Predicting ultrasonic grain noise in polycrystals: A Monte Carlo model

A Monte Carlo technique is described for predicting the ultrasonic noise backscattered from the microstructure of polycrystalline materials in a pulse/echo immersion inspection. Explicit results are presented for equiaxed, randomly oriented aggregates of either cubic or hexagonal crystallites. The model is then tested using measured noise signals. Average and peak noise levels and the distribution of the noise voltages are studied as the density of grains changes

Detectability of Small Flaws in Advanced Engine Alloys

As advanced materials are introduced into aircraft engines, operating under higher temperatures at greater stresses for longer lifetimes, the need to detect small, internal defects becomes increasingly important. Ultrasound is often the preferred inspection tool because of its ability to penetrate to the interior of a component. However, sound energy reflected from microstructural features in the component produces a background inspection noise which is seen even when no defects are present. This noise can inhibit the detection of sound energy reflected from critical internal defects such as cracks, pores, or inclusions. The primary objectives of this work are to develop a quantitative understanding of the factors which influence the detectability of small defects in advanced engine alloys, and to lay the foundation for an engineering methodology to predict detection capabilities. To focus the work we concentrate on the specific problem of ultrasonically detecting hard-alpha inclusions in titanium aircraft engine alloys. These inclusions result from excess local concentrations of oxygen or nitrogen which occasionally occur during processing. Such impurities tend to occupy interstitial sites and cause excess brittleness. An engineering understanding of their detectability requires three elements: (1) knowledge of the strength of the backscattered noise signals associated with normal microstructural inhomogeneities such as grain and phase boundaries; (2) knowledge of the strength of the competing ultrasonic signal reflected by the inclusion; and (3) the use of this information to predict quantities which bear on the probability of detection. Major progress was made in each of these three areas. In the course of the project, three models were developed for the prediction of absolute noise levels in normal-incidence, pulse/echo, ultrasonic immersion inspections. These are identified as the Independent Scattering Model for Tone Burst pulse inspections (ISMTB), the Independent Scattering Model for Broad Band pulse inspections (ISMBB), and the Monte-Carlo noise Model (MCM). Each model assumes that the backscattered noise is primarily due to single scattering by the individual grains in the metal specimen, and the models consequently apply to low-noise materials. The observed absolute noise level in a given setting will depend upon the microstructure of the specimen, and upon the details of the measurement system (e.g., the transducer and pulsing unit used, the inspection waterpath, the amplifier gain settings, etc.) Both types of dependencies are incorporated into our models. In the ISMTB and ISMBB, the dependence on microstructure enters primarily through a Figure-of-Merit (FOM) for inherent noise severity, which is a property of the specimen alone and is determined by the density of grains and the average scattering capability of a single grain. These two models relate the FOM and measurement system parameters to average noise characteristics, such as the position-averaged root-mean-square (rms) noise level. Either the ISMTB or ISMBB can be employed in two distinct ways: to deduce the FOM of a specimen from measured noise signals; or to predict average absolute noise levels for various inspection scenarios when the FOM is known. For the MCM, the microstructural inputs are more detailed, but predicted noise properties are more detailed as well: e.g., both peak and average noise levels can be estimated. In our report we document the underlying assumptions and mathematical development for each noise model, and we report on extensive experimental studies carried out to validate the models. For single-phased, equiaxed, randomly-oriented metals it is possible to estimate the FOM from photographs of the microstructure and knowledge of the elastic constants. The FOM value so obtained can be directly compared to that deduced from our model-dependent analysis of backscattered noise. The two values are generally found to agree to within a factor of 2. This level of agreement is considered to be quite good since the noise model contains no adjustable parameters and the predicted average noise level is typically 50-60 dB below a measured front-surface reference signal. For two-phase commercial titanium alloys, it is not yet feasible to determine the FOM from microphotographs and related information. However, it is straightforward to determine the FOM by analyzing backscattered noise data. In such cases the deduced FOM is found to be approximately independent of the measurement system parameters, as expected. However, the FOM has been found to vary significantly from specimen to specimen in a suite of commercial alloys, and with direction within a given specimen. These variations are believed to originate from macrostructural details related to the processing history of the specimen. We describe how particular etching and photographic methods can be used to reveal this macrostructure, and how supporting data can be obtained from x-ray diffraction studies. To estimate the strength of ultrasonic signals reflected from hard-alpha inclusions, one requires a knowledge of how the elastic moduli and density of the inclusions differ from those of the host alloy in which they reside. Based on reviews of the literature plus additional experiments conducted as needed, the influence of interstitial oxygen and nitrogen on those properties has been determined. It is clear that, at solute concentrations of a few percent, there are sufficient changes in the moduli to produce significant ultrasonic signals from hard-alpha inclusions in single-phase microstructures. In two-phase titanium alloys, the hardening of the alpha phase can be accompanied by a conversion of the beta phase to alpha. When it occurs, this conversion may diminish the impedance difference between the inclusion and host metal, and consequently make ultrasonic detection more difficult. For specific, reasonable choices of hard-alpha properties, we have used previously developed models to predict absolute defect signal amplitudes for a range of inclusion diameters. These have been combined with noise model predictions to obtain estimates of signal-to-noise (SIN) ratios for hard-alpha inclusions in representative titanium alloys. Such calculations were performed for hypothetical inspections using both focussed and planar transducers. The calculations indicate that the SIN ratio is approximately inversely proportional to the width of the incident sound beam in the vicinity of the defect. Thus, defect detection can be substantially improved by properly focussing and scanning the beam in the interior of the component being inspected. In addition to performing illustrative SIN calculations, we have developed approximate formulas which allow rapid estimation of relative and absolute SIN ratios. These can be used to estimate the optimal choices of transducer diameter, focal length, and waterpath for inspecting a given region of the component\u27s interior. Much of the formalism developed in this work is fairly general in scope, and is consequently applicable to a wide range of defect-detection problems. Our noise models and associated formulas for SIN ratios can be readily extended to the case of normal-incidence inspection through a curved water/metal interface, and such extensions are currently in progress under different sponsorship. These developments will allow one to estimate SIN ratios for simulated inspections of cylindrical metal billets, and hence to determine the optimum inspection parameters. Straightforward extensions to oblique-incidence inspections are also feasible. The SIN ratio alone cannot be used to fully assess the probability of flaw detection (POD). POD calculations require a complete understanding of both mean noise levels, and the manner in which the noise varies about its mean. Although we have made a good start toward understanding and quantifying the relationship between average and peak noise levels, more work is required on that front. The above accomplishments may be summarized as follows: • Developed experimental techniques and data-acquisition software for measuring noise levels and noise spectra. • Developed three models for predicting absolute backscattered noise levels (and other noise characteristics) seen in a given UT inspection: ISMTB: For toneburst-pulse inspections. Predicts rms average noise level. ISMBB: For broadband-pulse inspections. Predicts rms average spectral components. Monte-Carlo Model: For arbitrary pulse types. Predicts typical noise wave-forms, and hence any average or peak noise characteristic. The first two models relate backscattered ultrasonic noise to a frequency-dependent material figure-of-merit (FOM) and to details of the measurement system. • Performed numerous tests of the models using noise data gathered from specimens with simple microstructures (Cu, Stainless Steel, Alpha-Ti) and from titanium alloy specimens supplied by engine manufacturers. • Demonstrated (in collaboration with J. H. Rose) that the FOM could be predicted from first principles for single-phased, equi-axed, randomly-oriented microstructures. • Measured and analyzed noise data from representative Ti-6246 specimens. Noted strong dependence of noise level on direction of sound propagation in some specimens. • Used x-ray diffraction to investigate the sources of the noise anisotropy. It is now thought to arise from localized texture within the boundaries of prior beta grains . • Prepared specimens containing artificial hard-alpha material (oxygen contaminated case layer, nitrogen contaminated volumes). Measured sound speeds. Analyzed results using theories based on rule of mixtures . • Demonstrated how hard-alpha detectability could be assessed by combining noise models with models which predict echoes from defects. • Predicted signal-to-noise ratios for focussed and planar transducer inspections of embedded hard-alpha inclusions of various diameters. We have thus developed a firn scientific foundation for understanding the interrelationship of material and measurement parameters in determining the detectability of small flaws, particularly hard-alpha inclusions in titanium alloys. The next steps in the application of this knowledge should include: 1.) more extensive validation studies in collaboration with potential users; 2.) their use of the models to optimize the design of inspection systems for billets and other components where normal-incidence inspection is preferred; and 3.) use of the models to improve the quantification of detection reliability based on an analysis of field and laboratory data

Survey of Ultrasonic Grain Noise Characteristics in Jet Engine Titanium

In ultrasonic inspections of titanium billets and forgings, grain noise echoes are routinely observed. These arise from the scattering of the incident sound beam by the metal microstructure, and can limit the detection of small or subtle defects. We report on a survey of grain noise characteristics in fourteen billet and forging specimens supplied by aircraft engine manufacturers. All specimens were examined in a similar manner using a 5-MHz focussed transducer, with pulse/echo noise measurements made through three orthogonal sides of each specimen. Emphasis is placed on describing two related probability density functions (PDF’s) which characterize aspects of the backscattered noise seen in a scanning experiment. The first PDF describes the RF noise voltages seen at a fixed observation time t; the second describes the gated peak-to-peak noise voltages seen for time gates of various durations. The PDF for the RF noise voltages is expected to be Gaussian if a large number (\u3e10) of grains contribute appreciably to the noise at time t [1], but non-Gaussian behavior is seen in some specimens. The use of K-distributions to describe the non-Gaussian cases is examined. This work is in support of efforts described in a companion article [2] to develop methods for predicting gated peak noise (GPN) distributions

Coupling Microstructure Outputs of Process Models to Ultrasonic Inspectability Predictions

The efforts of the materials community can be characterized as the study of the relationship of processing, structure, properties and performance, as schematically illustrated in Figure 1. Added, in parentheses, are quantities of importance when these ideas are applied to ultrasonic NDE. It would be highly desirable if one could start from models of processes such as rolling, casting and extrusion; predict the microstructural features produced, such as grain size or shape, texture (preferred grain orientation), or the two-point correlation of elastic constants (to be discussed later); predict the resulting ultrasonic properties such as velocity v, attenuation a and backscattering coefficient η; and ultimately determine the inspectability of the part. Such a capability would allow NDE to be considered explicitly during the selection of material processing procedures

Adverse maternal, fetal, and newborn outcomes among pregnant women with SARS-CoV-2 infection: an individual participant data meta-analysis

Introduction: Despite a growing body of research on the risks of SARS-CoV-2 infection during pregnancy, there is continued controversy given heterogeneity in the quality and design of published studies. Methods: We screened ongoing studies in our sequential, prospective meta-analysis. We pooled individual participant data to estimate the absolute and relative risk (RR) of adverse outcomes among pregnant women with SARS-CoV-2 infection, compared with confirmed negative pregnancies. We evaluated the risk of bias using a modified Newcastle-Ottawa Scale. Results: We screened 137 studies and included 12 studies in 12 countries involving 13 136 pregnant women. Pregnant women with SARS-CoV-2 infection—as compared with uninfected pregnant women—were at significantly increased risk of maternal mortality (10 studies; n=1490; RR 7.68, 95% CI 1.70 to 34.61); admission to intensive care unit (8 studies; n=6660; RR 3.81, 95% CI 2.03 to 7.17); receiving mechanical ventilation (7 studies; n=4887; RR 15.23, 95% CI 4.32 to 53.71); receiving any critical care (7 studies; n=4735; RR 5.48, 95% CI 2.57 to 11.72); and being diagnosed with pneumonia (6 studies; n=4573; RR 23.46, 95% CI 3.03 to 181.39) and thromboembolic disease (8 studies; n=5146; RR 5.50, 95% CI 1.12 to 27.12). Neonates born to women with SARS-CoV-2 infection were more likely to be admitted to a neonatal care unit after birth (7 studies; n=7637; RR 1.86, 95% CI 1.12 to 3.08); be born preterm (7 studies; n=6233; RR 1.71, 95% CI 1.28 to 2.29) or moderately preterm (7 studies; n=6071; RR 2.92, 95% CI 1.88 to 4.54); and to be born low birth weight (12 studies; n=11 930; RR 1.19, 95% CI 1.02 to 1.40). Infection was not linked to stillbirth. Studies were generally at low or moderate risk of bias. Conclusions: This analysis indicates that SARS-CoV-2 infection at any time during pregnancy increases the risk of maternal death, severe maternal morbidities and neonatal morbidity, but not stillbirth or intrauterine growth restriction. As more data become available, we will update these findings per the published protocol

Progesterone resistance in endometriosis is modulated by the altered expression of microRNA-29c and FKBP4

Context: Endometriosis results in aberrant gene expression in the eutopic endometrium (EuE) and subsequent progesterone resistance. MicroRNA (miR) microarray data in a baboon model of endometriosis showed an increased expression of miR-29c. Objectives: To explore the role of miR-29c in progesterone resistance in a subset of women with endometriosis. Design: MiR-29c expression was analyzed in the endometrium of baboons and women with or without endometriosis. The role in progesterone resistance and decidualization was analyzed by transfecting human uterine fibroblast cells with miR-29c. Patients: Subjects diagnosed with deep infiltrative endometriosis (DIE) by transvaginal ultrasound with bowel preparation underwent surgical excision of endometriosis. Eutopic secretory endometrium was collected pre- and postoperatively. Women with normal EuE and without DIE served as controls. Results: Quantitative reverse transcription polymerase chain reaction demonstrated that miR-29c expression increased, while the transcript levels of its target, FK506-binding protein 4 (FKBP4), decreased in the EuE of baboons following the induction of endometriosis. FKBP4 messenger RNA and decidual markers were statistically significantly decreased in decidualized human uterine fibroblast cells transfected with a miR-29c mimic compared with controls. Human data corroborated our baboon data and demonstrated higher expression of miR-29c in endometriosis EuE compared with normal EuE. MiR-29c was significantly decreased in endometriosis EuE postoperatively compared with preoperative tissues, and FKBP4 showed an inverse trend following radical laparoscopic resection surgery. Conclusions: We demonstrate that miR-29c expression is increased in EuE of baboons and women with endometriosis, which might contribute to a compromised progesterone response by diminishing the levels of FKBP4. Resection of DIE is likely to reverse the progesterone resistance associated with endometriosis in women

COVID-19 length of hospital stay: a systematic review and data synthesis.

BACKGROUND: The COVID-19 pandemic has placed an unprecedented strain on health systems, with rapidly increasing demand for healthcare in hospitals and intensive care units (ICUs) worldwide. As the pandemic escalates, determining the resulting needs for healthcare resources (beds, staff, equipment) has become a key priority for many countries. Projecting future demand requires estimates of how long patients with COVID-19 need different levels of hospital care. METHODS: We performed a systematic review of early evidence on length of stay (LoS) of patients with COVID-19 in hospital and in ICU. We subsequently developed a method to generate LoS distributions which combines summary statistics reported in multiple studies, accounting for differences in sample sizes. Applying this approach, we provide distributions for total hospital and ICU LoS from studies in China and elsewhere, for use by the community. RESULTS: We identified 52 studies, the majority from China (46/52). Median hospital LoS ranged from 4 to 53 days within China, and 4 to 21 days outside of China, across 45 studies. ICU LoS was reported by eight studies-four each within and outside China-with median values ranging from 6 to 12 and 4 to 19 days, respectively. Our summary distributions have a median hospital LoS of 14 (IQR 10-19) days for China, compared with 5 (IQR 3-9) days outside of China. For ICU, the summary distributions are more similar (median (IQR) of 8 (5-13) days for China and 7 (4-11) days outside of China). There was a visible difference by discharge status, with patients who were discharged alive having longer LoS than those who died during their admission, but no trend associated with study date. CONCLUSION: Patients with COVID-19 in China appeared to remain in hospital for longer than elsewhere. This may be explained by differences in criteria for admission and discharge between countries, and different timing within the pandemic. In the absence of local data, the combined summary LoS distributions provided here can be used to model bed demands for contingency planning and then updated, with the novel method presented here, as more studies with aggregated statistics emerge outside China

A review on nanocellulosic fibres as new material for sustainable packaging: process an applications

The demand for exploring advanced and eco-friendly sustainable packaging materials with superior physical, mechanical and barrier properties is increasing. The materials that are currently used in packaging for food, beverage, medical and pharmaceutical products, as well as in industrial applications, are non-degradable, and thus, these materials are raising environmental pollution concerns. Numerous studies have been conducted on the utilization of bio-based materials in the pursuit of developing sustainable packaging materials. Although significant improvements have been achieved, a balance among environmental concerns, economic considerations and product packaging performance is still lacking. This is likely due to bio-based materials being used in product packaging applications without a proper design. The present review article intends to summarize the information regarding the potential applications of cellulosic nanofiber for the packaging. The importance of the design process, its principles and the challenges of design process for sustainable packaging are also summarized in this review. Overall it can be concluded that scientists, designers and engineers all are necessarily required to contribute towards research in order to commercially exploit cellulose nanofiber for sustainable packaging