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At least 937 records · Page 52

A review of fracture mechanics life technology

Lifetime prediction technology for structural components subjected to cyclic loads is examined. The central objectives of the project are: (1) to report the current state of the art, and (2) recommend future development of fracture mechanics-based analytical tools for modeling subcritical fatigue crack growth in structures. Of special interest is the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. The authors conducted a survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

Besuner, P. M.↗

An update on the life analysis of spur gears

An analytical method for predicting surface fatigue life of gears was presented. General statistical methods were outlined, showing the application of the general methods to a simple gear mesh. Experimentally determined values for constants in the life equation were given. Comparison of the life theory with test results and AGMA standards was made. Gear geometry pertinent to life calculations was reviewed.

Coy, J. J.↗

Strainrange partitioning behavior of the nickel-base superalloys, Rene' 80 and in 100

A study was made to assess the ability of the method of Strainrange Partitioning (SRP) to both correlate and predict high-temperature, low cycle fatigue lives of nickel base superalloys for gas turbine applications. The partitioned strainrange versus life relationships for uncoated Rene' 80 and cast IN 100 were also determined from the ductility normalized-Strainrange Partitioning equations. These were used to predict the cyclic lives of the baseline tests. The life predictability of the method was verified for cast IN 100 by applying the baseline results to the cyclic life prediction of a series of complex strain cycling tests with multiple hold periods at constant strain. It was concluded that the method of SRP can correlate and predict the cyclic lives of laboratory specimens of the nickel base superalloys evaluated in this program.

Halford, G. R.↗

Statistical Distribution of Gear Surface Fatigue Lives at High Reliability

The reliability of gears is important for a wide variety of applications, and the gearing community has a desire for better prediction of fatigue life at very high reliability. To improve predictions, a set of 950 NASA-conducted gear surface fatigue test results were gathered, pooled together using the general standardized Weibull variate, and then fit to a Weibull three-parameter distribution. An iterative fitting method was developed and then applied to the gear fatigue data to determine the values of the distribution parameters. Additional analyses were done using bearing and gear data that demonstrate a trend of increasing minimum life coefficient as correlated to the timeframe of the fatigue testing, and material cleanliness is proposed as a primary explanation for such correlation. It is noted that this observed trend supports published findings from analytical modeling and experimental studies that improvements to material cleanliness improves minimum fatigue life. Further use and study of the three-parameter Weibull distribution is recommended as a tool to quantify fatigue life most accurately in the high reliability regime.

gear↗

Modeling growth of fatigue cracks which originate at rivet holes

When a structural component is subjected to repeated stress cycles, it can fail at stresses which are well below the tensile strength of the material. The processes leading to this failure are termed fatigue. Instances of fatigue failure in aircraft have become an increasing concern. The crack leading to failure often originate at rivet holes and then grow in response to stress cycles which occur during the operation of the aircraft. A necessary step to preventing failures in todays fleet of aging aircraft is to increase the frequency and quality of inspections; steps were already taken in this direction. There is also a need for modeling of fatigue crack growth in the aircraft structures so that improvements in design can be established and predictions of the life of the components can be made. The purpose is to provide a method to accurately predict the growth of fatigue cracks and to use this method to make predictions about the life of aircraft structural components. The method relies on the formulation and numerical solution of a singular integral equation(s) for an arbitrarily shaped crack(s) which propagate in response to the applied loading. Of special interest to the aging aircraft studies are cracks which originate at circular holes (i.e., rivet holes), but other crack geometries can be treated equally as well.

Mear, Mark E.↗

Real-Time Aircraft Engine-Life Monitoring

This project developed an inservice life-monitoring system capable of predicting the remaining component and system life of aircraft engines. The embedded system provides real-time, inflight monitoring of the engine's thrust, exhaust gas temperature, efficiency, and the speed and time of operation. Based upon this data, the life-estimation algorithm calculates the remaining life of the engine components and uses this data to predict the remaining life of the engine. The calculations are based on the statistical life distribution of the engine components and their relationship to load, speed, temperature, and time.

Klein, Richard↗

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗

Predictive analysis of metal fatigue in the high cyclic life range

This report summarizes various aspects of predictive approaches in high cycle fatigue, hcf. The distinction between hcf and low cycle fatigue, lcf, is discussed in relation to the transition life and strainrange, and curves are presented to establish regions wherein each range predominates depending on the properties of any material of interest. The role of loading order on hcf in cumulative damage analysis is also discussed, together with mean stress effects and their relaxation. Also briefly discussed are high temperature fatigue and ultra-high cycle fatigue.

Manson, S. S.↗

Multifunctional Fiber-Reinforced Polymer Composites for Damage Detection and Memory

Self-structural health monitoring (SHM) functionalities for fiber-reinforced polymer composites have become highly sought after to ensure the structural safety of newly advancing components in the automotive, civil, mechanical, and aerospace industries. This paper introduces a self-damage detection and memory (SDDM) hybrid composite material, where the structural carbon fiber tow is transformed into a piezoresistive sensor network, and the structural glass fiber operates as electrical insulation. In this study, SDDM specimens were fabricated, and tensile and impact tests were performed. The tensile tests of SDDM specimens find two distinct loading peaks: first where the carbon fiber fails, and second where the glass fiber fails. A linear correlation was observed between the carbon fiber resistance and composite strain up to a threshold, beyond which a sharp nonlinear increase in resistance occurred. The resistance then approached infinity, coinciding with the first loading peak and failure of the carbon fiber elements. This demonstrates the potential for a damage early warning threshold. Additionally, the effect of stitching the sensor tow in a zig-zag pattern over a large area was investigated using tailored fiber placement (TFP) of 1-loop, 3-loop, and 5-loop specimens. Tensile testing found that increasing the number of loops improved the sensor’s accuracy for strain sensing. Furthermore, impact tests were conducted, and as the impact energy progressively increased, the sensor resistance permanently increased. This illustrates a capability for self-memory of microdamage throughout the life cycle of the structure, potentially useful for predicting the remaining life of the composite.

Demo, Luke B. (ORCID:0000000208806522)↗

A prediction model of the depth-of-discharge effect on the cycle life of a storage cell

Cycle life requirements are very high for batteries used in aerospace applications in low Earth orbit. The data base required to establish confidence in a particular cell design is thus both extensive and expensive. Reliable accelerated cycle life testing and performance decay modeling represent attractive alternatives to real-time tests of cycle life. In light of certain long-term cycle life test results, this paper examines a very simple performance decay model developed earlier. Application of that model to available data demonstrates a rigid relationship between a battery's expected cycle life and the depth of discharge of cycling. Further, modeling analysis of the data suggests that a significantly improved cycle life can be obtained with advanced components, materials, and designs; and that cycle life can be reliably predicted from the results of accelerated testing.

Thaller, Lawrence H.↗

A prediction model of the depth-of-discharge effect on the cycle life of a storge cell

Cycle life requirements are very high for batteries used in aerospace applications in low earth orbit. The data base required to establish confidence in a particular cell design is thus both extensive and expensive. Reliable accelerated cycle life testing and performance decay modeling represent attractive alternatives to real-time tests of cycle life. In light of certain long-term cycle life test results, this paper examines a very simple performance decay model developed earlier. Application of that model to available data demonstrates a rigid relationship between a battery's expected cycle life and the depth of discharge of cycling. Further, modeling analysis of the data suggests that a significantly improved cycle life can be obtained with advanced components, materials, and designs; and that cycle life can be reliably predicted from the results of accelerated testing.

Thaller, Lawrence H.↗

Diffusional transport and predicting oxidative failure during cyclic oxidation of beta-NiAl alloys

Nickel aluminides (NiAl) containing 40-50 at. percent Al and up to 0.1 at. percent Zr have been studied following cyclic oxidation at 1200, 1300, 1350 and 1400 C. The selective oxidation of aluminum resulted in the formation of protective Al2O3 scales on each alloy composition at each temperature. However, repeated cycling eventually resulted in the gradual formation of less protective NiAl2O4. The appearance of the NiAl2O4, signaling the end of the protective scale-forming capability of the alloy, was related to the presence of gamma-prime-(Ni3Al) which formed as a result of the loss of aluminum from the sample. A simple methodology is presented to predict the protective life of beta-NiAl alloys. This method predicts the oxidative lifetime due to aluminum depletion when the aluminum concentration decreases to a critical concentration. The time interval preceding NiAl2O4 formation (i.e., the lifetime based on protective Al2O3 formation) and predicted lifetimes are compared and discussed. Use of the method to predict the maximum use temperature for NiAl-Zr alloys is also discussed.

Nesbitt, J. A.↗

Test plan. GCPS task 7, subtask 7.1: IHM development

The overall objective of Task 7 is to identify cost-effective life cycle integrated health management (IHM) approaches for a reusable launch vehicle's primary structure. Acceptable IHM approaches must: eliminate and accommodate faults through robust designs, identify optimum inspection/maintenance periods, automate ground and on-board test and check-out, and accommodate and detect structural faults by providing wide and localized area sensor and test coverage as required. These requirements are elements of our targeted primary structure low cost operations approach using airline-like maintenance by exception philosophies. This development plan will follow an evolutionary path paving the way to the ultimate development of flight-quality production, operations, and vehicle systems. This effort will be focused on maturing the recommended sensor technologies required for localized and wide area health monitoring to a technology readiness level (TRL) of 6 and to establish flight ready system design requirements. The following is a brief list of IHM program objectives: design out faults by analyzing material properties, structural geometry, and load and environment variables and identify failure modes and damage tolerance requirements; design in system robustness while meeting performance objectives (weight limitations) of the reusable launch vehicle primary structure; establish structural integrity margins to preclude the need for test and checkout and predict optimum inspection/maintenance periods through life prediction analysis; identify optimum fault protection system concept definitions combining system robustness and integrity margins established above with cost effective health monitoring technologies; and use coupons, panels, and integrated full scale primary structure test articles to identify, evaluate, and characterize the preferred NDE/NDI/IHM sensor technologies that will be a part of the fault protection system.

Greenberg, H. S.↗

University of Miami G-band Vapor Radiometer Calibration (UMGVR_CAL) Field Campaign Report

Cold-air outbreak (CAO) clouds in the Arctic are commonly mixed-phase (MP); however, the partitioning of the amount of ice and water in CAO clouds and precipitation is not always well observed. Understanding how cloud phases partition as a function of cloud life cycle is important for predicting snowfall rates, convective life cycle, and intensity at weather timescales. The partitioning into liquid versus ice also has radiative impacts that are consequential for climate. These concerns motivated the incorporation of an airborne G-band vapor radiometer (GVR) into an National Science Foundation-supported aircraft campaign named the Cold Air outbreak Experiment in the Sub-Arctic Region (CAESAR). The GVR is an upward-pointing passive microwave radiometer using four frequencies centered around the 183.31 GHz water vapor absorption line, displaced by +- 1, 3, 7, and 14 GHz. For context, The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility operates a surface-based GVR at its North Slope of Alaska (NSA) site. The same GVR has been used previously for a field campaign in the southeast Pacific, where an offset was noticed between brightness temperatures (Tbs) measured under clear skies compared to those calculated from a radiative transfer model. To account for any calibration offsets to the Tbs, a request was made to DOE to allow the GVR to operate at ARM’s Southern Great Plains (SGP) observatory and enable comparisons between its measurements and those available at SGP. This request was granted, titled ‘UMGVR_CAL’, short for ‘UMGVR_Calibration’. From October 30 to November 10, 2023, the GVR was deployed to the ARM SGP site to take advantage of their regular, nearby radiosonde launches under clear-sky conditions. The latter were determined using the SGP total sky imagery data. The GVR brightness temperatures in these clear-sky conditions were compared to those calculated by a radiative transfer code (PAMTRA) based on the SGP radiosondes. During the campaign, four suitable clear-sky episodes could be used for the GVR calibration. While few in number, these proved to be enough to satisfy our goal.

54 ENVIRONMENTAL SCIENCES↗

Strainrange partitioning behavior of the nickel-base superalloys, Rene 80 and 100

A study has been made to assess the ability of the method of Strainrange Partitioning (SRP) to both correlate and predict high-temperature low-cycle fatigue lives of nickel-base superalloys for gas turbine applications. SRP is shown to correlate the cyclic lives of the baseline tests to within factors of nearly two. The partitioned strainrage versus life relationships for uncoated Rene 80 and cast IN 100 have also been determined from the ductility normalized-strainrange partitioning equations. These were used to predict the cyclic lives of the baseline tests. Predicted and observed cyclic lives agreed to within factors of nearly three. The life predictability of the method is also verified for cast IN 100 by applying the baseline results to the cyclic-life prediction of a series of complex strain-cycling tests with multiple hold periods at constant strain. It is concluded that the method of SRP can correlate and predict the cyclic lives of laboratory specimens of the nickel-base superalloys evaluated in this program.

Halford, G. R.↗

An assessment of the small-crack effect for 2024-T3 aluminum alloy

Data on small-crack behavior were obtained for a single-edge-notched tensile specimen made of 2024-T3 Al alloy and used to evaluate the capability of a semiempirical crack-growth and closure model to predict the fatigue life of notched specimens. Fatigue tests were conducted under either constant-amplitude loading (with stress ratios of 0.5, 0, -1, and -2) or spectrum loading, using a replication technique to record growth. It was found that small cracks exhibited the 'small-crack' effect in that they grew faster than large cracks when subjected to the same stress intensity factor range. Experimental small-crack growth rates agreed well with the model predictions. For making predictions of fatigue life, an initial surface defect void size of 3 x 12 x 0.4 microns was used in all calculations; predicted fatigue lives agreed well with experimentally determined values obtained in all tests. The crack-closure model indicated that the 'small-crack' effect on fatigue life was greatest in tests involving significant compressive loads.

Newman, J. C., Jr.↗

Predicting the oxidative lifetime of beta NiAl-Zr alloys

Nickel aluminides containing 40 to 50 at. pct Al and 0.1 at. pct Zr were studied following cyclic oxidation at 1400 C. The selective oxidation of Al resulted in the formation of protective Al2O3 scales on each alloy composition. However, repeated cycling eventually resulted in the gradual formation of less-protective NiAl2O4, first appearing on the 40Al alloys followed at longer times on the 45Al alloys. The appearance of the NiAl2O4, signaling the end of the protective scale-forming capability of the alloy, was related to the presence of gamma-prime (Ni3Al) which formed as a result of the loss of Al from the sample. A diffusion model, based on finite-difference techniques, was developed to predict the protective life of beta Ni-Al alloys. This model predicts Ni and Al concentration profiles after various oxidation exposures. The model can predict the oxidative lifetime due to Al depletion when the Al concentration decreases to a critical concentration. Measured Al concentration profiles on two alloys after various oxidation exposures are compared to those predicted by the diffusion model. The time to the appearance of the NiAl2O4 and that predicted by the diffusion model are compared and discussed.

Nesbitt, J. A.↗

Multi-Physics Based Thermo-Well Fatigue Design Tool

In this study, mathematical-based models for fatigue life were developed for Resistance Temperature Detectors (RTDs)/thermo-wells in high-pressure, cryogenic flow environments. A literature review that identified bench-scale stainless steel fatigue data at cryogenic temperatures that can be used to validate fatigue life mathematical models was pursued. Developing the ability to predict the fatigue life of RTDs/thermo-wells in high-pressure, cryogenic flow environments, especially liquid oxygen (LOX), will lead to a lower incidence of RTD damage and failure during propulsion test activities. During this performance period, the project was transitioned to a computational RTD/thermos-well fatigue modeling effort rather than the previously proposed experimental fatigue testing in FY19 since the computational modeling approach will provide a better fundamental understanding of fatigue behavior at cryogenic temperatures prior to pursuing potentially costly experimental tests. Due to COVID-19 issues impairing access to some needed university partnerships, tools and lab facilities, FY20efforts are continuing into FY21 and will be reported upon in greater detail in the FY21 report

Harry Ryan↗