Prediction of bendig load capacity of timber beams by finite element method simulation of knots and grain deviation

A finite element model was used to simulate timberbeams with defects and predict their maximum load in bending. Taking into account the elastoplastic constitutive law of timber, the prediction of fracture load gives information about the mechanisms of timber failure, particularly with regard to the influence of knots, and their local graindeviation, on the fracture. A finite element model was constructed using the ANSYS element Plane42 in a plane stress 2D-analysis, which equates thickness to the width of the section to create a mesh which is as uniform as possible. Three sub-models reproduced the bending test according to UNE EN 408: i) timber with holes caused by knots; ii) timber with adherent knots which have structural continuity with the rest of the beam material; iii) timber with knots but with only partial contact between knot and beam which was artificially simulated by means of contact springs between the two materials. The model was validated using ten 45 × 145 × 3000 mm beams of Pinus sylvestris L. which presented knots and graindeviation. The fracture stress data obtained was compared with the results of numerical simulations, resulting in an adjustment error less of than 9.7%

Multiple proportion case-basing driven CBRE and its application in the evaluation of possible failure of firms

Case-based reasoning (CBR) is a unique tool for the evaluation of possible failure of firms (EOPFOF) for its eases of interpretation and implementation. Ensemble computing, a variation of group decision in society, provides a potential means of improving predictive performance of CBR-based EOPFOF. This research aims to integrate bagging and proportion case-basing with CBR to generate a method of proportion bagging CBR for EOPFOF. Diverse multiple case bases are first produced by multiple case-basing, in which a volume parameter is introduced to control the size of each case base. Then, the classic case retrieval algorithm is implemented to generate diverse member CBR predictors. Majority voting, the most frequently used mechanism in ensemble computing, is finally used to aggregate outputs of member CBR predictors in order to produce final prediction of the CBR ensemble. In an empirical experiment, we statistically validated the results of the CBR ensemble from multiple case bases by comparing them with those of multivariate discriminant analysis, logistic regression, classic CBR, the best member CBR predictor and bagging CBR ensemble. The results from Chinese EOPFOF prior to 3 years indicate that the new CBR ensemble, which significantly improved CBRs predictive ability, outperformed all the comparative methods.

An experimental and numerical study of ductile failure under quasi-static and impact loadings of Inconel 718 nickel-base superalloy

A numerical and experimental study of ballistic impacts at various temperatures on precipitation hardened Inconel 718 nickel-base superalloy plates has been performed. A coupled elastoplastic-damage constitutive model with Lode angle dependent failure criterion has been implemented in LS-DYNA non-linear finite element code to model the mechanical behaviour of such an alloy. The ballistic impact tests have been carried out at three temperatures: room temperature (25 °C), 400 °C and 700 °C. The numerical study showed that the mesh size is crucial to predict correctly the shear bands detected in the tested plates. Moreover, the mesh size convergence has been achieved for element sizes on the same order that the shear bands. The residual velocity as well as the ballistic limit prediction has been considered excellent for high temperature ballistic tests. Nevertheless, the model has been less accurate for the numerical simulations performed at room temperature, being though in reasonable agreement with the experimental data. Additionally, the influence that the Lode angle had on quasi-static failure patterns such as cup-cone and slanted failure has been studied numerically. The study has revealed that the combined action of weakened constitutive equations and Lode angle dependent failure criterion has been necessary to predict the previously-mentioned failure patterns

A coupled elastoplastic-damage constitutive model with Lode angle dependent failure criterion

A coupled elastoplastic-damage constitutive model with Lode angle dependent failure criterion for high strain and ballistic applications is presented. A Lode angle dependent function is added to the equivalent plastic strain to failure definition of the Johnson–Cook failure criterion. The weakening in the elastic law and in the Johnson–Cook-like constitutive relation implicitly introduces the Lode angle dependency in the elastoplastic behaviour. The material model is calibrated for precipitation hardened Inconel 718 nickel-base superalloy. The combination of a Lode angle dependent failure criterion with weakened constitutive equations is proven to predict fracture patterns of the mechanical tests performed and provide reliable results. Additionally, the mesh size dependency on the prediction of the fracture patterns was studied, showing that was crucial to predict such patterns

Earthquake prediction: the interaction of public policy and science.

Earthquake prediction research has searched for both informational phenomena, those that provide information about earthquake hazards useful to the public, and causal phenomena, causally related to the physical processes governing failure on a fault, to improve our understanding of those processes. Neither informational nor causal phenomena are a subset of the other. I propose a classification of potential earthquake predictors of informational, causal, and predictive phenomena, where predictors are causal phenomena that provide more accurate assessments of the earthquake hazard than can be gotten from assuming a random distribution. Achieving higher, more accurate probabilities than a random distribution requires much more information about the precursor than just that it is causally related to the earthquake.

Statistical tests of load-unload response ratio signals by lattice solid model: Implication to tidal triggering and earthquake prediction

Statistical tests of Load-Unload Response Ratio (LURR) signals are carried in order to verify statistical robustness of the previous studies using the Lattice Solid Model (MORA et al., 2002b). In each case 24 groups of samples with the same macroscopic parameters (tidal perturbation amplitude A, period T and tectonic loading rate k) but different particle arrangements are employed. Results of uni-axial compression experiments show that before the normalized time of catastrophic failure, the ensemble average LURR value rises significantly, in agreement with the observations of high LURR prior to the large earthquakes. In shearing tests, two parameters are found to control the correlation between earthquake occurrence and tidal stress. One is, A/(kT) controlling the phase shift between the peak seismicity rate and the peak amplitude of the perturbation stress. With an increase of this parameter, the phase shift is found to decrease. Another parameter, AT/k, controls the height of the probability density function (Pdf) of modeled seismicity. As this parameter increases, the Pdf becomes sharper and narrower, indicating a strong triggering. Statistical studies of LURR signals in shearing tests also suggest that except in strong triggering cases, where LURR cannot be calculated due to poor data in unloading cycles, the larger events are more likely to occur in higher LURR periods than the smaller ones, supporting the LURR hypothesis.

Determinants of functional capacity in patients with chronic heart failure: Role of filling pressure and systolic and diastolic function

Background Previous work suggesting a better correlation of diastolic than systolic function with exercise capacity in heart failure may reflect the -relative insensitivity and load-dependence of ejection fraction (EF). We sought the correlation of new and more sensitive methods of quantifying systolic and diastolic function and filling pressure with functional capacity. Methods We studied 155 consecutive exercise tests on 95 patients with congestive heart failure (81 male, aged 62 +/- 10 years), who underwent resting 2-climensional echocardiography and tissue Doppler imaging before and after measurement of maximum oxygen uptake (peak VO2)Results The resting EF was 3 1 % 10% and a peak VO(2)was 13 +/- 5 mL/kg/min; the majority of these patients (80%) had an ischemic cardiornyopathy. Resting EF (r 0.14, P =.09) correlated poorly with peak VO2 and mean systolic (r = 0.23, P =.004) and diastolic tissue velocities (r 0.18, P =.02). Peak EF was weakly correlated with the mean systolic (r = 0.18, P =.02) and diastolic velocities (r = 0.16, P <.04). The mean sum of systolic and diastolic velocities in both annuli (r = 0.30, P <.001) and E/Ea ratio (r 0.31, P <.001) were better correlated with peak VO2 Prediction of peak VO2 was similar with models based on models of filling pressure (R = 0.61), systolic factors (R = 0.63), and diastolic factors (R 0.59), although a composite model of filling pressure, systolic and diastolic function was a superior predictor of peak VO2 (R 0.69; all P<.001). Conclusions The reported association of diastolic rather than systolic function with functional capacity may have reflected the limitations of EF. Functional capacity appears related not only to diastolic function, but also to systolic function and filling pressure, and is most closely associated with a combination of these factors.

Disease risk and mortality prediction in intensive care patients with pneumonia. Australian and New Zealand practice in intensive care (ANZPIC II)

This study of ventilated patients investigated pneumonia risk factors and outcome predictors in 476 episodes of pneumonia (48% community-acquired pneumonia, 24% hospital-acquired pneumonia, 28% ventilator-associated pneumonia) using a prospective survey in 14 intensive care units within Australia and New Zealand. For community acquired pneumonia, mortality increased with immunosuppression (OR 5.32, CI 95% 1.58-17.99, P < 0. 01), clinical signs of consolidation (OR 2.43, CI 95% 1.09-5.44, P = 0. 03) and Sepsis-Related Organ Failure Assessment (SOFA) scores (OR 1.19, CI 95% 1.08-1.30, P < 0. 001) but improved if appropriate antibiotic changes were made within three days of intensive care unit admission (OR 0.42, CI 95% 0.20-0.86, P = 0.02). For hospital-acquired pneumonia, immunosuppression (OR 6.98, CI 95% 1.16-42.2, P = 0.03) and non-metastatic cancer (OR 3.78, CI 95% 1.20-11.93, P = 0.02) were the principal mortality predictors. Alcoholism (OR 7.80, CI 95% 1.20-1750, P < 0.001), high SOFA scores (OR 1.44, CI 95% 1.20-1.75, P = 0.001) and the isolation of high risk organisms including Pseudomonas aeruginosa, Acinetobacter spp, Stenotrophomonas spp and methicillin resistant Staphylococcus aureus (OR 4.79, CI 95% 1.43-16.03, P = 0.01), were associated with increased mortality in ventilator-associated pneumonia. The use of non-invasive ventilation was independently protective against mortality for patients with community-acquired and hospital-acquired pneumonia (OR 0.35, CI 95% 0.18-0.68, P = 0.002). Mortality was similar for patients requiting both invasive and non-invasive ventilation and non-invasive ventilation alone (21% compared with 20% respectively, P = 0.56). Pneumonia risks and mortality predictors in Australian and New Zealand ICUs vary with pneumonia type. A history of alcoholism is a major risk factor for mortality in ventilator-associated pneumonia, greater in magnitude than the mortality effect of immunosuppression in hospital-acquired pneumonia or community-acquired pneumonia. Non-invasive ventilation is associated with reduced ICU mortality. Clinical signs of consolidation worsen, while rationalising antibiotic therapy within three days of ICU admission improves mortality for community-acquired pneumonia patients.

The appetitive motivation scale and other BAS measures in the prediction of Approach and Active Avoidance

The Appetitive Motivation Scale (Jackson & Smillie, 2004) is a new trait conceptualisation of Gray's (I 970 199 1) Behavioural Activation System. In this experiment we explore relationships that the Appetitive Motivation Scale and other measures of Gray's model have with Approach and Active Avoidance responses. Using a sample of 144 undergraduate students, both Appetitive Motivation and Sensitivity to Reward (from the Sensitivity to Punishment and Sensitivity to Reward Questionnaire, SPSRQ; Torrubia, Avila, Molto, & Ceseras, 2001), were found to be significant predictors of Approach and Active Avoidance response latency. This confirms previous experimental validations of the SPSRQ (e.g., Avila, 2001) and provides the first experimental evidence for the validity of the Appetitive Motivation scale. Consistent with interactive views of Gray's model (e.g., Corr, 2001), high SPSRQ Sensitivity to Punishment diminished the relationship between Sensitivity to Reward and our BAS criteria. Measures of BIS did not however interact in this way with the appetitive motivation scale. A surprising result was the failure for any of Carver and White's (1994) BAS scales to correlate with RST criteria. Implications of these findings and potential future directions are discussed. (C) 2004 Elsevier Ltd. All rights reserved.

Efffluent flux prediction in variably saturated soil zones within a septic tank-soil absorption trench

The treatment and hydraulic mechanisms in a septic tank-soil absorption system ( SAS) are highly influenced by the clogging layer or biomat zone which develops on bottom and lower sidewall surfaces within the trench. Flow rates through the biomat and sub-biomat zones are governed largely by the biomat hydraulic properties (resistance and hydraulic conductivity) and the unsaturated hydraulic conductivity of the underlying soil. One- and 2-dimensional models were used to investigate the relative importance of sidewall and vertical flow rates and pathways in SAS. Results of 1-dimensional modelling show that several orders of magnitude variation in saturated hydraulic conductivity (Ks) reduce to a 1 order of magnitude variation in long-term flow rates. To increase the reliability of prediction of septic trench hydrology, HYDRUS-2D was used to model 2-dimensional flow. In the permeable soils, under high trench loading, effluent preferentially flowed in the upper region of the trench where no resistant biomat was present (the exfiltration zone). By comparison, flow was more evenly partitioned between the biomat zones and the exfiltration zones of the low permeability soil. An increase in effluent infiltration corresponded with a greater availability of exfiltration zone, rather than a lower resistance of biomat. Results of modelling simulations demonstrated the important role that a permeable A horizon may play in limiting surface surcharge of effluent under high trench hydraulic loading.

Failure in composite materials

The economic and efficient exploitation of composite materials in critical load bearing applications relies on the ability to predict safe operational lives without excessive conservatism. Developing life prediction and monitoring techniques in these complex, inhomogeneous materials requires an understanding of the various failure mechanisms which can take place. This article describes a range of damage mechanisms which are observed in polymer, metal and ceramic matrix composites.

A facilities maintenance management process based on degradation prediction using sensed data

Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.

Identifying the Impact of Incomplete Datasets on Process Cycle Time Prediction in an Aerospace Assembly Line

Supply Chain Simulation (SCS) is applied to acquire information to support outsourcing decisions but obtaining enough detail in key parameters can often be a barrier to making well informed decisions.
One aspect of SCS that has been relatively unexplored is the impact of inaccurate data around delays within the SC. The impact of the magnitude and variability of process cycle time on typical performance indicators in a SC context is studied.
System cycle time, WIP levels and throughput are more sensitive to the magnitude of deterministic deviations in process cycle time than variable deviations. Manufacturing costs are not very sensitive to these deviations.
Future opportunities include investigating the impact of process failure or product defects, including logistics and transportation between SC members and using alternative costing methodologies.

Arterial stiffness and arteriovenous fistula failure of maturation

PURPOSE: Increased arterial stiffness is a common finding in patients with end-stage renal disease. Following creation of an arteriovenous fistula (AVF), appropriate dilation of the feeding artery must occur to facilitate AVF maturation. Arterial stiffness may impair the arterial dilation required to facilitate AVF development and contribute to subsequent failure to mature (FTM). The aim of this pilot study was to investigate the association between measurements of central and peripheral arterial stiffness, and AVF FTM.

METHODS: Patients undergoing AVF creation in a single centre (Belfast City Hospital, UK) between January and December 2015 were invited to have their carotid-femoral pulse wave velocity (PWV), brachial-radial PWV and augmentation index (AI) measured prior to AVF creation. Subsequent AVF outcomes were identified.

RESULTS: Fifty-nine patients who had an AVF procedure were included in the final analysis (mean age 62 years); 50.8% had diabetes mellitus. The mean pre-operative arterial diameter for all AVFs was 3.9 mm. Average values for carotid-femoral PWV were 9.5 m/s, brachial-radial PWV 7.7 m/s and AI 25.6%. Using logistic regression, these arterial stiffness parameters did not predict AVF FTM: carotid-femoral PWV (P = 0.20), brachial-radial PWV (P = 0.13), AI (P = 0.50).

CONCLUSIONS: This is the largest study to date exploring the association between arterial stiffness and AVF FTM. The measured central and peripheral arterial stiffness parameters were not associated with AVF FTM. Further research is needed to define if non-invasive arterial physiological measurements would be clinically useful in the prediction of AVF FTM.

Predictive Analytics and Decision Support for Heart Failure patients

Thesis (Master's)--University of Washington, 2016-08