Defect Dimensions Research Articles

Forecasting The Impact of the 2023 Current Procedural Terminology Coding Changes On Ventral Hernia Work Relative Value Units. A Cross-Sectional Study

BackgroundIn January 2023, significant changes were implemented to ventral hernia repair Current Procedural Terminology codes, with new codes replacing previous codes. The new codes were assigned a 0-day global period. The impact of these changes on clinical productivity remains unclear. Our objective was to forecast the impact of Current Procedural Terminology changes on ventral hernia-related work relative value units using historical data. MethodsVentral hernia repairs performed between March 2021 and December 2022 on adults by a single surgeon with available 90-day follow-up were retrospectively retrieved from the Abdominal Core Health Quality Collaborative. Demographic, hernia, and operative and postoperative data were collected. The ventral hernia repairs were coded twice using the previous and new Current Procedural Terminology codes, and work relative value units were calculated using both systems. The median work relative value units per case were compared using the Wilcoxon signed-rank test. ResultsA total of 143 ventral hernia repairs were included. The median age was 59 years, and 50% of patients were male. Median hernia width and length were 3.5 and 5.0 cm, respectively. The most common ventral hernia types were incisional 57% and umbilical 33%. Twenty percent of hernias were recurrent, and 99% were elective repairs. 49% of the procedures were open, 30% robotic, and 21% laparoscopic. Component separation was performed in 16%. The median length of stay was 0.0, and the median number of 90-day outpatient postoperative visits was 1.0. The new Current Procedural Terminology coding system was associated with a higher median 90-day work relative value units per case (14.1) than the previous system (13.8) (P = .002). Subset analysis identified statistically higher median 90-day work relative value units per case using the new versus previous Current Procedural Terminology codes for hernias with the largest defect dimension >10 cm (23.3 vs 18.8), umbilical/epigastric/Spigelian hernias (9.2 vs 7.1), recurrent hernias (20.1 vs 17.3) and open ventral hernia repairs (9.8 vs 7.1), all P < .05. Median 90-day work relative value units per case were statistically lower using the new versus previous codes for non-recurrent (11.6 vs 13.8) and incarcerated/strangulated (14.8 vs 14.9) hernias, all P < .05. In the new coding system, postoperative care within 90-days contributed to a median of 1.3 work relative value units per case (9% of total 90-day work relative value units). ConclusionWe forecast that in our practice, the 2023 ventral hernia repair Current Procedural Terminology changes will result in a modest impact on clinical productivity. The impact of these changes on a particular practice depends on surgical practice patterns and ventral hernia case mix.

Performance of axially loaded slender circular CFSTs with random local corrosion

The performance of axially loaded slender circular concrete-filled steel tubes with random local corrosion was investigated in this paper through experimental and numerical study. Specifically, the randomness of corrosion included the random locations along the column height, irregular corrosion profile, and uneven corrosion surface. In the experimental study, machining defects are employed to simulate local corrosion, and five slender CFSTs were tested, with four containing the defect located at different member heights and one intact specimen. Additionally, a numerical study is conducted to consider the random nature of local corrosion in terms of random locations, irregular profiles, and uneven surfaces. A parametric analysis is then conducted, with varying parameters such as defect dimensions, locations, material strengths, steel ratio, and slenderness ratio. The analysis finds that the ultimate strength of the slender member is influenced by the location and dimensions of the local defect. Some sightly corrosion occurring in the column end has negligible influence on the performance of slender members. A method based on the controlled section is proposed for calculating the ultimate strength of slender circular CFSTs with random local corrosion, yielding accurate results.

Data-driven algorithm based on the scaled boundary finite element method and deep learning for the identification of multiple cracks in massive structures

Structural defect identification is a vital aspect of structural health monitoring used to assess the safety of engineering structures. However, quantitatively determining the dimensions of structural defects is often difficult. Therefore, this study presents an innovative data-driven algorithm that combines the scaled boundary finite element method (SBFEM) and a deep learning framework based on a dilated causal convolutional neural network (CNN) to identify crack-like defects in large-scale structures. The SBFEM is used to simulate different crack-like defects. Mesh generation is significantly simplified by a simple procedure that requires only changing the scale centre at the crack tip and the positions of the nodes at the crack opening. This minimises remeshing and enables simple generation of sufficient data to train the neural network. In addition, an absorbing boundary model based on Rayleigh damping is used to avoid computing the entire model when simulating wave propagation in massive structures. To ensure that sequential data remain ordered and to obtain a large receptive field without increasing the complexity of the neural network, a dilated causal CNN is employed in the deep learning framework. Therefore, more historical information is captured, and the complex mapping relationship between the echo signal and the crack information is efficiently learnt. The proposed model can accurately identify the number, location, and depth of cracks in massive structures. Moreover, it is robust to noise, which is demonstrated via numerical examples. Therefore, the proposed algorithm provides valuable insight into the detection and diagnosis of structural defects, which can ultimately improve the safety of engineering structures.

A transvaginal ultrasound-based diagnostic calculator for uterus post-cesarean scar defect

BackgroundA cesarean scar defect (CSD) is incomplete healing of the myometrium at the site of a prior cesarean section (CS), complicating more than half of all cesarean sections. While transvaginal ultrasound (TVU) is the most common modality for diagnosing this defect, hysteroscopy remains the gold standard. We aimed to develop an efficient diagnostic tool for CSD among women with abnormal uterine bleeding (AUB) by integrating TVU findings and participants’ demographic features.MethodsA single-center cross-sectional study was conducted on 100 premenopausal and non-pregnant women with a history of CS complaining of AUB without a known systemic or structural etiology. Each participant underwent a hysteroscopy followed by a TVU the next day. The defect dimensions in TVU, patients’ age, and the number of previous CSs were integrated into a binary logistic regression model to evaluate their predictive ability for a hysteroscopy-confirmed CSD.ResultsHysteroscopy identified 74 (74%) participants with CSD. The variables age, the number of CSs, defect length, and defect width significantly contributed to the logistic regression model to diagnose CSD with odds ratios of 9.7, 0.7, 2.6, and 1.7, respectively. The developed model exhibited accuracy, sensitivity, and specificity of 88.00%, 91.89%, and 76.92%, respectively. The area under the receiver operating curve was 0.955 (P-value < 0.001).ConclusionAmong non-pregnant women suspected of CSD due to AUB, looking at age, the number of previous CSs, and TVU-based defect width and length can efficiently rule CSD out.

Application of double layer with collagen-elastin matrix (Matriderm®) and polyglycolic acid sheet (Neoveil®) for oroantral and oronasal fistula closure after maxillectomy: a retrospective single center experience

PurposeThis study investigates the effectiveness of a new double-layer approach for closing oroantral and oronasal fistulas (OA/ONFs) using Matriderm® and Neoveil®. Matriderm®, an acellular dermal matrix composed of collagen and elastin fibers, supports tissue regeneration, while Neoveil®, a biodegradable mesh sheet, serves as a barrier to prevent leakage and scarring. Material and MethodsA retrospective study of 12 maxillectomy patients with oral cancer between January 2022 and May 2023 was conducted. Patient data, including tumor stage, bone invasion, and defect size, were analyzed. Surgical techniques included sinus mucosa preservation, and either buccal fat grafting combined with the double layer technique or the double layer technique alone, with statistical analysis performed using R software to evaluate outcomes. ResultsThe results indicate a 41.7% incidence rate of fistula formation with lower T stages, absence of bone invasion, smaller defect dimensions, and intact sinus mucosa correlating with reduced fistula risk (p < 0.05). Notably, no patients required fistula-related surgical revisions, validating the efficacy of the approach. ConclusionThis study introduced a novel double-layer technique using Matriderm® and Neoveil® for closing OA/ONFs after maxillectomy. The technique demonstrated promising outcomes in addressing these post-operative complications. Lower tumor stages, no bone invasion, smaller defects, and intact sinus mucosa correlated with reduced fistula risk. This technique holds potential to enhance maxillectomy outcomes, offering a comprehensive approach to functional concerns, but warrants further investigation.

Bipaddle Pectoralis Major Myocutaneous Flap (PMMC) for Complex Composite Oral Cavity Defects: An Experience of a Tertiary Cancer Centre.

Although microvascular free flaps are considered the first choice in head and neck cancer defect reconstruction, their use is limited in developing regions by availability of resources and the expertise .The Bipaddle pectoralis major myocutaneous flap (PMMC flap) is a commonly used flap in head and neck cancer reconstruction, but in literature flap is associated with high incidence of drawbacks including donor site morbidity and added bulk of the flap reducing cosmetics and function. The purpose of the study is to evaluate the Bipaddle PMMC flap reliability, operative technique and outcome in reconstructive head and neck cancer surgery in the era of microvascular free flaps. Its a prospective study in which the records of 50 patients treated with Bippadle PMMC flap reconstruction between January 2022 to July 2022 were systematically collected and reviewed. Data of recipient site, serum albumin, history of adjuvant, recurrence, defect dimension, type of donor site closure, length of hospital stay, postoperative complications and outcomes were analysed. There were 45 males and 5 females with a mean age of 41 years (31-60). Bipaddle PMMC flap reconstruction was done in all patients of advanced squamous cell carcinoma of oral cavity. There were two males with complete necrosis of flap salvaged with latissimus dorsi flap and forehead flap. Minor infections were noted in two female and one male patient, managed conservatively and recovered well with acceptable final outcome. The Bipaddle PMMC flap is reliable for large defects in head and neck reconstructive surgery, particularly when a bulky flap is required to reconstruct composite defects where the lesion is involving the skin. Placing the flap horizontally with inclusion of nipple and areola in most of the patients increased the reach and size of available flap.

Magnetic Flux Leakage Testing Method for Pipelines with Stress Corrosion Defects Based on Improved Kernel Extreme Learning Machine

This study aims to study the safety of oil and gas pipelines under stress corrosion conditions and grasp the corrosion damage situation timely and accurately. Consequently, a non-destructive testing method combining magnetic flux leakage testing technology and a kernel function extreme learning machine improved by genetic algorithm (GA-KELM) is proposed. Firstly, the variation of the corrosion defect dimension and profile with time is obtained by numerical simulation. At the same time, the distribution of the magnetic flux leakage signal under different defect conditions is analyzed and studied. Finally, feature selection is carried out on the magnetic flux leakage signal distribution curve, and GA-KELM is used to predict the depth and length of corrosion defects so as to realize the non-destructive testing of the pipeline defects. The results show that different geometric features result in different magnetic flux leakage signal distributions. There is a corresponding relationship between the defect dimension and extreme value, area, and peak width of the magnetic flux leakage signal distribution curve. The GA-KELM prediction model can effectively predict the depth and length of corrosion defects, and the prediction accuracy is better than the traditional extreme learning machine prediction model.

Cortical Mandibular Bone Blocks Grafts and Piezoelectric Surgery in Complex Anterior Maxillary Alveolar Defects: A Case Report and Literature Review

The aim of this study is to assess the indication and efficacy of alveolar ridge reconstructions for complex horizontal and vertical augmentation procedures in the maxillary anterior area with Cortical Mandibular Bone Block Grafts (CMBBG). Localized alveolar three-dimensional bone defects are among the most challenging problems in surgical implant dentistry. Treatment protocols, such as short implants or small diameter implants are not always offering the desired clinical and esthetic results. The autogenous augmentation procedure can serve as an option, which allows a more biological reconstruction of the vertical and horizontal dimension of a complex bone defect in order to obtain sound replicas of natural teeth. The clinical case of a cortical autogenous block graft in an anterior complex maxillary defect is presented along with a literature review. The presented case and the selected articles demonstrate that cortical ramus bone block grafts show relatively low graft resorption, low donor site morbidity and high implant success rates.

Eccentric performance of slender CFST with machining defects representing local corrosion

This paper presents an experimental study on the mechanical performance of circular concrete-filled steel tubular beam-column specimens with simulated local corrosion. Thirteen specimens (including nine specimens with simulated local corrosion and four intact specimens) were tested. Machining defects represented the simulated local corrosion. The main test parameters include defect dimensions (length, width, and depth), defect shape, eccentricity, and slenderness. The effects of these parameters on failure modes, load-mid span deflection relations, and ductility on circular concrete-filled steel tubular beam-column specimens were revealed based on the test results. Finally, considering the characteristic of local corrosion, simplified calculation methods are proposed by modifying the calculation methods of cross-sectional capacity and flexural capacity of the composite section in current codes and verified against the experimental results.

CONCRETE CORE DEFECTS TOMOGRAPHIC IMAGINATION FOR MESOSCALE CFST MEMBERS USING STRESS WAVE MEASUREMENT

To visualize concrete core void defects in concrete-filled steel tube (CFST) members considering the mesoscale heterogeneity and randomness of concrete core is critical in practice. A stress wave travelling time tomography imagination method using piezoelectric-lead-zirconium-titanate (PZT) patches as actuators or sensors is proposed and validated numerically. A two-dimensional (2D) multi-physics and mesoscale coupling CFST-PZT model composed of number of PZT actuators and sensors, steel tubes, and concrete core with randomly distributed circular aggregates is established. The first stress wave arrival times of the mesoscale coupling CFST-PZT model without or with a concrete core void defect are recorded by PZT sensors when a PZT actuator is excited by pulse signals. A random walking algorithm (RWA) with the Snell laws is employed to determine the shortest wave travel path between each PZT actuator and each PZT sensor. Finally, the velocity fields of the mesoscale coupling models are identified using a simultaneous iterative reconstruction technique (SIRT) to minimize the difference between the first arrival time of the stress wave and the shortest wave travel time. Results show that the location and dimension of the void defect in the models with heterogeneous concrete core can be imaged with acceptable resolution.

Temperature and geometry impact on defect detection and sizing

Increasing requirements to minimize the frequency and duration of shutdowns of nuclear power plants have led to the need to address the implementation of ultrasonic testing of welded pipe connections at operating temperature. In practice, the pipes are made of carbon and stainless steel. Laboratory ultrasound tests were performed on two types of test pieces with different geometry and with homogeneous and heterogenous welds. The measurement was done within a temperature range of 50°C to 200°C in increment of 50°C. The aim of the performed measurements was to verify the detection of artificial defects created by electric discharge machining (EDM) in the root area of the weld on the carbon steel side by a selected test system and an impact of the change in focal laws (FLs) due to temperature on sizing. Together with this was evaluated the influence of elevated temperature on the determination of defect dimensions and impact of the test system, including ultrasonic, cooling, and handling subsystems for detection, sizing and using in the limited space of nuclear power plants. An inspection procedure and a safe workflow were created ss part of the testing. Both procedures were necessary for testing at elevated temperatures from the point of view of occupational safety and for carrying out individual test steps to maintain the repeatability of testing. The inspection procedure was subsequently qualified.

A physics-based defect tolerant design approach to predict the tensile performance of aluminium alloys with a defect

Inherent manufacturing defects are observed in additively manufactured and casted metallic alloys. During loading, the stress concentration due to defect results in poor tensile ductility and fatigue performance. A physics-based defect tolerant design approach is used in the present work to calculate the uniaxial tensile performance of cast ADC12 Aluminum alloys. The proposed model elucidates the correlation between tensile ductility and the dimensions of material defects. It derives a material constant referred to as the critical defect size, which is determined through a combination of uniaxial tensile testing on specimens with defects and employing finite element simulations. The proposed approach calculates well the tensile properties such as complete tensile stress–strain curve, ultimate tensile strength, and uniaxial tensile elongation.

Advanced Ultrasonic Inspection of Thick-Section Composite Structures for In-Field Asset Maintenance.

An investigation into the inspection capabilities of in-field advanced ultrasound detection for use on ultra-thick (20 to 100 mm) glass fibre-reinforced polyester composites is presented. Plates were manufactured using custom moulding techniques, such that delamination flaws were created at calibrated depths. The full matrix capture technique with an on-board total focussing method was used to detect flaws scanned by a 0.5 MHz linear array probe. Flaw through-thickness dimensions were altered to assess the threshold for crack face separation at which delaminations could be identified. Furthermore, part thickness and in-plane flaw dimensions were varied to identify the inspection capability limitations of advanced ultrasonics for thick composites. The results presented in this study demonstrate an inverse relationship between the ability to find delaminations and plate thicknesses, with inspections successful at depths up to 74 mm. When the delamination thickness exhibited surface-to-surface contact, the inspection capability was reduced to 35 mm. There was an exponential decay relationship between the accuracy of the flaw depth measurement and plate thickness, likely due to the necessity of low probe frequencies. The effective inspection depth was determined to be in the range of 1 to 20 times the wavelength. It is speculated that the accuracy of measurements could be improved using probes with novel coupling solutions, and detectors with optimised signal processing/filtration algorithms.

Comparison of cone-beam and fan-beam computed tomography and low-field magnetic resonance imaging for detection of proximal phalanx dorsoproximal osteochondral defects.

Dorsoproximal osteochondral defects commonly affect the proximal phalanx, but information about diagnosis on computed tomography (CT) and magnetic resonance imaging (MRI) is limited. To assess CT and MRI diagnoses of osteochondral defects, describe the lesions and compare sensitivity and specificity of the modalities using macroscopic pathology as gold standard. Cross-sectional study. Thirty-five equine cadaver limbs underwent standing cone-beam CT (CBCT), fan-beam CT (FBCT), low-field MRI and pathological examination. CT and MR images were examined for proximal phalanx dorsomedial and dorsolateral eminence osteochondral defects. Defect dimensions were measured. Imaging diagnoses and measurements were compared with macroscopic examination. Fifty-six defects were seen over 70 potential locations. On CBCT and FBCT, osteochondral defects appeared as subchondral irregularity/saucer-shaped defects. On MRI, osteochondral defects were a combination of articular cartilage defect on dorsal images and subchondral flattening/irregularity on sagittal images. Subchondral thickening and osseous short tau inversion recovery hyperintensity were found concurrent with osteochondral defects. Compared with pathological examination, the sensitivity and specificity of diagnosis were 86% (95% confidence interval [95% CI] 75%-93%) and 64% (95% CI 38%-85%) for FBCT; 64% (95% CI 51%-76%) and 71% (95% CI 46%-90%) for CBCT; and 52% (95% CI 39%-65%) and 71% (95% CI 46%-90%) for MRI. Sensitivity of all modalities increased with defect size. Macroscopic defect dimensions were strongly correlated with CBCT (r = 0.76, p < 0.001) and moderately correlated with FBCT and MRI (r = 0.65, p < 0.001). Macroscopic measurements were significantly greater than all imaging modality dimensions (p < 0.001), potentially because macroscopy included articular cartilage pathology. Influence of motion artefact could not be assessed. Osteochondral defects could be visualised using both CT and MRI with sensitivity increasing with defect size. Diagnostic performance was best using FBCT, followed by CBCT then MRI, but CBCT-measured defect size best correlated with macroscopic examination. MRI provided useful information on fluid signal associated with defects, which could represent active pathology.

Irreversibility, QNEC, and defects

We first present an analysis of infinitesimal null deformations for the entanglement entropy, which leads to a major simplification of the proof of the C, F and A-theorems in quantum field theory. Next, we study the quantum null energy condition (QNEC) on the light-cone for a CFT. Finally, we combine these tools in order to establish the irreversibility of renormalization group flows on planar d-dimensional defects, embedded in D-dimensional conformal field theories. This proof completes and unifies all known defect irreversibility theorems for defect dimensions d ≤ 4. The F-theorem on defects (d = 3) is a new result using information-theoretic methods. For d ≥ 4 we also establish the monotonicity of the relative entropy coefficient proportional to Rd−4. The geometric construction connects the proof of irreversibility with and without defects through the QNEC inequality in the bulk, and makes contact with the proof of strong subadditivity of holographic entropy taking into account quantum corrections.

Quantification of Structural Defects Using Pixel Level Spatial Information from Photogrammetry.

Aging infrastructure has drawn increased attention globally, as its collapse would be destructive economically and socially. Precise quantification of minor defects is essential for identifying issues before structural failure occurs. Most studies measured the dimension of defects at image level, ignoring the third-dimensional information available from close-range photogrammetry. This paper aims to develop an efficient approach to accurately detecting and quantifying minor defects on complicated infrastructures. Pixel sizes of inspection images are estimated using spatial information generated from three-dimensional (3D) point cloud reconstruction. The key contribution of this research is to obtain the actual pixel size within the grided small sections by relating spatial information. To automate the process, deep learning technology is applied to detect and highlight the cracked area at the pixel level. The adopted convolutional neural network (CNN) achieves an F1 score of 0.613 for minor crack extraction. After that, the actual crack dimension can be derived by multiplying the pixel number with the pixel size. Compared with the traditional approach, defects distributed on a complex structure can be estimated with the proposed approach. A pilot case study was conducted on a concrete footpath with cracks distributed on a selected 1500 mm × 1500 mm concrete road section. Overall, 10 out of 88 images are selected for validation; average errors ranging from 0.26 mm to 0.71 mm were achieved for minor cracks under 5 mm, which demonstrates a promising result of the proposed study.

Forecasting pipeline safety and remaining life with machine learning methods and SHAP interaction values

In-line inspection (ILI) is a common and useful way to provide comprehensive threat assessments and to detect defect dimensions. However, the ILI is very expensive and most of its costs are unnecessary since very few pipelines contain defects. Many previous studies have used machine learning (ML) methods to predict the safety of pipelines based on the features extracted from ILI signal results, which is very laborious and difficult to apply in industry. In this paper, the ILI results were predicted using multiple ML models through three prediction cases with only pipeline attributes and environmental features as input variables. In the first case, six ML methods were compared to predict whether there are defects in a pipeline section. The Catboost (CAT) method showed the best performance in all evaluation metrics with the highest certain prediction ratio (94%). The second case was using three ML methods to predict a defect depth, defect length, and defect width. The prediction accuracy of the defect depth was much higher than that of the defect length and defect width. A CAT model was the optimal model in this case due to its best performance in all the predictions. In the third prediction case, three ML methods were used to predict a defect length growth rate and defect depth growth rate based on different ILI results from different years. CAT was also the best method in this case with the highest accuracy. The predicted defect length growth rate and defect depth growth rate were used to calculate the remaining lifetime of pipelines based on the maximum allowable defect depth and failure pressure. The remaining lifetime of pipelines with different thickness, land use, and soil types was analyzed with changes in the specified minimum yield strength of a pipeline, a pipeline year, and maximum operating pressure. The accurate predictions in the three cases and the correlation analysis between input features and outputs helped company save a lot of costs and provided valuable information and suggestions in the further progress.

A review in rational design of graphene toward advanced Li–S batteries

For lithium–sulfur (Li–S) batteries, the problems of polysulfides shuttle effect, slow dynamics of sulfur species and growth of lithium dendrite during charge/discharge processes have greatly impeded its practical development. Of core importance to advance the performances of Li–S batteries lies in the selection and design of novel materials with strong polysulfides adsorption ability and enhanced redox electrocatalytic behavior. Graphene, affording high electrical conductivity, superior carrier mobility, and large surface area, has presented great potentials in improving the performances of Li–S cells. However, the properties of intrinsic graphene are far enough to achieve the multiple management toward electrochemical catalysis of energy storage systems. In addition, a general and objective understanding of its role in Li–S systems is still lacking. Along this line, we summarize the design routes from three aspects, including defect engineering, dimension adjustment, and heterostructure modulation, to perfect the graphene properties. Thus-synthesized graphene materials are explored as multifunctional electrocatalysts targeting high-efficiency and long-lifespan Li–S batteries, based on which the regulating role of graphene is comprehensively analyzed. This project provides a perspective on the effective engineering management of graphene materials to boost Li–S chemistry, meanwhile promote the practical application process for graphene materials.

A prospective case series on the efficacy of a cross-linked collagen matrix to increase buccal soft tissue thickness at large edentulous gaps: One-year results.

The objective of this study is to assess profilometric changes following soft tissue augmentation with a cross-linked porcine-derived collagen matrix (CMX) at large edentulous gaps of at least two units. Systemically healthy, nonsmoking patients with a large edentulous gap of at least two units demonstrating a horizontal soft tissue defect, were enrolled in a prospective case series. Soft tissue augmentation was performed in a one-stage approach with a 6 mm thick CMX at the time of implant placement. The primary outcome was the change in buccal soft tissue profile (BSP) at a mesial, central, and distal area of interest (AOI) up to 1 year when compared to the preoperative situation based on superimposed digital surface models. Secondary outcomes included the horizontal dimension of the soft tissue defect, complications, and marginal bone loss (MBL). Fifteen patients (eight females; mean age 58.73 years) were enrolled and 13 could be re-assessed at 1-year follow-up. The mean linear increase in BSP at 1 year was 0.66 mm (98.3% CI: 0.37-0.94), 0.80 mm (98.3% CI: 0.39-1.22), and 0.69 mm (98.3% CI: 0.32-1.06) at the mesial, central, and distal AOI, respectively. Substantial shrinkage of about 75% was observed in all areas between augmentation and 1-year follow-up. Even though 11 of 13 sites were fully augmented immediately postoperative, a soft tissue defect recurred in all sites at 1-year follow-up with a mean deficit of 2.30 mm. Altogether, 25% of the original soft tissue defect was eliminated by soft tissue augmentation. CMX was safe since no postoperative complications occurred and MBL was limited (0.70 mm). CMX is efficacious for horizontal soft tissue augmentation at large edentulous gaps. However, considerable graft resorption may be expected, and the clinical relevance of the augmentation may be questionable since all patients demonstrated a recurring and considerable soft tissue defect 1 year after surgery.

The role of evanescent modes in global-local analysis of ultrasonic guided waves in plates with varying local zone-scatterer relations

In order to provide a reliable and robust SHM performance, Ultrasonic Guided Waves (UGWs) need to be analyzed and understood. Numerical modeling of UGW propagation and scattering by hybrid methods offers the possibility of simulating UGW interaction with waveguides of arbitrary cross-sections and discontinuities. Maximizing the accuracy of such methods is important to perform quantitative SHM, while maintaining minimum computational cost. This work investigates the role of evanescent modes in the numerical analysis of UGWs in aluminum and composite plates with defects, by the hybrid Global-Local method. The complex solutions to the UGW eigenvalue problem are found and the scattering spectra for A0 and S0 incident modes are calculated. The accuracy of the numerical solution is then studied by computing the error in terms of energy balance. Parametric studies with respect to the local zone size, defect dimensions and shape are conducted including and excluding evanescent modes in the analysis. Considerations are provided to obtain a solution with error no greater than 5%, in terms of varying local zone – scatterer relations within plate waveguides.