Deterministic Stress Research Articles

Deterministic Stress Intensity Factor of a Railway Axle under Adverse Running Condition

Although railway axles are a crucial part of railway vehicles, they are susceptible to long-term failure because of repeated loads. The aim of this research is to investigate the stress intensity factor (SIF) of a surface elliptical crack on a high-speed railway axle under various operating conditions. The study employs numerical analysis to explore the impact of press-fitting, rotary bending, stable and adverse running conditions on the SIF solutions. The main findings demonstrate that adverse running conditions, such as the press-fitting force, asymmetric vehicle weight, lateral force and wheel-rail contact force, can significantly increase the SIF values and result in axle failure. The press-fitting effect and rotary bending also have a significant impact on the SIF values, highlighting their importance in the railway axle design and analysis. The outcome of this research emphasizes the significance of accurately estimating SIF values to ensure the safe and reliable performance of railway axles in adverse operating conditions.

Investigation of Unsteady Rotor–Stator Interaction and Deterministic Correlation Analysis in a Transonic Compressor Stage

Abstract Unsteady blade row interaction (UBRI) has a large impact on performance in high-speed axial compressors. Thus, the influence of UBRI should be accurately predicted in compressor routine design. In this study, the unsteady rotor–stator interaction in a transonic single-stage compressor, NASA Stage 35, is studied by steady and unsteady Reynolds-Averaged Navier–Stokes methods. First, the UBRI is analyzed. Periodic separation bubbles on the stator suction surface induced by the rotor wake are observed. Comparisons between steady and unsteady results show that the radial distribution of flow angle near the hub and tip region of the stator is strongly influenced by UBRI. Second, deterministic correlations are analyzed based on the average-passage equation system. The distribution of deterministic stress and the relationship between spatial correlations and deterministic correlations are analyzed. Results show that a strong nonlinear interaction caused by the rotor wake and the stator potential field is found in the rotor–stator gap, which is responsible for the generation of spatial–time correlation. Then, the anisotropy of deterministic correlations is analyzed using the Lumley triangle. Results show that the deterministic stress is highly anisotropic in the stator passage, which can be considered in the modeling using a similar strategy of turbulence modeling. At last, the relationships between the harmonics and decay rate of deterministic correlations are analyzed. The decay rate of deterministic correlation is highly related to the corresponding harmonics, and the higher-order harmonic exhibits a higher decay rate. A modified exponential decay model is proposed for deterministic correlation based on harmonics, which provides improved performance.

Heteroscedastic sparse Gaussian process regression-based stochastic material model for plastic structural analysis

Describing the material flow stress and the associated uncertainty is essential for the plastic stochastic structural analysis. In this context, a data-driven approach-heteroscedastic sparse Gaussian process regression (HSGPR) with enhanced efficiency is introduced to model the material flow stress. Different from other machine learning approaches, e.g. artificial neural network (ANN), which only estimate the deterministic flow stress, the HSGPR model can capture the flow stress and its uncertainty simultaneously from the dataset. For validating the proposed model, the experimental data of the Al 6061 alloy is used here. Without setting a priori assumption on the mathematical expression, the proposed HSGPR-based flow stress model can produce a better prediction of the experimental stress data than the ANN model, the conventional GPR model, and Johnson Cook model at elevated temperatures. After the HSGPR-based flow stress model is implemented into finite element analysis, two numerical examples with synthetic material properties are performed to demonstrate the model’s capability in stochastic plastic structural analysis. The results have shown that with sufficient data, the distribution of the structural load carrying capacity at elevated temperatures and the variation of load–displacement curves during the loading and unloading processes can be accurately predicted by the HSGPR-based flow stress model.

Numerical study of the influence of weld geometry variations on fatigue life using the notch stress analysis

Idealized geometry is typically used in standards for the fatigue life assessment of welded joints. In the presence of stochastic geometrical variations along the weld, the choice of the idealized geometry is however ambiguous. In the notch stress (NS) method with a fictitious notch radius rref = 1 mm, the FAT 225 curve is derived for welds with relatively good quality in toe profiles. In the NS method with rref = ractual + 1 mm, a lower FAT 200 curve is recommended. Both approaches neglect the stochastic variability in toe radius, toe angle and leg length along the weld. The aim of this paper is two-fold. First, a numerical comparison between both approaches in terms of their predicted fatigue life is performed for a non-load carrying fillet cruciform joints. The results show that the NS method with rref = 1 mm and FAT 225 is substantially more conservative. Second, these methods are enhanced by replacing the deterministic stress concentration factor by a probability distribution computed using Monte Carlo simulation. It is shown that NS with rref = 1 mm and FAT 225 does not predict any substantial influence of the stochastic variability in process parameters since the actual toe radius is not included in the analysis. However, the NS method with rref = ractual + 1 mm and FAT 200 predicts a decrease in fatigue life when uncertainties in geometrical parameters is included. This numerical study paves the way for an experimental validation of the predicted influence of stochastic variability of geometrical parameters based on the stochastic notch stress analysis.

Assessing the financial condition and accounts receivable risk among US farmer cooperatives

PurposeThe purpose of this paper is to examine the financial condition and ability of farmer cooperatives to withstand significant increases in bad debt expense.Design/methodology/approachA unique data set of farmer cooperative financial statements that spans from 1996 to 2019 is used to examine the changes in profitability, solvency, liquidity and accounts receivable risk. Also, a deterministic stress test model is designed to shock bad debt expense and the resulting write-off of accounts receivable for farmer cooperatives. The stress test provides insights to the resiliency of farmer cooperatives.FindingsResults find that farmer cooperatives are in a strong financial position, which has improved over time. The majority of farmer cooperatives are able to absorb a substantial increase in bad debt expense because of their sizable, retained earnings position. However, cooperatives that have significant profitability challenges do experience much larger losses, especially mixed farmer cooperatives (roughly equally amounts of grain and farm supply sales) and large cooperatives with more than $500 million in sales.Practical implicationsThe stress test results suggest farmer cooperative managers and boards of directors could re-examine their credit policies and consider extending additional credit. Also, cooperatives should consider monitoring and identifying an optimal accounts receivable to retained earnings ratio, which is similar to how banks examine their tier 1 capital ratios.Originality/valueThe value of this study is having data that allows for the examination of the financial condition of farmer cooperatives over time. Also, having current data means the accounts receivable stress test results are more relevant and timelier. This is important because these accounts receivable are primarily tied to crop input supplies, and farmer cooperatives are a significant market participant in the crop input supply market.

Mandibular reconstruction system reliability analysis using probabilistic finite element method

The aim of this study was to design for mandibular reconstruction of large lateral defect with minimum target reliability with designated confidence interval under bite force range of 300 ± 102 N. The performance of the models has been evaluated by numerical analysis considering the uncertainty of input parameters. Computer-Aided design was used to develop the models of three designs according to the patient's anatomy and to achieve to near symmetry of the mandible. Stress-strength modeling was utilized for the probabilistic physics of failure analysis under assumption of a quasi-static load. Monte-Carlo simulation was also applied for probabilistic finite element analysis and reliability assessment. The sensitivity analysis of the models was developed to reflect the significance of the variables in the models. The deterministic stress analysis shows that the highest stress and the second maximum stress are 110 MPa and 85 MPa for cortical bone around the screws, respectively. Also, it is determined that the maximum plate stress of the titanium conventional plate model is 580 MPa. The reconstruction system success rate was improved in all models by observing the anatomy of the patient's mandible in the plate designs by computer-aided design and additive manufacturing techniques. Based on the results, the reliability of plate strength and pull-out screws strength are 99.99% and 96.71% for the fibula free flap model, respectively, and 99.99% and 94.17%, respectively, for the customized prosthesis model. Probability sensitivity factors showed that uncertainty in the elastic modulus of the cortical bone has the greatest effect on the probability of screws loosening.

Liquidity Stress Testing a Tool for Integrated Liquidity Risk Management

Stress Test is forward looking simulation exercise to assess resilience of financial institutions in the midst of sever but plausible adverse scenario.Liquidity Stress testing is an important means for sketching out acomprehensive picture of liquidity risk profile of an institution. Stress testing is a powerful tool in the hands of Liquidty risk managers.Liquidity stress testing involves weighing potential net liquidity outflow exposures under stressed scenarios vis a vis the available counterbalancing capacity. Varying behaviour of fund providers and users in different stress situations based on their market and solvency perception of the concerned institutions necessitates measurement and management of liquidity risk scenario specific. Identification of cash-flow drivers is perhaps the most crucial step in defining and structuring the scenario parameters. Deterministic stress test pivots on assumptions and methods. The set of assumptions have to be as realistic as possible ensuring proper alignment in an internally consistent way. The stress test outcomes help in identification of severe vulnerabilities. The method however involves subjectivity throwing ideas about loss severity without any estimate of associated chance and probability of occurrence thereof. Stress Tests based on hypothetical data and assumptions are useful but not accurate. Stress testing provides where withal for formulation of the plan to tackle effectively liquidity problems as when arising. Stress testing work as effective tool provided its outcomes and findings are properly evaluated and incorporated in the strategic plan. Stress testing is not the ultimate! Instead it forms only a component of dynamic and integrated liquidity risk management process. However, stress testing is definitely an effective tool providing valuable inputs to risk management decisions provided it is sufficiently embedded and aligned to risk management frameworks and senior management decision making frameworks.

Numerical modelling of anomalous microseismicity influenced by lithological heterogeneity in longwall top coal caving mining

Mining-induced microseismicity has been extensively used to evaluate the potential for rock bursts and coal and gas outbursts in underground coal mines. In a research project completed a few years ago, it was observed that characteristics of microseismicity around a working longwall panel were fairly consistent over the monitoring period until a lithological heterogeneity zone with a relatively high coal strength was reached. The current research presented in this paper aims at achieving a better understanding of the effect of lithological heterogeneity on microseismic activity in longwall coal mining. The heterogeneous zone inferred from the tomography measurements was first digitalised and implemented into a 3D geomechanical model. A microseismicity modelling approach which combines deterministic stress and failure analysis together with a stochastic fracture slip evaluation was used to simulate the evolution of microseismicity induced by the progressive face advance passing through the heterogeneous zone. The heterogeneity was taken into account by varying the material strength and the fracture attributes of the elements within the high strength zone. Results have shown that both the high rock strength of coal lithotype and low power law scaling exponent of fractures within this zone contribute to the reduction in fitted b values from frequency-magnitude distribution of microseismicity and the increase in fitted Gaussian distribution parameters to the logarithmic event energy. These deviations are believed to result from the combined effects of increased stress drops and slipped fracture sizes when the heterogeneous zone is approached.

Numerical Analysis of the Deterministic Stresses Associated to Impeller-Tongue Interactions in a Single Volute Centrifugal Pump

In this paper, a deterministic stress decomposition is applied over the numerical three-dimensional flow solution available for a single volute centrifugal pump. The numerical model has proven in previous publications its robustness to obtain the impeller to volute-tongue flow interaction, and it is now used as starting point for the current research. The main objective has been oriented toward a detailed analysis of the lack of uniformity in the flow that the volute tongue promotes on the blade-to-blade axisymmetric pattern. Through this analysis, the fluctuation field may be retrieved and main interaction sources have been pinpointed. The results obtained with the deterministic analysis become of paramount interest to understand the different flow features found in a typical centrifugal pump as a function of the flow rate. Moreover, this postprocessing tool provides an economic and easy procedure for designers to compare the different deterministic terms, also giving relevant information on the unresolved turbulence intensity scales. Complementarily, a way to model the turbulent effects in a systematic way is also presented, comparing their impact on the performance with respect to deterministic sources in a useful framework, that may be applied for similar kinds of pumps.

Numerical Study of Deterministic Fluxes in Compressor Passages

Computational fluid dynamics (CFD) has been widely adopted in the compressor design process, but it remains a challenge to predict the flow details, performance, and stage matching for multistage, high-speed machines accurately. The Reynolds Averaged Navier-Stokes (RANS) simulation with mixing plane for bladerow coupling is still the workhorse in the industry and the unsteady bladerow interaction is discarded. This paper examines these discarded unsteady effects via deterministic fluxes using semi-analytical and unsteady RANS (URANS) calculations. The study starts from a planar duct under periodic perturbations. The study shows that under large perturbations, the mixing plane produces dubious values of flow quantities (e.g., whirl angle). The performance of the mixing plane can be considerably improved by including deterministic fluxes into the mixing plane formulation. This demonstrates the effect of deterministic fluxes at the bladerow interface. Furthermore, the front stages of a 19-blade row compressor are investigated and URANS solutions are compared with RANS mixing plane solutions. The magnitudes of divergence of Reynolds stresses (RS) and deterministic stresses (DS) are compared. The effect of deterministic fluxes is demonstrated on whirl angle and radial profiles of total pressure and so on. The enhanced spanwise mixing due to deterministic fluxes is also observed. The effect of deterministic fluxes is confirmed via the nonlinear harmonic (NLH) method which includes the deterministic fluxes in the mean flow, and the study of multistage compressor shows that unsteady effects, which are quantified by deterministic fluxes, are indispensable to have credible predictions of the flow details and performance of compressor even at its design stage.

Reliability analysis of soil nail internal limit states using default FHWA load and resistance models

Reliability analyses of nail pullout, nail-in-tension, and system reliability of internal limit states are presented for both permanent and temporary soil nails that are designed using default Federal Highway Administration nail load and resistance models within traditional deterministic allowable stress design (ASD) framework. The model uncertainty, correlations between soil strength parameters, between model factor, and nominal load term, and between the two internal limit states, and influence of model factor fittings are all addressed in the analyses. This study provides a general idea of the reliability that is implicitly embedded in current ASD-based soil nail internal limit state designs.

Reliability Analysis of Systems with Common Cause Failure Based on Stress-Strength Interference Model

Many mechanical systems have the characteristics of multiple failure modes and complex failure mechanisms. On the basis of stress-strength interference (SSI) model, this paper takes the mechanical system with common cause failure (CCF) as the research object. The relationship between the stress distribution and the strength distribution is studied, and the failures of components are independent of each other under the deterministic stress. Then, the concept of conditional reliability is introduced to build the system reliability models under the action of one-stress and multi-stress for both series and parallel systems. Finally, the corresponding properties of the proposed methods are discussed to show their advantages.

Numerical modelling of microseismicity associated with longwall coal mining

Microseismicity has long been a precursor for underground mining hazards such as rockbursts and coal and gas outbursts. In this research, a methodology combining deterministic stress and failure analysis and stochastic fracture slip evaluation, based upon the widely accepted fracture slip seismicity-generation mechanism, has been developed to simulate microseismic events induced by longwall mining. Using the built-in DFN facility in FLAC3D, discrete fractures following a power law size distribution are distributed throughout a 3D continuum model in a probabilistic way to account for the stochastic nature of microseismicity. The DFN-based modelling approach developed was adopted to simulate the evolution of microseismicity induced by the progressive face advance in a longwall top coal caving (LTCC) panel at Coal Mine Velenje, Slovenia. At each excavation step, global stress and failure analysis with reference to the strain-softening post-failure behaviour characteristic of coal, and fracture slip evaluation for microseismicity are conducted sequentially. The model findings are compared to the microseismic event data recorded during a long-term field monitoring campaign conducted at the same LTCC panel. It was found that the released energy and frequency-magnitude distribution of microseismicity are associated with the slipped fracture sizes and fracture size distribution. These features for recorded microseismic events were fairly constant until a xylite rich heterogeneous zone ahead of the working face was approached, which indicates that fractures within the extracted coal seam follow the same size distribution. The features obtained from modelled microseismic events were consistent over the production period, and matched well the field observations. Furthermore, the model results indicate that the power law fracture size distribution can be used to model longwall-mining-induced microseismicity. This model provides a unique prospective to understand longwall coal mining-induced microseismicity and lays a foundation to predict microseismicity, or even rockburst potential in specific geological realisations.

Geomechanical Risk Assessment for Subsurface Fluid Disposal Operations

Numerical models are commonly used to estimate the state of stress in the subsurface for various engineering applications. These estimates are subject to considerable uncertainty, and yet, the estimates are almost always deterministic, yielding no information about the certainty of the prediction. For some applications, unquantified uncertainties in stress are often acceptable, because the risks related to geomechanics may be of low relative importance compared to other risks (e.g., recoverable resource volume), for which uncertainties are often quantified. Furthermore, many geomechanics-related risks in the petroleum industry are relatively short-lived (e.g., well bore stability) and decrease in importance with time. In contrast, for wastewater injection or geologic carbon sequestration (GCS), geomechanics-related risks (e.g., seal integrity, induced seismicity) are on par with resource-related risks and are of long-term concern, with the risk generally increasing in importance for a significant period of time. For these reasons, the deterministic stress estimation and risk analysis approaches generally applied in the petroleum industry are insufficient for GCS applications. This paper describes a Bayesian approach to geomechanical uncertainty quantification and risk assessment. The method is demonstrated using data from an active enhanced oil recovery/geologic carbon sequestration field as a case study.

Investigation of Unsteady Flow Interactions in a Transonic High Pressure Turbine Using Nonlinear Harmonic Method

The performance of a transonic high pressure turbine is mainly influenced by the unsteady interactions associated with the passing blades. In this paper, the unsteady flow interactions in a transonic turbine have been numerically investigated using the nonlinear harmonic (NLH) method in comparison with the steady and unsteady Reynolds-averaged Navier–Stokes (RANS). The comparison shows that the NLH method using three harmonics could capture the main unsteady flow interactions efficiently with about seven times smaller computational cost than the unsteady RANS, resulting in a more accurate time-averaged flow than for steady RANS. However, the continuity of the flow variables across the rotor-stator interface has shown some discrepancies compared with the unsteady RANS, which can be further satisfied by increasing the numbers of harmonics. The unsteady interactions are analyzed in detail; the results show that the wake and trailing edge shock from the upstream stator are the major sources of unsteadiness in the downstream rotor passage. The stator trailing edge shock impinges on the suction side of the passing rotor blades and generates pressure waves. These pressure waves are periodically reflected back to trigger the stator wake shedding. These waves are strong enough to travel through the rotor passage, and eventually affect the flow at the rotor’s trailing edge. The stator wakes are chopped by the downstream rotor, and travel through the rotor passage. This significantly enhances the unsteadiness of the flow near the rotor trailing edge. Lastly, the deterministic stresses and enthalpy distributions extracted from the NLH method have revealed that the effects of the unsteadiness are relatively weaker in the axial direction. Furthermore, the deterministic correlations analysis has shown that, some empirical deterministic correlations models based on the decay concept of compressors are not suitable for turbines.

Fractional viscoelastic behaviour under stochastic temperature process

This paper deals with the mechanical behaviour of a linear viscoelastic material modelled by a fractional Maxwell model and subject to a Gaussian stochastic temperature process. Two methods are introduced to evaluate the response in terms of strain of a material under a deterministic stress and subjected to a varying temperature. In the first approach the response is determined making the material parameters change at each time step, due to the temperature variation. The second method, takes advantage of the Time–Temperature Superposition Principle to lighten the calculations. In this regard, a stochastic characterisation for the Time–Temperature Superposition Principle method is proposed for a Gaussian stochastic temperature process.A numerical example, based on experimental data of an epoxy resin at different temperatures, is presented to simulate a creep test under a Gaussian stochastic temperature process with assigned power spectral density function. Comparison between the two considered methods is shown, and the accuracy of the proposed stochastic characterisation is assessed.

Analysis of Fractional Viscoelastic Material With Mechanical Parameters Dependent on Random Temperature

Abstract It is well known that mechanical parameters of polymeric materials, e.g., epoxy resin, are strongly influenced by the temperature. On the other hand, in many applications, the temperature is not known exactly during the design process and this introduces uncertainties in the prevision of the behavior also when the stresses are deterministic. For this reason, in this paper, the mechanical behavior of an epoxy resin is characterized by means of a fractional viscoelastic model at different temperatures; then, a simple method to characterize the response of the fractional viscoelastic material at different temperatures modeled as a random variable with assigned probability density function (PDF) subjected to deterministic stresses is presented. It is found that the first- and second-order statistical moments of the response can be easily evaluated only by the knowledge of the PDF of the temperature and the behavior of the parameters with the temperature. Comparison with Monte Carlo simulations is also performed in order to assess the accuracy and the reliability of the method.

Phase-averaged flow statistics in compressors using a rotated hot-wire technique

A technique based on a rotated hot wire has been developed to characterise the unsteady, three-dimensional flow field between compressor blade rows. Data are acquired from a slanted hot wire rotated through a number of orientations at each measurement point. Phase-averaged velocity statistics are obtained by solving a set of sensor response equations using a weighted, non-linear regression algorithm. The accuracy and robustness of the method were verified a priori by conducting a series of tests using synthetic data. The method is demonstrated by acquiring a full set of phase-averaged flow statistics in the wake of a compressor stator blade row. The technique allows three components of phase-averaged velocity, six components of phase-averaged deterministic stress, and six components of phase-averaged Reynolds stress to be recovered using a single rotated hot-wire probe.

Probabilistic Analysis of Stress Corrosion Crack Growth and Related Structural Reliability Considerations

The predetection evolution of stress corrosion cracking has been examined as a necessary preliminary to effective detection of such cracks. Anodic dissolution (AD) and hydrogen embrittlement (HE) have been considered to calculate the stress corrosion crack (SCC) growth in AA7050-T6 for a surface-breaking crack with blunt tip in an aqueous environment. Since these processes are not completely deterministic, several advanced statistical methods have been used to introduce probabilistic considerations. Based on the data from designed computer experiments, the computer code developed by the authors (Lee et al., 2015, “A Comprehensive Analysis of the Growth Rate of Stress Corrosion Cracks,” Proc. R. Soc. A, 471(2178), p. 20140703) to conduct deterministic stress corrosion crack growth analysis has been represented by metamodels using Gaussian process regression. Through sensitivity analysis, important variables which need to be calibrated have been identified. The dynamic Bayesian network (DBN) model and Monte Carlo simulation (MCS) have been utilized to quantify uncertainties. Statistical parameters of input variables have been obtained by a machine learning technique. The calibrated model has been validated using Bayesian hypothesis testing. Since the DBN model yields a probability of detection (POD) comparable to the probability based on binary validation data, the probabilistic model with calibrated parameters is expected to well represent the growth of a stress corrosion crack. The results also show that the reliability largely depends on the accuracy of flaw detection methods and on the critical crack length.

Irregular Time-Varying Stress Degradation Path Modeling: a Case Study on Lithium-ion Cell Degradation

The aim of this paper is to investigate the issue of degradation modeling and reliability assessment for products under irregular time-varying stresses. Conventional degradation models have been extensively used in the relevant literature to characterize degradation processes under deterministic stresses. However, the time-varying stress, which may affect degradation processes, widely exists in field conditions. This paper extends the general degradation-path model by considering the effects of time-varying stresses. The new degradation-path model captures influences of varying stresses on performance characteristics. A nonlinear least square method is used to estimate the unknown parameters of the proposed model. A bootstrap algorithm is adopted for computing the confidence intervals of the mean time to failure and percentiles of the failure-time distribution. Finally, a case study of lithium-ion cells is presented to validate the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.