Highly scalable bio-inspired soft elastomeric capacitor for structural health monitoring applications

Over the past few decades, Structural Health Monitoring (SHM) has gained wide popularity as it became essential to integrate monitoring systems into complex structural systems to ensure structural integrity and minimize hazards that may arise from any structural failure or collapse. Current monitoring technologies are capable of monitoring small areas with a priori information about the location of an existing defect, therefore they lack the ability to efficiently monitor large-scale systems such as bridges and wind turbine blades. The objective is to create a system capable of performing real-time online SHM with continuous feedback. This research aims at developing a complete system for structural health monitoring of wind turbine blades, including the sensing element, the data acquisition system, and the damage detection algorithm. The proposal is a network of soft sensors covering large surfaces capable of monitoring global as well as local behavior. The advantages of such a solution include cost efficiency, customizability in size and shape to accommodate the application, simple fabrication and installment and direct feature extraction with simple signal processing and machine learning techniques. The studies conducted to complete this dissertation intended to develop the sensing element (material and fabrication), characterize it and demonstrate applications to real structures. The proposed sensing element is a novel soft elastomeric capacitor (SEC) sensor for monitoring of large surfaces, applicable to composite materials. This soft capacitor is fabricated using a highly sensitive elastomer sandwiched between electrodes. It transduces strain into changes in capacitance. The elastomer is made of a Styrene Ethylene Butylene Styrene (SEBS) polymer doped with high permittivity Titanium dioxide (TiO2) as a filler material to increase the overall composite permittivity and improve the durability. The electrodes are made of a similar polymer doped with carbon black particles. The first study was conducted on optimizing the fabrication process for the sensor. We investigated the influence of processing methods that dictate the performance enhancement in a nanocomposite soft capacitor. The efficiency of ultrasonic probe and high-shear melt mixing methods in dispersing TiO2 nanoparticles in SEBS polymer matrix was studied. The compression-molding method shows highly promising for engineering applications by enhancing fabrication speed, safety, and improving control over the film thickness. The second part investigated the influence of interfacial treatment on the matrix-filler interaction using a melt-mixing process to fabricate robust and highly stretchable elastomers. Silicone oil and silane coupling agent were studied as possible solutions to enhance the compatibility between the inorganic fillers and polymer matrix. Results showed that specimens filled with silicone oil coated particles have promising overall properties. The third part, consisted of several experiments to characterize the functionality and applicability of the SEC to implement SHM to real life structures. The sensor behavior under static and dynamic loads was evaluated. Static test results showed the capability of the sensor to measure strains above 25µε with an almost linear behavior up to 20% strain levels and a gauge factor of 2. Dynamic results showed capability to accurately detect frequency contents and mode shapes. All the characterization tests were verified with one or more method, including commercial strain gauges, accelerometers, and finite element models. Using SECs in a network configuration have a great potential to implement an efficient inexpensive real time SHM on large-scale structures such as wind turbine blades. SEC data can be used to perform damage detection, localization and prognosis based on statistical as well as vibration analysis

Network of Flexible Capacitive Strain Gauges for Reconstruction of Surface Strain

Monitoring of surface strain on mesosurfaces is a difficult task, often impeded by the lack of scalability of conventional sensing systems. A solution is to deploy large networks of flexible strain gauges, a type of large area electronics. The authors have recently proposed a soft elastomeric capacitor (SEC) as an economical skin-type solution for large-scale deployment onto mesosurfaces. The sensing principle is based on a measurable change in the sensor\u27s capacitance upon strain. In this paper, we study the performance of the sensor at reconstructing surface strain map and deflection shapes. A particular feature of the sensor is that it measures surface strain additively, because it is not utilized within a Wheatstone bridge configuration. An algorithm is proposed to decompose the additive in-plane strain measurements from the SEC into principal components. The algorithm consists of assuming a polynomial shape function, and deriving the strain based on Kirchhoff plate theory. A least-squares estimator (LSE) is used to minimize the error between the assumed model and the SEC signals after the enforcement of boundary conditions. Numerical simulations are conducted on a symmetric rectangular cantilever thin plate under symmetric and asymmetric static loads to demonstrate the accuracy and real-time applicability of the algorithm. The performance of the algorithm is further examined on an asymmetric cantilever laminated thin plate constituted with orthotropic materials mimicking a wind turbine blade, and subjected to a non-stationary wind load. Results from simulations show good performance of the algorithm at reconstructing the surface strain maps for both in-plane principal strain components, and that it can be applied in real time. However, its performance can be improved by strengthening assumptions on boundary conditions. The algorithm exhibits robustness in performance with respect to load and noise in signals, except when most of the sensors\u27 signals are close to zero due to over-fitting form the LSE

Interfacial treatment effects on behavior of soft nano-composites for highly stretchable dielectrics

We investigate the influence of interfacial treatment on the matrix–filler interaction using a melt mixing process to fabricate robust and highly stretchable dielectrics. Silicone oil and silane coupling agent are studied as possible solutions to enhance the compatibility between the inorganic fillers and polymer matrix. Morphology, thermomechanical and dielectric behavior of the prepared specimens are studied. Results show that specimens filled with silicone oil coated particles have promising dielectric and thermal properties. The mechanical properties reveal a stiffness enhancement by 67% with a high strain at break of 900%. The relative permittivity of the specimens prepared with silicone oil increased by 45% as observed from the dielectric analysis

Evaluation of the Impact of an Education Program on Self-Reported Leadership and Management Competence Among Nurse Managers

BACKGROUND: Developing leadership and management competencies for nursing managers is critical to the effective leadership of others and driving team and organizational performance. This paper aimed to evaluate the impact of a system-wide nursing leadership quality improvement initiative in a network of four public hospitals and one specialized outpatient center in the United Arab Emirates (UAE). The initiative was designed to enhance nursing middle managers’ leadership and managerial competencies. METHODS: This is a quantitative evaluation following the Standards for Quality Improvement Reporting Excellence (SQUIRES) guidelines. Secondary Data analysis of a pre- and post-course self-assessment for 105 middle nursing managers who attended a nursing leadership quality improvement training program between December 2017 and April 2019. RESULTS: Following participation in this quality improvement initiative, the paired sample t-test analysis demonstrated a statistically significant difference between the pre- and post-assessments total and individual leadership domains mean scores. CONCLUSION: Attending well-structured nursing leadership quality improvement programs positively enhances nurse managers’ professional abilities and perception of their management and leadership competencies. Leadership development programs should equip managers with the skills and tools to achieve their professional goals effectively and support their transition to becoming expert nurse leaders. Healthcare institutions’ ethical obligation is to provide them with the necessary resources and training to achieve this goal

Conductive paint-filled cement paste sensor for accelerated percolation

Cementitious-based strain sensors can be used as robust monitoring systems for civil engineering applications, such as road pavements and historic structures. To enable large-scale deployments, the fillers used in creating a conductive material must be inexpensive and easy to mix homogeneously. Carbon black (CB) particles constitute a promising filler due to their low cost and ease of dispersion. However, a relatively high quantity of these particles needs to be mixed with cement in order to reach the percolation threshold. Such level may influence the physical properties of the cementitious material itself, such as compressive and tensile strengths. In this paper, we investigate the possibility of utilizing a polymer to create conductive chains of CB more quickly than in a cementitious-only medium. This way, while the resulting material would have a higher conductivity, the percolation threshold would be reached with fewer CB particles. Building on the principle that the percolation threshold provides great sensing sensitivity, it would be possible to fabricate sensors using less conducting particles. We present results from a preliminary investigation comparing the utilization of a conductive paint fabricated from a poly-Styrene-co-Ethylene-co-Butylene-co-Styrene (SEBS) polymer matrix and CB, and CB-only as fillers to create cementitious sensors. Preliminary results show that the percolation threshold can be attained with significantly less CB using the SEBS+CB mix. Also, the study of the strain sensing properties indicates that the SEBS+CB sensor has a strain sensitivity comparable to the one of a CB-only cementitious sensor when comparing specimens fabricated at their respective percolation thresholds

Dynamic Characterization of a Soft Elastomeric Capacitor for Structural Health Monitoring

Structural health monitoring of civil infrastructures is a difficult task, often impeded by the geometrical size of the monitored systems. Recent advances in conducting polymers enabled the fabrication of flexible sensors capable of covering large areas, a possible solution to the monitoring challenge of mesoscale systems. The authors have previously proposed a novel sensor consisting of a soft elastomeric capacitor (SEC) acting as a strain gauge. Arranged in a network configuration, the SECs have the potential to cover very large surfaces. In this paper, understanding of the proposed sensor is furthered by evaluating its performance at vibration-based monitoring of large-scale structures. The dynamic behavior of the SEC is characterized by subjecting the sensor to a frequency sweep, and detecting vibration modes of a full-scale steel beam. Results show that the sensor can be used to detect fundamental modes and dynamic input. Also, a network of SECs is used for output-only modal identification of a full-scale concrete beam, and results are benchmarked against off-the-shelf accelerometers. The SEC network performs well at estimating both natural frequencies and mode shapes. The resolution of the sensor is currently limited by the available electronics to measure small changes in capacitance, which reduces its accuracy with increasing frequencies in both the time and frequency domain

Novel nanocomposite technologies for dynamic monitoring of structures: a comparison between cement-based embeddable and soft elastomeric surface sensors

The authors have recently developed two novel solutions for strain sensing using nanocomposite materials. While they both aim at providing cost-effective solutions for the monitoring of local information on large-scale structures, the technologies are different in their applications and physical principles. One sensor is made of a cementitious material, which could make it suitable for embedding within the core of concrete structures prior to casting, and is a resistor, consisting of a carbon nanotube cement-based transducer. The other sensor can be used to create an external sensing skin and is a capacitor, consisting of a flexible conducting elastomer fabricated from a nanocomposite mix, and deployable in a network setup to cover large structural surfaces. In this paper, we advance the understanding of nanocomposite sensing technologies by investigating the potential of both novel sensors for the dynamic monitoring of civil structures. First, an in-depth dynamic characterization of the sensors using a uniaxial test machine is conducted. Second, their performance at dynamic monitoring of a full-scale concrete beam is assessed, and compared against off-the-shelf accelerometers. Experimental results show that both novel technologies compare well against mature sensors at vibration-based structural health monitoring, showing the promise of nanocomposite technologies for the monitoring of large-scale structural systems

The effect of intentional nurse rounding and nurse prompt response time to Call system on patient satisfaction, patient complaints, and patient clinical outcome: An Audit trial

Background: Improving patient satisfaction and safety is a critical goal for hospitals around the world. Healthcare providers have increasingly recognized the importance of strategic initiatives and the impact they have on patient outcomes.Objectives: This study examines the effect of intentional nurse rounding and the call system's response times on patient satisfaction, patient complaints, falls, and hospital-acquired pressure injuries (HAPI).Methods: This descriptive study was conducted between December 2017 to August 2018 in a hospital in the United Arab Emirates. The Intentional Nurse Rounding (INR) and Prompt Response to Call System (PRTCS) were introduced in December 2017. It comprised of: (1) hourly nurses’ rounds between 07:00 hours to 23:59 hours and 2 hourly rounds between 24:00 hours to 06:59 hours daily, (2) measurement of nurses’ response time to call bells, (3) leadership rounds to assess patient satisfaction. The outcomes were patient satisfaction, patient complaints, fall rates, and HAPI rates. Baseline data were collected through retrospective reviews of the data on these outcomes in December 2017. The second period of data collection was conducted over eight months after the initiation of the system, from December 2017 to August 2018. The Chi-square test was used to detect significant differences in outcomes pre and post intervention.Results: The overall adherence to the “Intentional Nurse Rounding and Prompt Response Time to Call System” was 91% while the overall patient satisfaction rate was 97% in August 2018. The average response to call time was 1.2 minutes. Patient complaints decreased from 0.75/month to 0.125/month between December 2017 to August 2018. During the same period, the rates of patient falls and HAPI decreased from 1.17/month to 0.38/month and 0.35/month to 0.24/month respectively. Though the observed differences were not statistically significant, there was a promising difference in patient complaints pre and post intervention (P=0.08).Conclusion: Integrating nursing-led strategic initiatives such as intentional nurse rounding and reduced response time to the call bell system can positively impact patient satisfaction, complaints, and clinical outcome