Life Prediction Of Components Research Articles

Probabilistic fatigue life prediction of metallic components based on continuum damage mechanics

Based on continuum damage mechanics, a probabilistic method of predicting high-cycle fatigue life for metallic components is proposed. First, macro-meso two-scale stress-strain equations are established by combining Eshelby-Kroner localization law and classic elastic-plastic constitutive equation. Second, some parameters in Lemaitre's fatigue damage evolution model are randomized. Probabilistic properties of which are obtained by inverse-analysis and optimization. Then, the probabilistic method of predicting high-cycle fatigue life is established by coupling the model with macro-meso two-scale equations. And the proposed algorithm is coded with Fortran language, which is non-intrusive post-program of FEM analysis. Next, constant amplitude fatigue test of Al 2024-T3 coupon is performed to determine probabilistic properties of model parameters. Finally, as the object of study, wallboard is analyzed by FEM. Taking skin-strip component as research object, the fatigue life of hot spot is predicted by proposed method. The corresponding fatigue test of the component is performed, which verifies the effectiveness of proposed method to predict probabilistic life of metallic components.

Planning for Maintenance and Repair of Continuous Ship Unloader Using the IRRO Method

The problem faced is damage, especially to the screw conveyor from the Continuous Ship Unloader (CSU) as a dry bulk material transfer equipment (phosphate rock) which is taken from the ship's hold which is flowed by a screw conveyor followed by the belt conveyor to the material warehouse to be processed into a type of fertilizer. The purpose of planning is to obtain a schedule and estimated cost of maintenance and repair of CSU for the period 2022 to 2025, and to obtain the ratio of maintenance-repair costs to the profit of the machine. Planning methods uses the IRRO (Inspection, Replace, Repair, and Overhoul) method include data collection of machine maintenance history and component breakdowns, checking CSU specifications, making a list of component life predictions and component prices, predicting costs and duration of component dissasembly, screw conveyor repair, maintenance and repair scheduling, and maintenance and repair cost estimates. The real results of planning in the form of a maintenance and repair schedule for the period of 2022 to 2025; maintenance and repair costs respectively for the years 2022 to 2025 are IDR 136,873,000; IDR 335,986,000; IDR 160,687,000; and IDR 464,733,000; and the ratio between maintenance costs to profit for the years 2022 to 2025 is 0.51, 1.22, 0.57, and 1.63 which means the machine is still fit for use without the need for refurbishment because it is still prospective.

Low-cycle fatigue life prediction of I-shaped steel brace components and braced frames

Four methods (seven models) are extended and applied to the low-cycle fatigue life prediction of steel brace, including the ductile damage method, the equivalent strain method, the critical plane method, and the representative strain method. Using these models, the fatigue life of 53 steel brace components and 5 bracing members in single diagonal braced frames is predicted and compared with the measured life in experiments. Thus, some useful information on the accuracy and reliability of different methods is provided. Based on a parametric sensitivity analysis, the ductile damage model can represent the fracture process of the brace and has a good application on fatigue life prediction, especially when the fatigue life is less than 60. The equivalent strain method overestimates the fatigue life while the critical plane method underestimates the fatigue life. The fatigue parameters of steel Q235B in these two life prediction methods are obtained. The proposed representative strain method compensates for the fact that the fiber model cannot consider the effect of local buckling on the fatigue life of the bracing member. This method has good accuracy and computational efficiency on fatigue life prediction.

An Improved Creep-Fatigue Life Model Involving the Cyclic Softening/Hardening and Stress Relaxation Effect

Abstract In this work, improved creep-fatigue life prediction models based on time fraction (TF) and ductility exhaustion (DE) rule are established for creep-fatigue life prediction of components at elevated temperatures. Cyclic softening/hardening and stress relaxation models for cyclic softening/hardening material are incorporated in the model. Materials data conducted by authors and collected from references are employed for validations. Results indicated that the improved models proposed could present more realistic evolution behavior of materials than the half-life models. The differences of the predicted lives based on the improved models and half-life models are dependent on cyclic behaviors of materials. The predicted life by the improved model is lower than that gained by the half-life model for cyclic softening steels, while it is higher than that by the half-life model for cyclic hardening steels. In addition, the DE rule could overcome the influence of cyclic softening/hardening on creep-fatigue life prediction more significantly than the TF rule.

Deep LSTM Enhancement for RUL Prediction Using Gaussian Mixture Models

This paper introduces a new deep learning model for Remaining Useful Life (RUL) prediction of complex industrial system components using Gaussian Mixture Models (GMMs). The used model is an enhanced deep LSTM approach, for which Gaussian mixture clustering is performed for all collected sensors data and operational monitoring information. This distribution-based clustering using the hyperparameter e leads to an adequate deep neural network for RUL prediction. An expectation-maximization algorithm was implemented to configure the deep LSTM network for RUL estimation. The proposed Gaussian mixture Clustering-based deep LSTM model for useful life prediction of the industrial components is trained and tested on the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) datasets. The experiments of the enhanced deep LSTM model show clearly the relevance of using Gaussian mixture clustering for quality improvement of RUL prediction through deep LSTM models. ( https://github.com/sayahmhgithub/EnhancedLSTM4RUL.git ).

Multiaxial fatigue life prediction based on a simplified energy-based model

Thanks to the reliable correlation with experimental data, conventional energy-based models are widely employed in multiaxial fatigue life prediction of structural components, by combining energy-based variables with reference life curves. However, in practical applications, additional calibration factors and incremental plasticity theories are usually indispensable to characterize fatigue damage along multiaxial loading paths, whose procedures are usually rather complicated and time-consuming. In this paper, a simplified energy-based model, as an alternative to the incremental plasticity-based model, is proposed to predict the fatigue life under multiaxial loading. Being different from conventional models, the proposed model is based on a series of multiaxial energy-life curves, which avoids the introduction of additional calibration factors. Particularly, to eliminate the model’s dependence on incremental plasticity theory, the effect of loading paths is captured by a loading path-dependent factor which is derived from the non-proportionality factor and the Moment of Inertia method. The availability of the proposed model is validated by reasonable correlations with experimental data of four kinds of materials under diverse loading paths.

Mathematics of Gas Ingress of Hermetic Packages

We have derived a gas ingress and egress equation from the first principles of ideal gases. This work is intended to benefit the hermetic microelectronics packaging community, but it may be applied to other fields that require a deep understanding of gas ingress and egress dynamics. The equation outlined herein encompasses package material properties, package characteristics, hermetic testing conditions, and service conditions. It serves as a practical utility for calculating package pressure changes due to gas ingress and egress and, therefore, a power tool for component and system service life predictions.

Impact of Prognostic Uncertainty in System Health Monitoring

Across many industries, systems are exceeding their intended design lives, whether they are ships, bridges or military aircraft. As a result failure rates can increase and unanticipated wear or failure conditions can arise. Health monitoring research and application has the potential to more safely lengthen the service life of a range of systems through utilization of sensor data and knowledge of failure mechanisms to predict component life remaining. A further benefit of health monitoring when combined across an entire platform is system health management. System health management is an enabler of condition based maintenance, which allows repair or replacement based on material condition, not a set time. Replacement of components based on condition can enable cost savings through fewer parts being used and the associated maintenance costs. The goal of this research is to show the management of system health can provide savings in maintenance and logistics cost while increasing vehicle availability through the approach of condition based maintenance.This work examines the impact of prediction accuracy uncertainty in remaining useful life prognostics for a squadron of 12 aircraft. The uncertainty in this research is introduced in the system through an uncertainty factor applied to the useful life prediction. An ARENA discrete event simulation is utilized to explore the effect of prediction error on availability, reliability, and maintenance and logistics processes. Aircraft are processed through preflight, flight, and post-flight operations, as well as maintenance and logistics activities. A baseline case with traditional time driven maintenance is performed for comparison to the condition based maintenance approach of this research.This research does not consider cost or decision making processes, instead focusing on utilization parameters of both aircraft and manpower. The occurrence and impact of false alarms on system performance is examined. The results show the potential availability, reliability, and maintenance benefits of a health monitoring system and explore the diagnostic uncertainty.

Service life prediction of building components in the times of climate change

Buildings components and assemblies are prone to decay over time due to the inherent characteristics of the materials, environmental conditions and operational use of them. For this reason, it is very important to know the right time and type of maintenance and adaptation interventions that need to be applied to the specific compounds. The answer to the above issue can be given through the service life prediction (SLP) of the components by using standardized calculation methods.In historic buildings, the process of SLP takes significant importance because these buildings hold non-renewable cultural heritage value and therefore, the interventions should be performed in a way that preserves the original material and value while enhancing the service life. Nowadays, for such buildings that are predicted to live for centuries, the SLP needs to be corrected by considering the effects of climate change in the construction materials.The paper presents an overview of the application of the well-known factor method in the estimation of the serviceability of the building components, with a special focus on historic buildings impacted by climate change. The technical compatibility, economic viability, use of the building and the indoor/outdoor environments are considered during the assessment of the service life which is strictly linked with the level of decay. It gives a short explanation of the factors that constitute the method by including the effects of climate change and an example of application to a specific case study in Norway.

Structural Evaluation of Variable Gauge Railway

In the Eurasian railway network, a different gauge length is used across several countries. A railroad variable gauge allows railway vehicles in rail transport to travel across a gauge break caused by two railway networks with differing track gauges. The variable gauge railway consists of the bogie system to change the length of the wheel shaft and the gauge changing railroad track. Thus, it is important to assess the structural performance of the variable gauge system. In this study, as a performance improvement subject of the variable gauge bogie and railroad, a structural analysis using dynamic finite element calculation was performed to evaluate the reliability and life cycle of the release system and the variable gauge railway. First, the contact pressure and structural stress of the release disk and the release rail were calculated, which provided the wear condition and fatigue life prediction of variable gauge components. Second, a structural analysis of the gauge stabilization rail after the gauge release was executed. The maximum principal stress was evaluated to guarantee the required service life of the stabilization rail section. For the operational safety of the variable gauge system, the operation conditions and maintenance requirements of the variable gauge railway were proposed.

Fatigue crack growth mechanisms in powder metallurgy Ni-based superalloys—A review

Powder metallurgy (PM) Ni-based superalloys are widely used for aeroengine turbine disc applications due to their excellent mechanical properties and good corrosion resistance at elevated temperatures. Understanding the fatigue crack growth (FCG) mechanisms of PM Ni-based superalloys is important for both disc alloy development and life prediction of disc components in these advanced aeroengines where damage tolerance design prevails. FCG in PM Ni-based superalloys is a complicated function of microstructure, temperature, loading conditions and environment and is usually a consequence of the synergistic effects of fatigue, creep and environmental damage. In this review, the mechanisms controlled by microstructural features including grain size, grain misorientation, γ′ size and distribution on short and long FCG behaviour in PM Ni-based superalloys are discussed. The contribution of creep and environmental damage to FCG has been critically assessed. The competing effects of mechanical damage (i.e. fatigue and creep) and environmental damage at the crack tip are microstructure-sensitive, and usually results in transition between transgranular, mixed-trans-intergranular and intergranular FCG depending on the contribution of environmental damage to FCG processes.

Thermal vulnerability detection in integrated electronic and photonic circuits using infrared thermography.

Failure prediction of any electrical/optical component is crucial for estimating its operating life. Using high temperature operating life (HTOL) tests, it is possible to model the failure mechanisms for integrated circuits. Conventional HTOL standards are not suitable for operating life prediction of photonic components owing to their functional dependence on the thermo-optic effect. This work presents an infrared (IR)-assisted thermal vulnerability detection technique suitable for photonic as well as electronic components. By accurately mapping the thermal profile of an integrated circuit under a stress condition, it is possible to precisely locate the heat center for predicting the long-term operational failures within the device under test. For the first time, the reliability testing is extended to a fully functional microwave photonic system using conventional IR thermography. By applying image fusion using affine transformation on multimodal acquisition, it was demonstrated that by comparing the IR profile and GDSII layout, it is possible to accurately locate the heat centers along with spatial information on the type of component. Multiple IR profiles of optical as well as electrical components/circuits were acquired and mapped onto the layout files. In order to ascertain the degree of effectiveness of the proposed technique, IR profiles of complementary metal-oxide semiconductor RF and digital circuits were also analyzed. The presented technique offers a reliable automated identification of heat spots within a circuit/system.

Creep fracture parameter C* solutions for axial internal and external surface cracks in pressurized cylinders

Accurate calculations of creep fracture mechanics parameter C* is very important for life prediction and assessment of high-temperature cracked components. The current two engineering estimation approaches (EPRI and reference stress approaches) for C* can seriously overestimate or sometimes underestimate C* of cracked components, thus it is desirable to develop accurate C* solutions. In this work, based on extensive three-dimensional (3D) finite element analyses, the C* solutions for axial internal and external surface cracks with a wide range of sizes in pressurized cylinders with different geometry sizes are investigated and developed. The creep influence function Hc for calculating C* along the crack fronts has been obtained and fitted into equations, and the accuracy of the equations has been verified. The correlation equations between C* and creep hardening exponent n are firstly developed which can be conveniently used to estimate C* for materials with different n values. The effects of crack sizes and cylinder geometries on the C* distributions along the crack fronts also are analyzed.

Prediction of fatigue life of suspension parts of the semi-trailer in the early stages of design

Cargo delivery by trucks is a main method of transportation of goods to the cities and other places. Many goods are transported by articulated lorries. Thus, improving the design methods of the articulated lorries is relevant. Trailer suspension is the object under study. A fatigue life prediction of the trailer suspension components is a urgent task at the early stage of design concept development. The formation principles of the MBD model is essential in obtaining best results. In this paper two types of models are considered: containing only the rigid bodies; containing the flexible bodies. Research objective: the investigation of the effect of the load distribution that was obtained using different MBD models on the durability of suspension parts. A comparison of the results obtained using the different suspension models was performed. The research has shown that loads are reducedusing the flexible bodies in the MBD model. Using flexible bodies permits to specify the results of the durability analysis.

A modified stress field intensity approach for fatigue life prediction of components

In the present paper, a modified fatigue life model is proposed based on stress field intensity (SFI) approach, where the average weight function is introduced as the denominator of the traditional model and a modified definition of the fatigue zone is given using the concept of characteristic stress. Combined with finite element analysis, the fatigue life predictions of a central hole specimen from the literature and the notched plate specimens/a simulated engineering component conducted by the authors are carried out by the new model. Results indicate that the predicted lives are in good agreement with the experimental results and the modified stress field intensity approach is convenient for practical use.

LCF/TMF Model Based Approach for the Prediction of Fatigue Life of Components in Lightweight Automotive Engines

The life prediction of mechanical components in presence of Thermo-Mechanical Fatigue (TMF) is a crucial issue of the design activity. In the combustion engine, that action looks rather difficult because of a superposition of several damage phenomena. Some TMF models are currently available in the literature, but they include many parameters, whose calibration usually requires an onerous testing activity. Therefore, industry requires an assessment of those techniques, to be implemented through some simplified and reliable procedures. In this paper, the prediction of TMF life of a lightweight engine component is based on a new procedure, exploiting the isothermal Low-Cycle Fatigue (LCF) and creep tests, some theoretical approaches applied to TMF and numerical modeling. The A356 Aluminum Alloy is analyzed, as an example of strategic material used to design the new automotive lightweight engines. The calibration of TMF models based on the isothermal LCF and creep tests was found reliable. The fatigue life prediction looks compatible with some preliminary experimental results. Therefore, the proposed approach is suitable to simplify the design procedure, to decrease costs, especially related to testing, and to perform a preliminary trade-off activity of the engine layout.

An upscaling approach for micromechanics based fatigue: from RVEs to specimens and component life prediction

A novel approach has been developed to estimate fatigue life at the specimen/component level from the simulation of relatively small Representative Volume Elements (RVE) of the polycrystalline microstructure. This technique estimates the statistical distribution of fatigue lives under general multiaxial loading conditions accounting for both microstructure and specimen size. The model relies on computational homogeneization where the crystal behavior follows a crystal plasticity model and simulations are performed using a FFT based solver. The simulation of the cyclic response of a set of different RVEs provides the statistical distribution of Fatigue Indicator Parameters for that RVE size, which can be accurately represented by an extreme value distribution as the Gumbel distribution. This distribution is upscaled to the actual size of the specimen or component of interest using a weakest link approach and is finally transformed into a distribution of fatigue lives using a simple fatigue-life expression fitted with experiments. The framework proposed estimates fatigue lives of specimens with millions of grains from the results obtained with RVEs containing only hundreds of grains and is able to reproduce the specimen size effect on fatigue life. The approach is first numerically validated and then used to predict the statistical distribution of fatigue life of a polycrystalline Ni-based superalloy showing very accurate results.

Diamond-Coated Mechanical Seal Remaining Useful Life Prediction Based on Convolution Neural Network

Reliable remaining useful life (RUL) prediction of industrial equipment key components is of considerable importance in condition-based maintenance to avoid catastrophic failure, promote reliability and reduce cost during the production. Diamond-coated mechanical seal is one of the most critical wearing components in petroleum chemical, nuclear power and other process industries. Estimating the RUL is of critical importance. We consider the data-driven approaches for diamond-coated mechanical seal RUL estimation based on AE sensor data, since it is difficult to construct an explicit mathematical degradation model of seal. The challenges of this work are dealing with the noisy AE sensor data and modeling the degradation process with fluctuation. Faced with these challenges, we propose a pipeline method CDF-CNN to estimate the RUL for mechanical seal: WPD-KLD to raise the signal-to-noise ratio, novel CDF-based statistics to represent seal degradation process and CNN structure to estimate RUL. To acquire AE sensor data, several diamond-coated seals are tested from new to failure in three working conditions. Experimental results demonstrate that the proposed method can accurately predict the RUL of diamond-coated mechanical seal based on AE signals. The proposed prediction method can be generalized to other various mechanical assets.

Interacting Effects of Internal Defects and Corrosion Pits on the Stress Concentration of Hourglass-Shaped Specimens

The interacting effects of internal defects and corrosion pits on the stress concentration factors in hourglass-shaped specimens were investigated through a finite element method investigation. Very high cycle fatigue tests were performed to confirm the shape of the internal defects and the depth of the corrosion pit. According to the experimental observations, a series of three-dimensional models containing internal voids and corrosion pits were established. Stress distribution around the internal void and the corrosion pit under uniaxial tensile loading were obtained. Based on the finite element analysis, the stress concentration factors around the defects were found fully dependent on the structure parameters of the internal void and the corrosion pit. Stress concentration factors increased with the depth-to-length ratios Rd for models with a single corrosion pit. For models with a single internal void, the stress concentration factors increased dramatically when the internal void is present near the surface. Parameters of distance-to-radius ratio (D2 − h)/a and depth-to-length ratio Rd play important roles in the stress distribution for a model with both an internal void and a corrosion pit. Severe stress concentration would be introduced when the parameter (D2 − h)/a < 2. For a deep corrosion pit (i.e., Rd ≥ 1), the stress concentration factors were determined by two parts which were dominated by parameters of (D2 − h)/a and Rd, separately. For a shallow corrosion pit (i.e., Rd < 1), the stress concentration factors were dominated by the interaction of (D2 − h)/a and Rd. Two very close corrosion pit and void were most likely to be an initiation position and gave rise to devastating effects on the very high cycle fatigue performance of the specimens. Empirical equations were proposed to evaluate the relationship between the stress concentration factors and the structural parameters of defects. The obtained quantitative information would be useful for understanding of crack initiation and fatigue life prediction of engineering components.

Investigation of Fatigue Strength and Life Prediction for Automotive Safety Components of V-Notched and Un-notched Specimen Part I: Utilization of Waste Materials into Raw Materials

This paper deals with a design of industrial cast-parts and mainly focuses on fatigue life influenced by organic and inorganic particles at different stress levels over a wide range spectrum, which is evaluated and compared. The fracture mechanisms and fatigue strength of V-notch and un-notch specimens are described. The notch factor and notch sensitivity factors have been studied. Porosity is the main factor for crack growth, and it reduces with the addition of waste particles. This combination receives a lot of attention due to its low cost and environmental safety. The micro-/macro-cracks and fracture surface are revealed using SEM and OM analysis.