Lamb wave defect detection and evaluation using a fully non-contact laser system

Traditional Lamb wave structural health monitoring (SHM)/nondestructive evaluation (NDE) system employs contact type transducers such as PZT, ultrasonic transducers, and optical fibers. In application, transducer attachment and maintenance can be time and labor consuming. In addition, the use of couplant and adhesives can introduce additional materials on structures, and the interface coupling is often not well understood. To overcome these limitations, we proposed a fully non-contact NDE system by employing pulsed laser (PL) for Lamb wave actuation and scanning laser Doppler vibrometer (SLDV) for Lamb wave sensing. The proposed system is implemented on aluminum plates. The PL Lamb wave excitation is calibrated, and the optimal parameters are obtained. Lamb wave modes are then characterized through 1D wavefield analysis. With the calibrated and characterized system, defect detection and evaluation are achieved on aluminum plates with simulated defects (surfaced-bonded quartz rod, and machine milled crack) through 1D and 2D inspection in both time-space and frequency-wavenumber domains

Labview Implementation of the Electromechanical Impedance (EMI) Method as Part of an Integrated Structural Health Monitoring (SHM) System

There is an escalating interest in monitoring sensing system to assess the health of engineering structures in real-time. A wide body of literature demonstrated that structural health monitoring (SHM) methods based on acoustic emission (AE), electromechanical impedance (EMI), and guided ultrasonic waves (GUWs) can assess the health of simple waveguides and a certain number of complex structures. AE, EMI, and GUW have advantages and limitations. To boost the advantages and to overcome the shortcomings, a group at the University of Pittsburgh is working on a multi-modal integrated SHM where the three methods are driven by a single centralized hardware working under LabView environment. The suite mimics the sensory integration and processing of the human body, where the stimuli from the five sensory organs are transmitted by the nerves to the brain. In this thesis, we present the integration of the EMI and the GUW-based methods in LabView and the analysis of the EMI data. A large flat aluminum plate was monitored with an array of six transducers and damage was simulated by adding small masses to the plate. Then, the GUW and AE waveforms were analyzed using a common statistical index. The results presented in this thesis show that the EMI enable the detection of the simulated damage

Lamb Wave Nondestructive Evaluation and Imaging on Plate-Like Structures

Structure components are designed with a certain service life and damage may occur, or they may come with manufacture defects. Such damage and defects may lead to structural failure if not detected in time. To ensure the structural safety and prevent catastrophic failure, effective inspection is critical for in-time maintenance. Nondestructive evaluation (NDE) and structural health monitoring (SHM) have been widely applied for damage inspection and evaluation in various industries due to their noninvasive nature. Lamb wave based NDE/SHM has become the most popular ultrasonic methods that has been proved effective in different engineering applications that can be used to detect not only surface damage but also those internal. Lamb waves are guided waves that propagate in plate-like structures and they can propagate long distance with low energy loss which makes large structure inspection possible. They are also sensitive to various damage/defects across the thickness such as crack in metallic structures and delamination or debonding in composite structures. Despite the intensive studies and application of Lamb wave based NDE/SHM, there are still some challenges that need to be addressed such as damage with complex profiles that is difficult to quantify; alternative excitation and sensing methods that can be applied remotely without the need to leave the transducers on the structure surface; and also the feasibility and effectiveness of the Lamb wave methodologies in real world applications. This dissertation aims to address the aforementioned challenges. Two parts of research work have been conducted for this purpose: Part I focuses on the fundamental studies of Lamb waves and development of the system as well as the supplementary damage detection methodologies, while Part II focuses on applying the developed methods to various NDE/SHM applications from aerospace to nuclear structures. In Part I, the Lamb wave based wavefield analysis methods are first demonstrated. Based on that, an actuator network Lamb wave imaging method that can quantify complex damage with great details is developed. In addition, a fully noncontact/remote NDE system through laser excitation and sensing strategy is developed and evaluated on both metallic and composite structures towards more flexible real-world applications. In Part II, the developed Lamb wave based systems and methodologies are investigated and evaluated on various real-world applications in order to prove their efficacy and reliability, including inspection on typical damage/defects such as crack, wrinkle, and delamination in aerospace structures, and stress corrosion cracking and material degradation in nuclear structures. This dissertation uniquely addressed the complex damage profile quantification issue with a high-resolution actuator network imaging method, developed a reliable and noncontact/remote laser based Lamb system accompanied with effective evaluation methods which enables more flexible field application, and systematically investigated the Lamb wave based NDE reliability and effectiveness on various real world applications which provided guidelines for typical damage and defects inspection in aerospace and nuclear structures. In the long run, this research work will facilitate the advancement of actuation and sensing strategies, development of evaluation methodologies, and the formation of standard guidelines towards more effective, rapid and flexible Lamb wave based NDE/SHM to ensure the structural safety

Rational Choice or Altruism Factor: Determinants of Residents’ Behavior toward Household Waste Separation in Xi’an, China

Understanding why people do or do not perform household waste separation is a vital premise for designing relevant policies to promote waste management. As such, in this paper, an empirical study was carried out to explore the impacts of both rational choice and altruism factors on residents’ household waste separation behavior. Through the analysis of the survey sample (n = 1102) from Xi’an, China, using structural equation modeling, the main findings suggested that (i) the rational choice model can better explain such behavior, (ii) the altruism factor cannot directly affect household waste separation behavior, (iii) the altruism factor is highly correlated with the attitude determinant of household waste separation behavior, and (iv) rational choice models incorporating the altruism factor may have better explanatory efficacy. After that, some factors influencing residents’ altruism to household waste separation were identified. The main aim of this study was to compare two different tendencies in explaining sustainable behavior and help to find a better framework for behavior analysis

Meta-Evaluation for the Evaluation of Environmental Management: Standards and Practices

Environmental management plays a key role in the sustainable development of cities. The effectiveness of environmental management is commonly examined through some evaluation schemes, but the effectiveness of such evaluation schemes also needs to be verified. As such, in this study, meta-evaluation was creatively introduced into environmental management to improve the evaluation of environmental management (EEM). Meta-evaluation is the evaluation of an evaluation scheme, and can verify and enhance the evaluation quality. First, a set of new meta-evaluation standards and criteria was proposed based on the unique characteristics of environmental management, which made meta-evaluation standards more adaptable and effective. After that, the efficacy of the proposed meta-evaluation standards was verified through their application to two evaluation schemes used in different fields of EEM. Based on meta-evaluation, suggestions for improving these two EEM schemes were also provided. The major contributions of this study are to introduce meta-evaluation into environmental management, establish new evaluation standards, and examine the efficacy of EEM. The research showed that it is critical to carry out meta-evaluation before and/or after the implementation of EEM

Autophagy inhibitor facilitates gefitinib sensitivity in vitro and in vivo by activating mitochondrial apoptosis in triple negative breast cancer.

Epidermal growth factor receptor (EGFR) is over-expressed in about 50% of Triple negative breast cancers (TNBCs), but EGFR inhibitors have not been effective in treating TNBC patients. Increasing evidence supports that autophagy was related to drug resistance at present. However, the role and the mechanism of autophagy to the treatment of TNBC remain unknown. In the current study, we investigated the effect of autophagy inhibitor to gefitinib (Ge) in TNBC cells in vitro and in nude mice vivo. Our study demonstrated that inhibition of autophagy by 3-Methyladenine or bafilomycin A1 improved Ge's sensitivity to MDA-MB-231 and MDA-MB-468 cells, as evidence from stronger inhibition of cell vitality and colony formation, higher level of G0/G1 arrest and DNA damage, and these effects were verified in nude mice vivo. Our data showed that the mitochondrial-dependent apoptosis pathway was activated in favor of promoting apoptosis in the therapy of Ge combined autophagy inhibitor, as the elevation of BAX/Bcl-2, Cytochrome C, and CASP3. These results demonstrated that targeting autophagy should be considered as an effective therapeutic strategy to enhance the sensitivity of EGFR inhibitors on TNBC

Planting Patterns and Deficit Irrigation Strategies to Improve Wheat Production and Water Use Efficiency under Simulated Rainfall Conditions

The ridge furrow (RF) rainwater harvesting system is an efficient way to enhance rainwater accessibility for crops and increase winter wheat productivity in semi-arid regions. However, the RF system has not been promoted widely in the semi-arid regions, which primarily exist in remote hilly areas. To exploit its efficiency on a large-scale, the RF system needs to be tested at different amounts of simulated precipitation combined with deficit irrigation. Therefore, in during the 2015–16 and 2016–17 winter wheat growing seasons, we examined the effects of two planting patterns: (1) the RF system and (2) traditional flat planting (TF) with three deficit irrigation levels (150, 75, 0 mm) under three simulated rainfall intensity (1: 275, 2: 200, 3: 125 mm), and determined soil water storage profile, evapotranspiration rate, grain filling rate, biomass, grain yield, and net economic return. Over the two study years, the RF treatment with 200 mm simulated rainfall and 150 mm deficit irrigation (RF2150) significantly (P < 0.05) increased soil water storage in the depth of (200 cm); reduced ET at the field scale by 33%; increased total dry matter accumulation per plant; increased the grain-filling rate; and improved biomass (11%) and grain (19%) yields. The RF2150 treatment thus achieved a higher WUE (76%) and RIWP (21%) compared to TF. Grain-filling rates, grain weight of superior and inferior grains, and net economic profit of winter wheat responded positively to simulated rainfall and deficit irrigation under both planting patterns. The 200 mm simulated rainfall amount was more economical than other precipitation amounts, and led to slight increases in soil water storage, total dry matter per plant, and grain yield; there were no significant differences when the simulated rainfall was increased beyond 200 mm. The highest (12,593 Yuan ha−1) net income profit was attained using the RF system at 200 mm rainfall and 150 mm deficit irrigation, which also led to significantly higher grain yield, WUE, and RIWP than all other treatments. Thus, we recommend the RF2150 treatment for higher productivity, income profit, and improve WUE in the dry-land farming system of China

Machine Learning Prediction of Visual Outcome after Surgical Decompression of Sellar Region Tumors

Introduction: This study aims to develop a machine learning-based model integrating clinical and ophthalmic features to predict visual outcomes after transsphenoidal resection of sellar region tumors. Methods: Adult patients with optic chiasm compression by a sellar region tumor were examined to develop a model, and an independent retrospective cohort and a prospective cohort were used to validate our model. Predictors included demographic information, and ophthalmic and laboratory test results. We defined “recovery” as more than 5% for a p-value in mean deviation compared with the general population in the follow-up. Seven machine learning classifiers were employed, and the best-performing algorithm was selected. A decision curve analysis was used to assess the clinical usefulness of our model by estimating net benefit. We developed a nomogram based on essential features ranked by the SHAP score. Results: We included 159 patients (57.2% male), and the mean age was 42.3 years old. Among them, 96 patients were craniopharyngiomas and 63 patients were pituitary adenomas. Larger tumors (3.3 cm vs. 2.8 cm in tumor height) and craniopharyngiomas (73.6%) were associated with a worse prognosis (p < 0.001). Eyes with better outcomes were those with better visual field and thicker ganglion cell layer before operation. The ensemble model yielded the highest AUC of 0.911 [95% CI, 0.885–0.938], and the corresponding accuracy was 84.3%, with 0.863 in sensitivity and 0.820 in specificity. The model yielded AUCs of 0.861 and 0.843 in the two validation cohorts. Our model provided greater net benefit than the competing extremes of intervening in all or no patients in the decision curve analysis. A model explanation using SHAP score demonstrated that visual field, ganglion cell layer, tumor height, total thyroxine, and diagnosis were the most important features in predicting visual outcome. Conclusion: SHAP score can be a valuable resource for healthcare professionals in identifying patients with a higher risk of persistent visual deficit. The large-scale and prospective application of the proposed model would strengthen its clinical utility and universal applicability in practice