bluuebunny/crossref_metadata_2025 huggingface dataset:
Dishonesty and Public Employment
Authors: Cruces Guillermo , Rossi Martín A. , Schargrodsky Ernesto
Published: December 2023

We exploit a natural experiment to study the causal link between dishonest behavior and public employment. When military conscription was mandatory in Argentina, eligibility was determined by both a lottery and a medical examination. To avoid conscription, individuals at risk of being drafted had strong incentives to cheat in their medical examination. These incentives varied with the lottery number. Exploiting this exogenous variation, we first present evidence of cheating in medical examinations. We then show that individuals with a higher probability of having cheated in health checks exhibit a higher propensity to occupy nonmeritocratic public sector jobs later in life. (JEL D91, J45, K42, O15)
Firm-Level Upgrading in Developing Countries
Authors: Verhoogen Eric
Published: December 2023

In principle, firms in developing countries benefit from the fact that advanced technologies and products have already been developed in industrialized countries and can simply be adopted, a process often referred to as industrial upgrading. But for many firms this advantage remains elusive. What is getting in the way? This paper reviews recent firm-level empirical research on the determinants of upgrading in developing countries. The first part focuses on how to define and measure various dimensions of upgrading—learning, quality upgrading, technology adoption, and product innovation. The second part takes stock of recent evidence on the drivers of upgrading, classifying them as output-side drivers, input-side drivers, or drivers of know-how. I conclude with some thoughts about promising directions for research in the area. (JEL D21, D24, D83, F14, L26, O14, O31)
Generative AI for Economic Research: Use Cases and Implications for Economists
Authors: Korinek Anton
Published: December 2023

Generative artificial intelligence (AI) has the potential to revolutionize research. I analyze how large language models (LLMs) such as ChatGPT can assist economists by describing dozens of use cases in six areas: ideation and feedback, writing, background research, data analysis, coding, and mathematical derivations. I provide general instructions and demonstrate specific examples of how to take advantage of each of these, classifying the LLM capabilities from experimental to highly useful. I argue that economists can reap significant productivity gains by taking advantage of generative AI to automate micro-tasks. Moreover, these gains will grow as the performance of AI systems continues to improve. I also speculate on the longer-term implications of AI-powered cognitive automation for economic research. The online resources associated with this paper explain how to get started and will provide regular updates on the latest capabilities of generative AI in economics. (JEL A11, C45, D83, I23, O33)
Η τάξη της Κυκλικής Οικονομίας
Authors: Μάκιος Αθανάσιος
Published: December 2023

Το άρθρο παρουσιάζει παραδείγματα κυκλικής οικονομίας
δίνοντας έμφαση στο πως μπορούν να αναπτύξουν οι μαθητές την ικανότητα να σκεφτούν τον
πλήρη κύκλο ζωής κάποιων προϊόντων που χρησιμοποιούμε στην καθημερινή μας
ζωή.
Η συναισθηματική επικοινωνία με το παιδί
Authors: Βράχας Χρίστος
Published: December 2023

Το άρθρο παρουσιάζει τη συναισθηματική επικοινωνία με το
παιδί και πως μπορούμε να το βοηθήσουμε να εκφράζει τα συναισθήματά του αντί να τα κρατά
μακριά από το ίδιο και από εμάς.
Οι Φωνολογικές και Αρθρωτικές Διαταραχές ως προγνωστικός παράγοντας
στις Δυσκολίες Γραφής κι Ανάγνωσης
Authors: Βασιλοπούλου – Μούντανου Παναγιώτα
Published: December 2023

Το άρθρο εστιάζει στις φωνολογικές και αρθρωτικές
διαταραχές ως προγνωστικός παράγοντας στις δυσκολίες γραφής κι
ανάγνωσης.
Η Αξιοποίηση της Εννοιολογικής Χαρτογράφησης στην Εκπαιδευτική Διαδικασία
Authors: Τόδας Αλέξανδρος
Published: December 2023

Στο συγκεκριμένο άρθρο γίνεται αναφορά στη χρησιμότητα του εννοιολογικού χάρτη ως εργαλείο διδασκαλίας, το οποίο προσφέρει πολλαπλά οφέλη στους μαθητές/τριες. Συγκεκριμένα περιγράφεται η έννοια του εννοιολογικού χάρτη, η διαδικασία του σχεδιασμού του, οι επιμέρους στόχοι της εννοιολογικής χαρτογράφησης και οι τρόποι ένταξής της στη διδακτική πράξη. Επιπρόσθετα, αναδεικνύεται η αξία της εννοιολογικής χαρτογράφησης, όταν αυτή συνδυάζεται με τη χρήση των Τεχνολογιών Πληροφορίας και Επικοινωνίας. Για το σκοπό αυτό παρουσιάζονται τα πλεονεκτήματα της υπολογιστικής υποστήριξης της χαρτογράφησης εννοιών και στη συνέχεια παρατίθενται παραδείγματα παιδαγωγικών δραστηριοτήτων με χρήση του λογισμικού Κidspiration.
Κατασκευάζω τον δικό μου νερόμυλο
Authors: Μαρκοπούλου Αικατερίνη , Μαρκοπούλου Μερόπη
Published: December 2023

Η παρούσα εργασία αποτελεί μια διδακτική πρόταση που έχει τη μορφή του διδακτικού σεναρίου με εστίαση σε ένα κεντρικό θέμα (κατασκευή νερόμυλου) για την προσχολική εκπαίδευση, με συγκεκριμένους μαθησιακούς στόχους, διδακτικές προσεγγίσεις και στρατηγικές αξιολόγησης. Βασίζεται στην ενιαιοποιημένη εκπαίδευση STEAM και στη διαδικασία του μηχανικού σχεδιασμού που αποτελεί και μέρος του νέου αναλυτικού προγράμματος σπουδών για το Νηπιαγωγείο. Η εκπαιδευτική προσέγγιση STEAM συνιστά μια διεπιστημονική προσέγγιση των θεματικών πεδίων της επιστήμης, της τεχνολογίας, της μηχανικής και γενικότερα των θετικών επιστημών. Έχει τις ρίζες της στη θεωρία του κονστρουκτιβισμού, με βάση τη θεματική προσέγγιση και τη διερευνητική μάθηση ακολουθώντας διεπιστημονικές συνδέσεις, οργάνωση του φυσικού χώρου σύμφωνα με τα ενδιαφέροντα των μαθητών/τριών, υλοποίηση συμβατικών και ψηφιακών δραστηριοτήτων και τελική αποτίμηση με επίκεντρο πάντα τον/τη μαθητή/τρια και τα ενδιαφέροντά του.
Βιβλιοθεραπεύοντας τις ψυχολογικές επιπτώσεις της νόσου COVID-19 σε παιδιά προσχολικής και σχολικής ηλικίας: προτάσεις παιδικών βιβλίων με θέμα τον κορωνοϊό και την πανδημία
Authors: Ακριτίδου Παρασκευή , Μπάρλα Έλλη
Published: December 2023

Το παρόν άρθρο προτείνει τη βιβλιοθεραπευτική προσέγγιση των ψυχολογικών επιπτώσεων της πανδημίας της νόσου COVID-19 σε σχολικό πλαίσιο για μαθητές/-τριες προσχολικής και σχολικής εκπαίδευσης. Αρχικά, συνοψίζονται οι ψυχολογικές επιπτώσεις της πανδημίας για τα παιδιά προσχολικής και σχολικής ηλικίας. Στη συνέχεια, παρουσιάζεται η μέθοδος της βιβλιοθεραπείας. Ύστερα, γίνεται μια επισκόπηση της βιβλιογραφίας όσον αφορά την εφαρμογή της βιβλιοθεραπείας στην Ελλάδα και το εξωτερικό γενικά και ειδικά εν σχέσει με τη νόσο COVID-19. Έπειτα, προτείνονται δύο βιβλιοθεραπευτικές επιλογές-δραστηριότητες, μία για το Νηπιαγωγείο και μία για το Δημοτικό. Τέλος, μετά τις βιβλιογραφικές αναφορές, παρατίθεται λίστα με την ελληνική παιδική βιβλιοπαραγωγή (λογοτεχνία-παραμύθια και βιβλία γνώσεων) με θέμα την πανδημία και τον κορωνοϊό καθώς και οι διαδικτυακές πηγές απ’ όπου αντλήθηκε το υλικό.
The use of restored monuments for the exhibition of contemporary artworks: where is (preventive) conservation?
Authors: Stoupathis Konstantinos
Published: December 2023

Abstract. The key issue raised in this paper concerns the absence of an institutional framework for the operation of the buildings with the condition of preventive conservation of the modern collections. The main interest of curators focuses on the restoration of the monument in order to be "functional" and accessible rather than to the provision of facilities that will prevent the deterioration of contemporary works (two-dimensional paintings, in-situ installations, sculptures, video projections, etc.). Secondly, the monuments cannot always provide possibilities for a controlled microclimate. The fact that the exhibits are modern, made of technologically advanced or recycled materials - sometimes not original ones but replicas - should not preclude the practical application of preventive conservation measures. After all, it is proven that the establishment of an exhibition regulation is necessary regardless of the bioclimatic design of the buildings.
ANEMIA IN PATIENTS WITH MALIGNANT NEOPLASMS (literature review)
Authors: Kel'berer E.
Published: December 2023

Anemia is a common complication of both oncopathology itself and ongoing drug and chemoradiotherapy. Anemia not only worsens the quality of life of patients, but also negatively affects the effectiveness of specific treatment and patient survival rates. The frequency of anemia varies from 20 to 90% depending on the nosology, the stage of the disease, and the antitumor treatment being carried out.

In cancer patients, anemia has a complex origin and can be caused by various reasons. As a rule, there are a number of factors at once, among which the suppressive effect of proinflammatory cytokines on erythropoiesis, synthesis of endogenous erythropoietin, sensitivity of erythropoietin receptors, as well as increased formation of hepcidin with the development of functional iron deficiency prevail.

A detailed understanding of the pathogenesis of anemia caused by a tumor or chronic disease will allow the clinician to build a competent tactic for correcting the anemia syndrome, which will timely prevent the development of clinical symptoms and aggravation of the severity of the cancer patient's condition.
Russian Yearning for Elite Power: Nikolai Berdyaev’s Reflections on the Metaphysics of Democratism
Authors: Jedliński Marek
Published: December 2023

The purpose of this article is to present Nikolai Berdyaev’s view of power and how it is exercised in a democracy. The Russian thinker treated power as an evil that the democratic system was not free from. Berdyaev regarded the metaphysics of democratism as a manifestation of human hubris and a fall into what is mediocre and devoid of deeper spirituality. He argued that power should be aristocratic, not egalitarian. In his view, only the chosen, few, the eminent, possessed the ability to guide the masses toward the highest values.
The philosophical idea of a new Christian civilization in Russian Religious Philosophy
Authors: Rarot Halina
Published: December 2023

The article argues, using the thought of Fyodor Dostoevsky and Nikolai Berdyaev as an example, that the search for the genesis of the current political ideology, guiding the armed conflict launched by Russia in Ukraine, in the thought represented by Russian religious philosophers of the second half of the 19th and early 20th centuries, i.e., the founders of a strictly national philosophy, is quite superficial and essentially unfounded. For the idea of a new Christian civilization with a new state order and a new role for the Orthodox Church, which they formulated, was an idea of such a Christian reality, the fulfilment of which, in their view, could only occur at a very distant time, actually at the end of human history, and required an earlier spiritual and moral revolution.
Russian Intelligentsia toward the Legal Nihilism. Reading the “Landmarks” (1909) and “Out of the Depth” (1918) after February 24, 2022
Authors: Przeciszewska Maria
Published: December 2023

The aim of this paper is to re-read the criticism of the Russian intelligentsia, which was made by authors of Landmarks (“Vekhy”, 1909) and Out of the Depth (“Iz glubiny”, 1918), in the context of the support given to the Russian invasion on the Ukraine in 2022 by the large part of Russian intellectuals. Instead of perceiving the current “rapprochement” of the Russian intelligentsia to the Putin government as a kind of “aberration” and a departure from its “moral mission”, the author would like to show the arguments concerning long duration of the tradition of their acceptance of the anti-liberal and authoritarian course of the Russian government. This tradition was unveiled by such outstanding Russian liberals and religious thinkers as, among others: Nikolai Berdyaev, Petr Struve, Bogdan Kistyakovski, Iosif Pokrovsky and Sergei Kotlyarevsky. They believed that the susceptibility of the intelligentsia to revolutionary slogans was caused not only by hostility to the Old Regime, but by their instrumental attitude to the state and law. They claimed that the Russian intelligentsia had much more in common with the representatives of Tsarist autocracy than would result from the hostility felt towards it. A common feature of both was “legalnihilism” – a point of view that assumed a distrustful attitude towards rational law. The only way to overcome this distrust was therefore instilling Kant’s personalism and raising the authority of natural law among the broad strata of the Russian intelligentsia.
George Santayana i problem wolności
Authors: Grzeliński Adam , Pietras Alicja
Published: December 2023

This article is a commentary and an introduction to the Polish translation of George Santayana’s work, Freedom, which is a chapter in the fourth volume of his series, The Realms of Being, titled The Realm of Spirit (1940). It provides an overview of hisprevious works, particularly his series The Life of Reason (1905–1906) and Scepticism and Animal Faith (1926). Additionally, it briefly examines the evolution of Santayana’s standpoint and the meaning of the fundamental categories and concepts of his ontology. The analysis of Freedom, along with a comparison to the standpoints of Nicolai Hartmann and Hannah Arendt, enables us to classify it as a form of compatibilism. Within this perspective, natural determinism harmonizes with the teleological self-determination of human will. Human freedom, directed towards an open horizon of the future, unveils an essential tragic aspect of human condition, as the choice of a value is perpetually linked to unfulfillment. Ultimately, any value resides in the realm of ideals, and by making a choice, we neglect other values and select only one of the potential paths in our lives.
SURFACE DAMAGE IDENTIFICATION IN 3D PRINTED METAL PARTS USING CONVOLUTIONAL NEURAL NETWORK
Authors: MODIR ALIREZA , TANSEL IBRAHIM
Published: December 2023

Surface Response to Excitation (SuRE) is an active Structural Health Monitoring (SHM) method used in this study for the detection and quantification of the artificial damages created by the milling operation on additively manufactured metal plates. In this method, one piezoelectric element is bonded to one end of the test specimen to excite it with surface waves and the dynamic response to excitation is recorded by another piezoelectric at the other end of the part. The excitation signal is a sweep sine wave with a duration of 1 ms and a frequency range of 50-120 kHz. Using a Markforged metal 3D printer, five stainless steel plates of identical size (195×54×2.5 mm) were created. The data was recorded when all the parts were in a healthy condition and when they were face milled at 3 different lengths. The collected sensory data in the time domain were converted to time-frequency representation images using continuous wavelet transform (CWT). Different data augmentation methods have been implemented for expanding the size of the dataset. The image dataset was used as input to train a Two-Dimensional Convolutional Neural Network (2D-CNN) for the detection of damage and also for quantifying the damage length. The CNN could detect the damaged parts with 97.4% accuracy and classify the damage length with an overall accuracy of 98.7%.
OPTIMIZATION OF DAMAGE FEATURES CONTAMINATED BY NONSTATIONARY COLORED NOISE ALGORITHMS USING JOHANSEN COINTEGRATION
Authors: SAHAHASSANI SAHAR , DACKERMANN ULRIKE , GANDOMI AMIR H.
Published: December 2023

For structural health monitoring (SHM), researchers have primarily investigated the effects of signals contaminated with stationary white noise, with very few studies examining pollution caused by highly correlated nonstationary colored noise, such as Brown noise. To address this issue, this paper proposes an optimization-based damage detection technique for composite structures exposed to nonstationary colored noise using condensed frequency response functions (CFRF) as damage-sensitive features (DSF). Two different signal-to-noise ratios (SNR) of Brownian motions, i.e., 20 and 10, are used in the investigation to contaminate CFRFs. Contamination produces nonstationary patterns, making it difficult to detect damage with vibration-driven methods. In this study, we propose a new goal function based on Johansen cointegration, an econometric concept. The proposed objective function converts nonstationary CFRF signals into stationary representations, subsequently fed into optimization-based model updating algorithms. The Reptile Search Algorithm (RSA) is employed to update unknown structural damage indices based on the constructed objective function. The new method is validated on a finite element (FE) model simulating composite laminates with different ply orientations. By comparing the proposed method to a damage detection approach in the literature, the superiority of the proposed method is demonstrated.
PIECE-WISE RITZ ANALYSIS OF BEAMS SUBJECTED TO DISCONTINUITY IN SLOPE
Authors: PARTHASARATHY SUDHARSAN , KAPANIA RAKESH K.
Published: December 2023

This study presents a Ritz-type analysis for obtaining the vibration frequencies and mode shapes of beams that have a discontinuity in slope. Such structures have a wide range of applications in engineering as they often represent structural idealizations of complex structures such as robotic arms, crack modeling and foldable wings of aircraft. In the present study, the beams have been modeled using Euler Bernoulli’s theory, and the discontinuity in slope is represented by a torsional spring connecting the two segments of the beam. The beams are discretized into subdomains based on the location of the discontinuity. Legendre polynomials are used to define the displacement variation over individual uniform domains. The continuity of displacement is applied at the interface of adjacent subdomains and is enforced into the global system of equations using a condensation procedure. This procedure eliminates the dependent Ritz constant obtained from the displacement continuity. This study focuses on obtaining the vibration frequencies and mode shapes of a simply-supported beam with a discontinuity in slope and compares the results with the analytical solution. The paper would be of interest to researchers involved with the structural health monitoring of beams with cracks, robotic arms, and vibrations of folding wings like the one being considered for 777-X.
NOVEL MEANS AND WAYS OF GETTING STRUCTURAL HEALTH MONITORING INTO APPLICATION
Authors: CBOLLER CHRISTIAN
Published: December 2023

Research and development of Structural Health Monitoring (SHM) has been around for decades now. However, with so much effort performed in the past, much more SHM application would have been expected. Reasons for this situation are various but one is certainly the diversity of subjects and topics in which SHM plays a role and vice versa. A way on how to grasp the diversity in SHM and to get it focused to some degree is to get the application of SHM to be shown based on demonstrators. SHM demonstrators is not something new. However, what often happens to those demonstrators is, that they are not used once the project they have been funded from has been completed. In addition to this, the demonstration usually turns up during the end of a project and this maybe even happening in a rush. This short period of time does often not even allow the outcome of the demonstrators to be sufficiently communicated with the true potential applicants, which may be an industry allowing the SHM technology to be commercialized. An initiative has therefore been started out of Germany recently with international participation from Greece, Poland, South Korea and the USA, where available SHM demonstrators are extended in their use, such that data obtained from those can be shared with an international community or data can be generated, validated and disseminated with any SHM technology potential applicants want to get linked to the demonstrator with. So far 14 potential demonstrators ranging from aerospace over wind energy to civil engineering and others have been identified. Within this paper the different demonstrators available so far are briefly introduced including their potential with data already available and the options for SHM technology providers, to get their technology applied, validated, and demonstrated in future actions. The network and hence platform for this SHM technology demonstration initiative will be generally opened to the general public and it is intended to demonstrate the application of SHM technology at various future scientific and technology trading events, would this be traditional conferences, symposia, fairs and possibly others.
PERFORMANCE OF CROSSED LONG-GAUGE STRAIN SENSORS IN THE SPREAD FOOTING FOUNDATION
Authors: LIANG YITIAN , GLISIC BRANKO
Published: December 2023

Estimations of shear stresses are essential design procedures of spread footing foundations and detecting shear strain at critical planes is crucial in structural health monitoring because it provides valuable insights into the structural stability of the foundation. Crossed topology of long-gauge strain sensors can be used to monitor shear strain. By an ideal layout of two strain sensors in a planar case, the effect from the normal force, bending moments, and even temperature gradient can be eliminated. However, some slight position changes, e.g., due to on-site conditions, may affect the performance of crossed sensors. Therefore, it is necessary to study the influence of imperfections in the geometrical position of sensors on the measurements of crossed sensors. This paper presents a study on the performance of long-gauge sensors embedded in a spread footing foundation of a five-floor garage at Princeton University. We investigate the effects of topology on the measurement of average shear strain and the relationship between the evaluated shear and loading from the superstructure. The results show that the imperfections in the positioning of sensors have a significant impact on the measurement of shear strain, which needs to be taken into consideration when interpreting the sensor data. The average shear strain evaluated using the crossed sensors measurements is compared with theoretical values obtained from structural analysis. The results validate the estimated relationship between detected strain and applied forces. The findings of this study have important implications for the use of crossed long-gauge strain sensors beyond spread footing foundations, as the method applied here can be extended to other types of structural elements.
BAYESIAN DAMAGE ESTIMATION WITH REGULARIZED DATA-DRIVEN STOCHASTIC TIME SERIES MODEL
Authors: ZHOU PEIYUAN , KOPSAFTOPOULOS FOTIS
Published: December 2023

A probabilistic vibration-based global SHM technique is proposed. In the process, experimental data from a modal test on a wing structure is used to identify a unified model with i) a Vector-dependent Functionally Pooled (VFP) component, ii) and an Auto-Regressive eXogenous (ARX) component. LASSO regularization is incorporated as a model structure selection method while introducing model sparsity. A probabilistic damage identification/quantification method within a Bayesian architecture is applied to solve the inverse problem, which provides a decision confidence interval for damage estimation.
ONLINE FATIGUE DAMAGE DETECTION FOR STRUCTURES UNDER RANDOM LOADING USING A COMPARATIVE SENSOR-DATA APPROACH
Authors: CHAABAN RANNAM , FRITZEN CLAUS-PETER
Published: December 2023

Fatigue failure of metallic structures such as wind turbines towers or steel bridges is a problem that affects their remaining service life. The current industry standard of fatigue damage assessment is based on time domain cycle counting to estimate the cumulative fatigue damage which is compared to a reference value to detect fatigue failure. The stochastic nature of the fatigue process and the uncertainty in choosing the appropriate reference value limit the applicability of this approach. Fatigue crack detection is the focus of many structural health monitoring techniques. A novel sensor-data comparative approach for fatigue damage detection is proposed in this paper. This approach is based on online monitoring of the linear correlation between monitored and reference sensordata. Fatigue failure is detected when the linear correlation is lost. The proposed concept is validated experimentally and the obtained experimental results prove the possibility of early detection of fatigue failure.
EFFECTS OF IMPERFECT INTERFACE ON THE DISPERSION CURVES OF TORSIONAL WAVES IN A COMPOSITE HOLLOW CYLINDER
Authors: WANG JUNZHEN , QU JIANMIN
Published: December 2023

This paper investigates the influence of interfacial imperfections on the dispersion relationship of torsional waves in a composite hollow cylinder. The imperfect interface between the inner and outer tubes is modelled by a linear spring interface model, where tractions are continuous across the interface and the displacement jump is assumed to be proportional to the tangential shear stress acting on the interface. The dispersion curves of normalized frequency as a function of normalized wavenumber can be determined by solving an eigenvalue problem. It is shown that for a fixed wavenumber, the modal frequency decreases with increasing interfacial spring compliance, especially for smaller wavenumbers. Besides, at larger wavenumbers, the loss of perfect continuity at the interface has a reduced impact. The thickness effect of the outer tube is further analyzed. The computational results indicate that the modal frequency rises in the case of the thinner coating layer. These torsional wave propagation features may provide insights and guidelines for nondestructive evaluation of composite hollow cylinders with imperfect interfaces. The paper finishes with a summary and concluding remarks.
WAVE-BASED DAMAGE IDENTIFICATION IN COMPOSITE STRIPS AND 2D SOLIDS USING INVERSE MULTIRESOLUTION WAVELET METHODS
Authors: DIMITRIOU DIMITRIS , SARAVANOS DIMITRIS
Published: December 2023

An inverse procedure for damage identification on 1D and 2D solids based on wave propagation using the multiresolution finite wavelet domain (MR-FWD) method is presented. The forenamed method utilizes Daubechies wavelet and scaling functions for the approximation of state variables and as such, it involves two types of solutions, the coarse and the fine solutions. In that way, the multiresolution nature of the method can be utilized for efficient damage estimation in experimental applications since the fine solutions of the method have manifested remarkable localization and isolation capabilities and high sensitivity to damage. In order to fully take advantage of the additional benefits of the MR-FWD method, full-field displacement measurements of the wave propagation are taken into consideration. Wavelet decomposition using Daubechies wavelets is now applied on the measurements, leading to approximation and detail components that are directly comparable to the coarse and fine solutions of the multiresolution simulation, respectively. Therefore, MR-FWD models can be created using the same Daubechies wavelets as the decomposition of the experimental data, so as to compare the simulation results with the measured ones. Numerical results reveal that comparing the detail component of the experiments with the fine solution of the simulations using appropriate metrics can lead to efficient damage identification. In such manner, an optimization process can be conducted in order to characterize the investigated damage scenarios. This procedure can lead to more sensitive and accurate damage estimation due to the advantages of the multiresolution analysis.
FIBER BRAGG GRATING SENSOR BASED MODE FILTERING USING COSINE DISTANCE METRIC
Authors: SOMAN ROHAN , BALASUBRAMANIAM KALEEESWARAN , MALINOWSKI PAWEL
Published: December 2023

Fiber Bragg grating (FBG) sensors are considered ideal for structural health monitoring (SHM) due to their small weight and size, ability to be embedded and ability to be multiplexed. So, FBG sensors are commonly used as strain sensors for SHM but their use for ultrasonic guided wave (GW) measurements is not common due to the low sensitivity. In the recent times, a renewed interest is seen in the use of FBG sensors for GW measurements using the edge reflection approach which increases the sensitivity several folds. It has been reported, that the mechanism of the measurement of the incident GW is different based on the relative ratio of the wavelength of the incident GW (GW) and the grating length (L) of the FBG sensor. For ratios GW/L» 1 the propagating wave leads to uniform strain over the FBG resulting in the shift of the Bragg wavelength. For the λGW/L ≈ 1 the FBG experiences non-uniform strain over the FBG which results in the distortion of the spectrum (widening or narrowing) of the peak. By separating these effects on the FBG, mode filtering may be achieved. In the previous work the mode filtering was achieved by scanning the entire reflectivity spectrum of the FBG (over 300 points). This approach is time consuming and hence has limited applicability for in-service SHM. Hence, a novel method which uses only measurements at 2 locations on the spectrum is proposed in this paper. The cosine distance in the waveforms is calculated and then used for identifying the mode. This information is then used for damage localization on a simple plate.
STRUCTURAL INTEGRITY ASSESSMENT OF NUCLEAR SPENT FUEL CANISTERS USING GUIDED WAVES
Authors: LIVADIOTIS STYLIANOS , LEE GUAN-WEI , WILSON NATHAN , SALAMONE SALVATORE
Published: December 2023

Dry storage canisters (DSC) are primarily used for storing nuclear spent fuel rods for an extended period. Due to the critical role of these assemblies, periodic inspections are necessary for mitigating potential accidents and subsequent release of radioactive material to the environment. Aside from visual inspections, the most effective approach to evaluate their structural integrity is by non-destructive techniques. In this work, we utilize helical guided ultrasonic waves (HGUW) to develop a non-destructive scheme for the structural health monitoring of DSC. These waves share identical characteristics with traditional Lamb waves but travel circumferentially in cylindrical waveguides. The proposed methodology is comprised of instrumenting the canister with a permanently attached network of piezoelectric patches (PZT) capable of transmitting and receiving high frequency HGUW. Using the data collected from the HGUW inspection, a probabilistic imaging technique is employed to localize defects within the span of the PZT arrays. Furthermore, an investigation of the scattering of the fundamental Lamb modes from different cracks and notches is investigated and the patterns are exploited for improving the fidelity and accuracy of the imaging method. Experiments have been conducted on various specimens including a 6-in-diameter cylinder in the lab and an actual DSC with a diameter of approximately 6 feet.
ACTIVE SENSING USING LDV AND T-SHAPED ARRAYS IN METALLIC PLATES FOR DAMAGE LOCALIZATION
Authors: LIMA LUIS PAULO M. , PARK GYUHAE
Published: December 2023

In this work, T-shaped arrays of sensors generated by a single laser Doppler vibrometer (LDV) are used for damage localization in a metallic plate. Previous studies have used a single T-shaped array of piezoelectric patches to estimate the direction of arrival of waves in plate-like structures. Here, by comparing the measurements of two and four T-shaped arrays with baseline information, this technique could be extended for damage localization, resulting in an active sensing application. Instead of piezoelectric transducers, a LDV is used to create the T-shaped arrays, which enables the testing of arrays with different numbers of measuring points and different positions. The difference between test and baseline measurements is used, as it contains information on waves from a known acoustic source that scatter and reflect at a damage site. Beamforming is then applied to these residual signals, and the resulting beamforming maps are transformed into a map of positions in the inspected area. The measurements of each array results in one position map, and combining all maps results in an estimated location of the damage. This is demonstrated in a square metallic plate with a single source of vibration located at its center, while the arrays are located at the boundaries of the inspection area. The tests show that even for low density arrays, increasing the number of arrays enables damage detection with reasonably good results, even when employing simple delay-andsum beamforming instead of more advanced and complicated processors. This work also serves as a proof of concept that a set of T-shaped arrays can be reliably used for active sensing of damage in plane plates.
WIRELESS GAIT AND RESPIRATION MONITORING USING NANOCOMPOSITE SENSORS
Authors: PIERCE TAYLOR , LIN YUN-AN , LOH KENNETH J.
Published: December 2023

The measurement of posture, loading conditions, and physiological parameters during physical activity is key in human performance monitoring and assessment. Of particular interest in this study is the monitoring of these parameters during high intensity activities associated with firefighting. The objective is to capture various walking cycles using nanocomposite pressure sensors built into the backpack-type harnesses of a Self-Contained Breathing Apparatus (SCBA) unit. It was hypothesized that the sensor’s high stability, linearity, and sensitivity would allow this sensor to be used for human posture and activity monitoring. First, nanocomposite sensors were prepared by integrating piezoresistive graphene nanosheet thin films between elastomer layers. Two sensors were then integrated with the SCBA harnesses and mounted at symmetric locations to capture gait and respiration cycles. Second, a small, portable, wireless data acquisition unit was developed to non-intrusively monitor up to eight sensors and wirelessly transmit the data for external data storage and analysis. This sensing node included analog signal conditioning circuits alongside an ARM based microprocessor for analog to digital conversion, signal processing, and wireless transmission. Third, human participant tests were performed while wearing these harnesses. The participants performed various low intensity walking and respiratory cycles. The results confirmed that the wireless sensing unit was able to reliably acquire sensor measurements, while the sensing streams also exhibited unique features indicative of different activities and postures.
DETECTING GAIT ABNORMALITIES IN FOOT-FLOOR CONTACTS DURING WALKING THROUGH FOOTSTEP- INDUCED STRUCTURAL VIBRATIONS
Authors: DONG YIWEN , WU YUYAN , NOH HAEYOUNG
Published: December 2023

This study aims to detect abnormal human gait patterns through the dynamic response of floor structures during foot-floor interactions. Gait abnormality detection is critical for the early discovery and progressive tracking of musculoskeletal and neurological disorders, such as Parkinson’s and Cerebral Palsy. Especially, analyzing the foot-floor contacts during walking provides important insights into gait patterns, such as contact area, contact force, and contact time, enabling gait abnormality detection through these measurements. Existing studies use various sensing devices to capture such information, including cameras, wearables, and force plates. However, the former two lack force-related information, making it difficult to identify the causes of gait health issues, while the latter has limited coverage of the walking path. In this study, we leverage footstep-induced structural vibrations to infer foot-floor contact profiles, which allows force-informed and more wide-ranged gait abnormality detection. The main challenge lies in modeling the complex force transfer mechanism between the foot and the floor surfaces, leading to difficulty in reconstructing the force and contact profile during foot-floor interaction using structural vibrations. To overcome the challenge, we first characterize the floor vibration for each contact type (e.g., heel, midfoot, and toe contact) to understand how contact forces and areas affect the induced floor vibration. Then, we leverage the time-frequency response spectrum resulting from those contacts to develop features that are representative of each contact type. Finally, gait abnormalities are detected by comparing the predicted foot-floor contact force and motion with the healthy gait. To evaluate our approach, we conducted a real-world walking experiment with 8 subjects. Our approach achieves 91.6% and 96.7% accuracy in predicting contact type and time, respectively, leading to 91.9% accuracy in detecting various types of gait abnormalities, including asymmetry, dragging, and midfoot/toe contacts.
SMART SENSING TECHNOLOGY AND ITS AID IN FLOOD DATA ANALYSIS FOR NORTHERN NEW MEXICO
Authors: MOREU FERNANDO , THIERGART TIMOTHY JACOB , MOHAMMADKHORASANI ALI , MALEK KAVEH
Published: December 2023

This paper addresses the need for infrastructure protection in Ohkay Owingeh, a tribal community located in a high desert region with a pronounced monsoon season. The extended dry period of 8-9 months makes the area susceptible to flooding during the monsoon season, leading to significant disruptions in transportation, infrastructure damage, and the displacement of tribal members. To mitigate these challenges, the adoption of smart sensing sonar LEWIS technology is proposed. The LEWIS sonar system will enable the detection of flood activity by measuring water level fluctuations. This valuable information will provide tribal members with an alert system to monitor and respond to flood events promptly. Moreover, the data gathered by the LEWIS Sonar will empower the tribal community of Ohkay Owingeh to take control of the current situation and make informed decisions for future flood prevention measures.
QUASI-STATIC COMPONENT GENERATION OF GUIDED WAVES AND ITS APPLICATIONS ON DAMAGE DETECTION
Authors: LI WEIBIN , JIANG CHANG , DENG MINGXI , QING XINLIN
Published: December 2023

Quasi-static component (QSC) generation is a typical nonlinear effect of ultrasonic wave propagation, which can be used for materials characterization with the features of high sensitivity and low attenuative effect (generated QSC pulse's carrier wave frequency is zero). This study presents a novel method for early-stage microdamage detection and localization using QSC generation of ultrasonic guide wave L(0,1) mode propagation in pipes under group velocity mismatching condition. Finite element (FE) model was developed to provide insights on the generation and propagation characteristics of the QSC induced by both the global weak material nonlinearity and local microdamage in metallic pipes. FE analysis verified the L(0,1) mode of the QSC. The cumulation feature of QSC pulse was obtained in terms of the temporal pulse width and the pulse amplitude. A microdamage localization method was pro-posed based on the L(0,1)-QSC mode pair. Experiments were conducted in corrosion-induced aluminum pipes to investigate the QSC pulse signals. The QSCrelated nonlinear pulse signals caused by the material nonlinearity and micro-damage were detected and identified. The mode of QSC and feasibility of the proposed microdamage localization technique were verified. The FE and experimental results demonstrated the basic properties of QSC generation in isotropic metallic pipes and validated potential applications.
AUTONOMOUS ROBOTIC INSPECTION BASED ON ACTIVE VISION AND DEEP REINFORCEMENT LEARNING
Authors: TANG WEN , JAHANSHAHI MOHAMMAD R.
Published: December 2023

Over the years, various methods based on computer vision have been proposed for the problem of damage detection and segmentation. Recently, remarkable progress has been made in this field owing to the emergence of deep neural networks. However, there is a main assumption among these works that the data collection (e.g., taking photos) is usually carried out by human inspectors, so there is little occlusion or bad lighting conditions. With that being said, the uncertainties that could occur in data collection are handled manually to ensure the dataset is clean and free of confusing or occluded damages. This assumption limits the applicability of autonomous robotic inspection to real-world settings due to the uncertainties in data collection and data interpretation. To bridge this gap, this study integrates the concept of active perception into damage detection and proposes a framework based on the Partially Observable Markov Decision Process (POMDP) and Deep Reinforcement Learning (DRL). The proposed framework facilitates the learning process for robotic agents to explore the 3D environment and intelligently select informative viewpoints to reduce uncertainty and minimize confusion, which leads to more reliable decision-making. Besides uncertainty reduction, the DRL agent can also inspect the workspace more efficiently compared with traditional raster scanning. The trained DRL agent is evaluated for the autonomous assessment of cracks on metallic surfaces. Results show that the agent equipped with the active perception module outperforms the raster scanning inspection by 57% in terms of crack IoU. In addition, the DRL agent can reduce the total inspection time by two times while the prediction accuracy is on par with the raster scanning.
REINFORCEMENT LEARNING-BASED BRIDGE INSPECTION MANAGEMENT
Authors: ZHANG XIN , SALMERON MANUEL , WOGEN BENJAMIN E. , LIU XIAOYU , ITURBURU LISSETTE , DYKE SHIRLEY
Published: December 2023

Biannual inspections are required to assess the physical and functional condition of our nation’s bridges. The Federal Highway Administration (FHWA) and various Departments of Transportation (DOT) in the United States periodically update specifications and techniques to normalize and advance the bridge inspection procedures. However, some ambiguity remains in these inspection requirements. One relevant example relates to inspection intervals and techniques. Currently, FHWA requires routine bridge inspection at least every two years, and if necessary, inspectors can adjust the inspection frequency. The details of how one would adjust the inspection frequency is not specified. And while many advanced techniques, e.g., ultrasonic surface wave and AI-based image inspection methods, can be applied to inspect bridges, the rationale to use these techniques relies on bridge inspectors’ experience. This study focuses on developing a reinforcement learning-based method to assist inspectors in managing bridge inspection planning. In this method, a reinforcement learning algorithm is utilized to optimize the frequency of inspection and the selection of the inspection method. A physics-based damage development model is utilized to simulate the deterioration process of the bridge. The reward function designed in the reinforcement learning process considers both economic cost and inspection plan risk. After training, the reinforcement learning agent can rapidly determine an optimal bridge inspection policy based on a bridge’s state, which can minimize both the cost and the risk of bridge inspection work. Thus, inspectors can refer to this agent to make a specific inspection plan for each bridge based on a bridge’s design, history, and features.
“GEN III” PIEZOELECTRIC PMN-PZT SINGLE CRYSTAL SENSORS AND ACTUATORS FOR STRUCTURAL HEALTH MONITORING APPLICATION
Authors: JOO HYUN-JAE , KIM MOON-CHAN , LEE HO-YONG
Published: December 2023

Crystallographically engineered Relaxor-PT single crystals, specifically PMN-PT (Generation I) and PIN-PMN-PT/PMN-PZT (Generation II), offer much higher piezoelectric and electromechanical coupling coefficients (d33 > 1,500 pC/N, k33 > 0.9), when compared to polycrystalline PZT ceramics. Recently Ceracomp Co., Ltd. (www.ceracomp.com) has developed the solid-state single crystal growth (SSCG) technique and successfully fabricated Gen III PMN-PZT single crystals modified with acceptors or donors [Fig. 1]. The piezoelectric constants (d33) of (001) Gen III PMN-PZT single crystals were measured to be higher than 4,000 pC/N and thus about two times higher than those of PMN-PT/PZN-PT (Gen I) and PIN-PMN-PT/PMN-PZT (Gen II) single crystals. The Gen III PMN-PZT single crystals have been firstly applied to single crystal-epoxy composites, ultrasonic transducers, piezoelectric sensors, and piezoelectric actuators [Fig. 2]. In this presentation, we will introduce the development of high performance piezoelectric sensors and actuators by using the Gen III PMN-PZT single crystals for SHM (structural health monitoring) application.
CURING MONITORING OF COMPOSITE PATCH USING ELECTROMECHANICAL IMPEDANCE
Authors: WEN JINSHAN , ZHU JIANJIAN , WANG YISHOU , QING XINLIN
Published: December 2023

The repair technology of surface-bonded composite patches has garnered significant attention in the engineering field. The quality of the repair is directly impacted by the curing degree of the patch. Thus, monitoring the curing process of the patches is necessary. This paper proposes a real-time monitoring method for the curing of composite patches based on electromechanical impedance (EMI) technology. The proposed method can accurately track the curing process of composite patches. A piezoelectric sensor was embedded in T300 woven carbon fiber prepreg, and EMI signals were collected at 2-minute intervals during the curing process. Dielectric analysis (DEA) was performed to verify the effectiveness and feasibility of the method. The resonant resistance and correlation coefficient (CC) index were utilized to characterize the curing process of the patches. The experimental results demonstrate that the resonant resistance remains stable when the resin is converted to approximately 85%. The development trend of the CC aligns with the curing behavior of the resin, and the rate of change of the CC can reflect the speed of resin conversion. Furthermore, the proposed method can accurately monitor the curing process of both the carbon fiber prepreg patches and those bonded to an aluminum plate, demonstrating the universality of this method.
A FEW-SHOT LEARNING FRAMEWORK FOR ROTOR UNBALANCE AND SHAFT CRACK FAULT DIAGNOSTIC BASED ON PHYSICS-INFORMED NEURAL NETWORK
Authors: DENG WEIKUN , NGUYEN KHANH T. P. , GOGU CHRISTIAN , MORIO JEROME , MEDJAHER KAMAL
Published: December 2023

This study aims to detect and localize rotor unbalance and shaft crack damage in a few-shot data scenario. It proposes a reinforcement learning-based approach with physics preferences (called RLP2). RLP2 is used to guide the physics consistency in the rotor finite element mimetic neural network (RFEMNN). The RFEMNN is first trained in an unsupervised manner using mixed simulation and experimental datasets in the task of reconstructing rotor’s vibration signals. Then, the RFEMNN is fine-tuned in the RLP2 framework using a physics preference reward as policy loss to ensure similarity between hidden layer output and rotor system parameters. The output of the RFEMNN is fed into a downstream multi-output convolutional neural network (CNN) for fault diagnostic and localization. The proposed method’s effectiveness is demonstrated through experiments on a PT500 platform under zero-shot, one-shot, and few-shot learning scenarios. The obtained results indicate the potential of this method for the predictive maintenance of rotor systems in real-world applications with limited training data.