times. The examination of the CrMnTiV irradiated samples revealed organized deformation patterns depicting new features, which we suspect twinning and twin boundaries due to the addition of Ti to CrMnV. Ti, a hexagonal-close-packed crystal structure, is commonly known for deformation twinning behavior.

36 MATERIALS SCIENCE↗

NASA NTRS1997

Multi-Billion Shot, High-Fluence Exposure of Cr(4+): YAG Passive Q-Switch

NASA's Goddard Space Flight Center is developing the Geoscience Laser Altimeter System (GLAS) employing a diode pumped, Q-Switched, ND:YAG laser operating at 40 Hz repetition rate. To meet the five-year mission lifetime goal, a single transmitter would accumulate over 6.3 billion shots. Cr(4+):YAG is a promising candidate material for passively Q-switching the laser. Historically, the performance of saturable absorbers has degraded over long-duration usage. To measure the multi-billion shot performance of Cr(4+):YAG, a passively Q-switched GLAS-like oscillator was tested at an accelerated repetition rate of 500 Hz. The intracavity fluence was calculated to be approximately 2.5 J/cm(exp 2). The laser was monitored autonomously for 165 days. There was no evidence of change in the material optical properties during the 7.2 billion shot test.. All observed changes in laser operation could be attributed to pump laser diode aging. This is the first demonstration of multi-billion shot exposure testing of Cr(4+):YAG in this pulse energy regime

Stephen, Mark A.↗

NASA NTRS2015

Initial Thrust Measurements of Marshall's Ion-ioN Thruster

Electronegative ion thrusters are a variation of traditional gridded ion thruster technology differentiated by the production and acceleration of both positive and negative ions. Benefits of electronegative ion thrusters include the elimination of lifetime-limiting cathodes from the thruster architecture and the ability to generate appreciable thrust from both charge species. While much progress has been made in the development of electronegative ion thruster technology, direct thrust measurements are required to unambiguously demonstrate the efficacy of the concept and support continued development. In the present work, direct thrust measurements of the thrust produced by the MINT (Marshall's Ion-ioN Thruster) are performed using an inverted-pendulum thrust stand in the High-Power Electric Propulsion Laboratory's Vacuum Test Facility-1 at the Georgia Institute of Technology with operating pressures ranging from 4.8 x 10(exp -5) and 5.7 x 10(exp -5) torr. Thrust is recorded while operating with a propellant volumetric mixture ratio of 5:1 argon to nitrogen with total volumetric flow rates of 6, 12, and 24 sccm (0.17, 0.34, and 0.68 mg/s). Plasma is generated using a helical antenna at 13.56 MHz and radio frequency (RF) power levels of 150 and 350 W. The acceleration grid assembly is operated using both sinusoidal and square waveform biases of +/-350 V at frequencies of 4, 10, 25, 125, and 225 kHz. Thrust is recorded for two separate thruster configurations: with and without the magnetic filter. No thrust is discernable during thruster operation without the magnetic filter for any volumetric flow rate, RF forward Power level, or acceleration grid biasing scheme. For the full thruster configuration, with the magnetic filter installed, a brief burst of thrust of approximately 3.75 mN +/- 3 mN of error is observed at the start of grid operation for a volumetric flow rate of 24 sccm at 350 W RF power using a sinusoidal waveform grid bias at 125 kHz and +/- 350 V. Similar bursts in thrust are observed using a square waveform grid bias at 10 kHz and +/- 350 V for volumetric flow rates of 6, 10, and 12 sccm at 150, 350, and 350 W respectively. The only operating condition that exhibits repeated thrust spikes throughout thruster operation is the 24 sccm condition with a 5:1 mixture ratio at 150 W RF power using the 10 kHz square waveform acceleration grid bias. Thrust spikes for this condition measure 3 mN with an error of +/- 2.5 mN. There are no operating conditions tested that show continuous thrust production.

Caruso, Natalie R. S.↗

NASA NTRS1973

Correlation of ion and beam current densities in Kaufman thrusters.

In the absence of direct impingement erosion, electrostatic thruster accelerator grid lifetime is defined by the charge exchange erosion that occurs at peak values of the ion beam current density. In order to maximize the thrust from an engine with a specified grid lifetime, the ion beam current density profile should therefore be as flat as possible. Knauer (1970) has suggested this can be achieved by establishing a radial plasma uniformity within the thruster discharge chamber; his tests with the radial field thruster provide an example of uniform plasma properties within the chamber and a flat ion beam profile occurring together. It is shown that, in particular, the ion density profile within the chamber determines the beam current density profile, and that a uniform ion density profile at the screen grid end of the discharge chamber should lead to a flat beam current density profile.

Wilbur, P. J.↗

NASA NTRSDate not supplied

Martian Dust Abrasion Damage on Solar Arrays: HALT Experimental Investigation and Opportunity Rover Performance Analysis

We explored the utility of ground-based highly accelerated life testing (HALT) on epitaxial lift-off (ELO) triple-junction coverglass interconnected cells (CICs) after exposure to simulated Martian dust storms. Dust storm impingement was replicated by sandblasting CICs with Mars dust simulant replicating conditions similar to the weather conditions reported by the Viking landers. We observed that even in cases when there are no observable open circuit voltage (VOC) losses, the minority carrier lifetime is reduced. Short circuit current (JSC) losses can be recovered upon cleaning, suggesting JSC losses are not linked to permanent damage, like cell cracking. This suggests a permanent degradation could be determined by quantifying the difference between recoverable and non-recoverable power loss. We mined field data from the Mars Exploration Rover, Opportunity and extracted a degradation rate to compare to our experimental data. We found exceptional agreement between 4.9 Martian years of mined field data (9.4%) and the irreversible damage observed in our HALT experiment (9.7%). We demonstrate that the laboratory method for exposing CICs to Martian dust storm conditions well represents the physical reality of long duration CIC operation on Mars.

Lyndsey McMillon-Brown↗

DOE OSTI2026

How Selective Transport Layer Improves Efficiency and Durability of Proton Exchange Membrane Fuel Cells

In any electrochemical device, the separator or membrane allows specific ions to transport but blocks electrons and other chemical species, enabling the electrochemical energy to be harvested. However, small amounts of undesired species are known to permeate through the membrane, reducing overall system efficiency and lifetime. An emerging concept called the “Selective Transport Layer” preferentially allows only protons to pass through but reduces the permeance of other species by a meaningful degree. Here, in this study, we demonstrate that a 60 nm thick graphene oxide composite layer can be very effective in reducing gas and ion permeation, even for a gas as small as H 2 , while not noticeably increasing proton transport resistance. In electrode and membrane accelerated stability tests, we show that both electrode and membrane durability are improved by a factor of two. Microscopy and mathematic simulations confirm that the graphene oxide composite is effective in blocking transport of dissolved Pt 2+ . The improved durability and reduced H 2 fuel crossover are expected to substantially reduce initial and operating costs of the fuel cell system. How this technology may affect other membrane-based electrochemical devices is also discussed.

Ngo, Phuong Quynh [General Motors, Pontiac, MI (Un↗

NASA NTRSDate not supplied

A Dynamic Testing Approach for Particulate Erosion–Corrosion for Gas Turbine Coatings

Particle interactions in gas turbine engines can be multicomponent, complex phenomena leading to the degradation of thermal (TBCs) and environmental barrier coatings (EBCs) meant to protect engine components. Ingestion of particles into the engine can lead to recession of coatings due to particle erosion. Similarly, these same particles can become molten, adhere to coatings and result in thermochemical corrosion of coating materials. Particle erosion testing is often carried out where the particles are injected into a gas stream, accelerated within a nozzle, and impinge on sample. Conversely, most molten particle corrosion testing is often done in static laboratory furnaces, which does not capture the dynamic nature of deposition in application. Nevertheless, these damage mechanisms are often tested separately and no single standard exists to test both erosive and corrosive particle interactions with coating materials under relevant operating conditions for gas turbine engines. Understanding the synergies of particle interactions in engines is crucial in determining operating lifetimes of potential coating materials. Such considerations emphasize the need for realistic approaches in standardizing particle interaction testing in combustion environments. The current study outlines initial efforts at NASA Glenn’s Erosion Burner Rig Facility in improving dynamic erosion/corrosion testing methods by assessing the durability of state-of-the-art (SOA) TBC material 7 wt.% yttria stabilized zirconia (7YSZ) as a function of particle deposition rate, burner temperature, and particle size. Calibration data to determine particle deposition rate will be presented, and mass and optical profilometry measurements were utilized to estimate mass/volume loss versus deposition per increment of particulate used over time. Electron microscopy analyses were then carried out to assess coating damage after testing.

TBC↗

NASA NTRSDate not supplied

A Dynamic Testing Approach for Particulate Erosion–Corrosion for Gas Turbine Coatings

Particle interactions in gas turbine engines can be multicomponent, complex phenomena leading to the degradation of thermal (TBCs) and environmental barrier coatings (EBCs) meant to protect engine components. Ingestion of particles into the engine can lead to recession of coatings due to particle erosion. Similarly, these same particles can become molten, adhere to coatings and result in thermochemical corrosion of coating materials. Particle erosion testing is often carried out where the particles are injected into a gas stream, accelerated within a nozzle, and impinge on sample. Conversely, most molten particle corrosion testing is often done in static laboratory furnaces, which does not capture the dynamic nature of deposition in application. Nevertheless, these damage mechanisms are often tested separately and no single standard exists to test both erosive and corrosive particle interactions with coating materials under relevant operating conditions for gas turbine engines. Understanding the synergies of particle interactions in engines is crucial in determining operating lifetimes of potential coating materials. Such considerations emphasize the need for realistic approaches in standardizing particle interaction testing in combustion environments. The current study outlines initial efforts at NASA Glenn’s Erosion Burner Rig Facility in improving dynamic erosion/corrosion testing methods by assessing the durability of state-of-the-art (SOA) TBC material 7 wt.% yttria stabilized zirconia (7YSZ) as a function of particle deposition rate, burner temperature, and particle size. Calibration data to determine particle deposition rate will be presented, and mass and optical profilometry measurements were utilized to estimate mass/volume loss versus deposition per increment of particulate used over time. Electron microscopy analyses were then carried out to assess coating damage after testing.

TBC↗

NASA NTRSDate not supplied

A Dynamic Testing Approach for Particulate Erosion–Corrosion for Gas Turbine Coatings

Particle interactions in gas turbine engines can be multicomponent, complex phenomena leading to the degradation of thermal (TBCs) and environmental barrier coatings (EBCs) meant to protect engine components. Ingestion of particles into the engine can lead to recession of coatings due to particle erosion. Similarly, these same particles can become molten, adhere to coatings and result in thermochemical corrosion of coating materials. Particle erosion testing is often carried out where the particles are injected into a gas stream, accelerated within a nozzle, and impinge on sample. Conversely, most molten particle corrosion testing is often done in static laboratory furnaces, which does not capture the dynamic nature of deposition in application. Nevertheless, these damage mechanisms are often tested separately and no single standard exists to test both erosive and corrosive particle interactions with coating materials under relevant operating conditions for gas turbine engines. Understanding the synergies of particle interactions in engines is crucial in determining operating lifetimes of potential coating materials. Such considerations emphasize the need for realistic approaches in standardizing particle interaction testing in combustion environments. The current study outlines initial efforts at NASA Glenn’s Erosion Burner Rig Facility in improving dynamic erosion/corrosion testing methods by assessing the durability of state-of-the-art (SOA) TBC material 7 wt.% yttria stabilized zirconia (7YSZ) as a function of particle deposition rate, burner temperature, and particle size. Calibration data to determine particle deposition rate will be presented, and mass and optical profilometry measurements were utilized to estimate mass/volume loss versus deposition per increment of particulate used over time. Electron microscopy analyses were then carried out to assess coating damage after testing.

burner rig↗