bluuebunny/crossref_metadata_2025 huggingface dataset:
A NOVEL NUMERICAL APPROACH FOR FATIGUE LOAD EMULATION OF OFFSHORE WIND TURBINES USING MACHINE LEARNING
Authors: BOTERO MIGUEL RESTREPO , ILIOPOULOS ALEXANDROS , STINENBOSCH TOBIAS , BEAUDET LAURENT
Published: December 2023

During their lifetime, offshore wind turbines are subjected to complex loading conditions. Understanding the loading history of the support structure of these structures and the long-term implications on the structural integrity renders structural health monitoring (SHM) imperative. In that direction, it is common practice in the wind turbine industry to use only a few physical sensors in a small number of intelligent turbines per fleet to directly measure the load levels in the support structure, implying SHM insights limited to only the instrumented turbines. This often leaves stakeholders with insufficient information on a farm level, not facilitating important decisions regarding project lifetime or adjustments to the trade-off between energy harvest and fatigue damage accumulation through upgraded controller behavior. To bridge this gap, machine learning models have been used as surrogate models with the purpose of virtually sensing fatigue loads through a process known as load emulation. However, previous applications have used site-specific, position-specific training data to develop the machine learning models. As such, the resulting surrogate model decreases in performance when asked to extrapolate to a different site, or even to a different position of the same wind farm. This research presents a novel methodology for constructing a single machine learning load emulation object that is useful for emulating fatigue loads in a generic concept, applicable to any wind turbine within a wide, pre-defined solution space without loss in accuracy. The methodology introduces the use of simplified structural models which preserve key degrees of freedom of the geometric and dynamic properties to represent potential offshore wind sites that cover the desired solution space. These structural models are used to run 10-minute, hydro-servo-aeroelastic numerical simulations and the results are used to train the machine learning model. Load emulation is performed at the foundation-tower interface level. Finally, the surrogate model is validated by comparing the emulated loads from the novel simplified approach against the detailed loads from the numerical assessment of site-specific turbine models at two offshore sites in the North Sea.
WIRELESS STRAIN MONITORING SYSTEM ON THE HERNANDO DE SOTO BRIDGE DURING CRITICAL REPAIRS
Authors: KALANTARI KHANDANI MEHDI KALANTARI , GHORBANISHEIKHNESHIN MOHEB
Published: December 2023

The article discusses the use of a wireless structural health monitoring system supplied by Resensys, after a major fracture was discovered in the tie girder of one of the arch span bridge units on the Hernando de Soto Bridge. The bridge is significant to the US transportation system and the business community in Memphis, as it connects Memphis to Arkansas and most western states in the US. The fracture discovery resulted in an immediate shutdown of the bridge, causing significant economic impacts due to traffic rerouting and massive congestion. According to multiple reports and studies, the cost of closure of the bridge was estimated to be $2-3 million per day. Due to the high urgency of the repairs, monitoring and instrumentation had to be done quickly and before conducting repairs on the tie girder. The Resensys SenSpot™ [1] strain gauges were a perfect solution, providing reliable, precise, and real-time data (strain and temperature) on all high-risk members. The wireless strain gauges were attached to all high-risk members to monitor loads during the repair process, which involved applying tension to the fractured members. Furthermore, the strain gauges monitored strain/stress in critical members when heavier equipment such as cranes were moved on the bridge to carry special equipment and retrofit plates. The Resensys monitoring system provided data to help the bridge repair engineers gather information around real-time strain, and studying stresses and strains on critical elements caused by thermal effects and live loads has helped to ensure that the repair process was effective. Due to the size and other complexities of this project, wiring systems and their associated installation on structures were cost prohibitive. Resensys wireless monitoring system provided numerous benefits in the project which made the implementation of the monitoring program cost-effective and practical. These advantages include longevity, fast and easy installation, cloud-based monitoring, superior sensing, advantageous in construction sites, reusability, etc. Wireless SenSpot™ sensors use non-rechargeable batteries with a battery life of ten years. SeniMax™ [2] remote communication gateways are solar powered. As a result, the complete system is energy self-sufficient and does not require access to external electrical input or infrastructure for its operation.
ON CONDITION MONITORING OF A CORRODING STEEL TRUSS BRIDGE – A CASE STUDY
Authors: SARAVANAN U. , LENKA KAIBALYA
Published: December 2023

A railway steel truss bridge connecting the mainland India with Rameswaram had corrosion issues. This bridge was continuously monitored from August 2020 through December 2022 to ensure the serviceability of the bridge. This paper summarizes the technical learning from the monitoring. The truss bridge was heavily instrumented – 84 out of 92 members were instrumented with linear electrical strain gauges, 20 of the 52 nodes had biaxial accelerometers, and 10 resistance-based temperature sensors. For each train pass, the collected data was analyzed to estimate the axle loads of the train, cross-sectional areas of the members, and certain other parameters from the acceleration time history. While the observed strains could be matched excellently with the strains estimated by simple truss analysis in 70 members, the computed accelerations were the order of magnitude lower for all the acceleration measurements. The displacement profile obtained by double integrating the acceleration with appropriate filtering, as suggested in the literature, did not agree with the predicted displacement even qualitatively. As one would expect, even though there was a steady deterioration of the structure, the commonly used dynamic response parameters – the natural frequency and mode shapes – did not reflect the change statistically. The extreme strains in most of the members showed a steady increase or decrease in values. But the truss being statically determinate, the strains could not capture the loss in the area of members due to corrosion at locations other than where they were located. However, certain frequency and time domain parameters of the acceleration were able to capture the steady deterioration of the truss bridge. Thus, in the case of statically determinate truss bridges, data-driven approaches seem to perform better than physics-based approaches in determining the changes occurring in the bridge.
INTEGRATING PRE-EXISTING TELECOMMUNICATION FIBER CABLE VIBRATION SENSING AND DRIVE-BY VEHICLE VIBRATION SENSING FOR SCALABLE BRIDGE HEALTH MONITORING
Authors: LIU JINGXIAO , YUAN SIYUAN , BIONDI BIONDO , NOH HAE YOUNG
Published: December 2023

We introduce a novel and scalable bridge health monitoring approach by combining pre-existing telecommunication fiber vibration sensing and drive-by vehicle vibration sensing. Many bridges have pre-existing telecommunication fiber cables crossing in conduits, which can function as a distributed acoustic sensing system to continuously record bridge dynamic strain responses in high spatiotemporal resolution. In addition, the drive-by vehicle vibrations capture the information of the input load to the bridge and the interactive bridge vibrations with high spatial resolution. Our approach integrates the two sensing systems to offer complementary input-output information and insights into bridge conditions. It estimates bridge modal properties by modeling the vehicle-bridgefiber interaction with an augmented state-space model. The model considers the bridge dynamics and input loads as a joint state observed by the telecommunication fiber vibration and drive-by vehicle vibration sensing systems, respectively. Our approach is scalable as it does not require on-site installation and maintenance of sensing systems on the bridge. It is also more accurate than using a single sensing system because it takes into account both the input and output signals of the system being analyzed. We evaluate our approach with real-world experiments on a steel stringer/multi-beam bridge in Palo Alto, California, with telecommunication fiber cables running under the deck. Our approach successfully estimates bridge dynamic properties, including natural frequency, damping ratio, and mode shape. It outperforms a baseline method that only uses telecommunication fiber vibrations, which indicates the potential for accurate and scalable bridge health monitoring.
A DATA-SPARSE APPROACH TO IN-SITU FAULT DETECTION AND IDENTIFICATION FOR METAL ADDITIVE MANUFACTURING
Authors: CHEN ALVIN , KOPSAFTOPOULOS FOTIS , MISHRA SANDIPAN
Published: December 2023

With increasing adoption of metal additive manufacturing (AM) in manufacturing, detecting faults in the printing process has the potential to reduce waste from failed prints and streamline the production process. To increase robustness of anomaly detection, a statistical method of detecting faults from melt pool images is presented. This method uses parametric identification of 1D compression of melt pool images to build a nominal predictive model. Nominal melt pools result in residuals that are Gaussian white noise processes, whereas anomalous melt pools will not follow this distribution. Detection is performed through statistical comparison of incoming data with a nominal reference generated on sparse data. This approach successfully applies statistical time-series methods to detect anomalous melt pools in a metal AM process.
BEST RECONSTRUCTION FREQUENCY OF LAMB WAVES VIA BROADBAND MEASUREMENT
Authors: KAPURIA SANTOSH
Published: December 2023

This article presents the theoretical basis of the best reconstruction frequency (BRF) of Lamb waves. It has been proposed earlier by the author’s group as the probing frequency in the refined time-reversal method for damage detection to achieve enhanced sensitivity and accuracy. It is shown to be the frequency at which the amplitude dispersion of the main mode of the reconstructed signal is minimum. It is then possible to compute the BRF from a single measurement of Lamb wave response under a broadband (e.g., Gaussian) excitation. Thus, it is no longer required to compute the similarity at different central frequencies of the narrowband input. It is further shown that the BRF is a system property of a given transducer-plate-adhesive system, which is independent of the distance between the transducers used for the time-reversal method in pitch-catch mode. This property makes it suitable for use when a network of sensing paths is used to identify damage locations.
THE EFFECT OF TEMPERATURE ON GUIDED WAVE SIGNAL CHARACEERISTICS IN A HONEYCOMB COMPOSITE SANDWICH STRUCTURE WITH DISBOND AND DELAMINATION
Authors: B RAMANA RAJA , TALLUR SIDDHARTH , BANERJEE SAUVIK
Published: December 2023

Researchers developing guided wave (GW) based structural health monitoring (SHM) techniques frequently utilize amplitude and group velocity variations to detect and localize damage. However, external factors such as temperature and moisture can affect these features. To address this, a coordinated numerical and experimental study was conducted to investigate GW propagation characteristics in honeycomb composite sandwich structures (HCSS) with two types of damage: disbond and delamination, across a temperature range of 0° to 90° C. Computationally efficient two-dimensional (2D) numerical models were developed using COMSOL Multiphysics that takes into account a variety of temperature-related phenomena, such as thermal stresses and changes in the material properties of honeycomb sandwich and piezoelectric wafer transducers (PZTs). The amplitude and group velocity of the fundamental anti-symmetric (A0) mode are found to increase with disbond and decrease with delamination. Additionally, the normalised amplitude of the A0 mode linearly decreased with increasing temperature for both healthy and damaged cases. Given the A0 mode’s wide usage for damage detection, an adjustment equation for amplitude and group velocity with temperature change is proposed.
DIFFERENTIAL STRATEGY TO HIGH-SPEED INSPECTION OF RAILS VIA PASSIVE ULTRASONIC MONITORING
Authors: BATISTA IZABELA C. , HOSSEINZADEH ALI ZARE , DATTA DIPTOJIT , SCALEA FRANCESCO LANZA DI
Published: December 2023

This work presents an amplitude-imbalance identification approach to noncontact high-speed rail inspections. The passive monitoring utilizes an array of capacitive aircoupled ultrasonic transducers for data acquisition of ultrasonic-guided waves propagating in the rail. The excitation is generated by a combination of the test car’s wheel-rail friction and white noise generated by two additional actuators. The transfer function is reconstructed passively between two air-coupled sensors and transformed to the time domain by deconvolution. When discontinuities are present in the rail, the signature waveform in the time domain transfer function will change due to scattering. These changes in the amplitude of the reconstructed signal can be associated with the potential presence of a flaw. This method is referred to as the conventional approach to defect detection. However, tracking changes in one waveform is still subject to variability due to changing test conditions, different rail geometries, wear, poorer signal strength, and other rail anomalies that may be falsely flagged as defects. This paper presents a more robust defect detection strategy achieved by simultaneously assessing amplitude-related features from time signals of two sensors pairs probing adjacent segments of rail and using any significant mismatch as the indicator of an internal rail flaw in one of the two segments, hence, the differential strategy for defect detection. The performance of such a method in detecting flaws was assessed via receiver operating characteristic curves on data acquired from field tests at testing speeds of 40 mph conducted at the Transportation Technology Center Inc (TTCI) in Pueblo, CO.
RAY TRACING METHODOLOGY FOR ELASTIC WAVE PROPAGATION IMPROVE SIMULATION APPLIED TO AERONAUTIC COMPOSITE STRUCTURES
Authors: IGLESIAS FERNANDO SÁNCHEZ , LÓPEZ ANTONIO FERNÁNDEZ , GORDO ALFREDO GÜEMES
Published: December 2023

Data processing and simulations for guided wave based Structural Health Monitoring (SHM) systems can be extremely challenging, especially in complex geometries. Aerospace structures, specifically, may contain integrated stiffeners, thickness changes and other structural details, which will result in a very complex signal on the sensor network due to the multiple reflection of the multiple modes on the structural elements. Currently, the most common methodologies to simulate Lamb waves are generally based in the finite element method (FEM), spectral element method (SEM). FEM models require a large amount of computational resources and therefore are limited in the size and number of cases that could be calculated, and SEM present some difficulties to implement out of plane reinforcements and to modelize structural details. For this reason, being able to perform a fast and efficient assessment of the propagation of elastic waves can be very helpful to reduce the need of physical tests, and could be used to identify the critical cases to run with a more detailed numerical simulation or to perform an stochastic analysis. In an attempt to solve this problem, this study presents an analytical methodology based on the ray tracing method, able to solve the propagation of symmetric and anti-symmetric elastic waves on a 2D space and able to take into account different material characteristics, propagation velocities and simple boundaries; the methodology considers different propagation modes independently and takes into account the splitting of rays and possible mode changes when encountering a boundary during the propagation. The capabilities of this method are demonstrated on a series of analytical study cases and compared against physical tests, presenting an equivalent or better correlation than the finite element method, with a substantial reduction in the computational cost.
MEASURING THE GOLF SWING PATTERN USING MOTION TAPE FOR FEEDBACK AND FAULT DETECTION
Authors: HUANG SHIH-CHAO , LIN YUN-AN , PIERCE TAYLOR , WYCKOFF ELIJAH , LOH KENNETH J.
Published: December 2023

Golfers must hone the sequence of the golf swing for consistent and efficient results, where a good golf shot is both precise and accurate. It takes countless hours of practice to develop the skill, and methods such as video feedback and coaching serve as aids to the process. However, few methods outside of visual observations exist to identify factors in the swing that cause a poor shot. Most golf analysis equipment is expensive and requires extensive setup time. Some systems only measure the physics of the ball and are limited to the practice range, whereas wearable sensors for golf are limited to specific motions such as the wrist. To address these challenges, a fabric-based, on-body sensor was developed and investigated to assess biomechanical movements during the swing. The wearable sensor, herein referred to as Motion Tape (MT), is a low-profile, disposable, self-adhesive, skin-strain sensor formed by spray-coating piezoresistive graphene nanocomposites directly onto kinesiology tape (K-tape). The objective of this study is to use MT to identify key movements in the swing sequence at four body locations: wrist, flexor carpi, anterior deltoid, and torso. First, MT sensors were fabricated for testing. Second, a human subject test protocol recording the golf swing of an experienced golfer was designed and conducted with participants wearing four MT sensors at the aforementioned locations. Last, the test data were processed, and the results showed that MT was able to identify unique movements during the swing. The MT data was analyzed using machine learning algorithms to identify movement abnormalities associated with poor swings. This allows for analysis of swing tempo for direct feedback to the golfer for improved performance.
EMOTION RECOGNITION USING FOOTSTEP-INDUCED FLOOR VIBRATION SIGNALS
Authors: WU YUYAN , DONG YIWEN , VAID SUMER , HARARI GABRIELLA M. , NOH HAE YOUNG
Published: December 2023

Structural vibrations induced by human footsteps contain rich information that can be used for a wide range of applications, including occupant identification, localization, activity recognition, and health and emotional state estimation. Among these, emotion recognition holds great potential for improving smart buildings by enabling mental health monitoring and human-centric services. Existing emotion recognition approaches use cameras, wearables, and mobile devices to capture people’s changing gait patterns under various emotional states. However, these approaches come with corresponding drawbacks, such as being limited by visual obstructions and requiring users to carry devices that cause discomfort. To overcome these drawbacks, we introduce a new emotion recognition approach using footstep-induced structural vibration signals. The main intuition of this approach is that people’s gait patterns change under various emotions [1], thus inducing distinct structural vibration patterns as they walk. Compared to other methods, our approach is non-intrusive, insensitive to visual obstructions, and has fewer perceived-privacy concerns. The main research challenge in developing our approach is that emotions have both explicit and implicit effects on gait, making the explicit gait parameters insufficient to describe such a complex relationship. To this end, we develop a set of emotionsensitive features from the vibration signals, including gait parameters, sequential features, and time-frequency spectrum features to capture both the explicit and implicit effects of emotion on gait. To better integrate multiple types of features, we develop the fully-connected layer, the long-short-term-memory (LSTM) layer, and the convolutional layer to extract information from the features and a multilayer perceptron to estimate emotion. Our approach is evaluated in a real-world walking experiment involving 5 participants with over 100 minutes of footstep-induced floor vibration signals. Our results show that our approach achieves a mean absolute error of 1.33 for valence score estimation and 1.26 for arousal score estimation out of an overall score range of 1 to 9, which has an accuracy of 72% for High / Low valence classification and 82% for High / Low arousal for emotion classification.
HUMAN-MACHINE INTERFACES USING AUGMENTED REALITY
Authors: MOREU FERNANDO , MALEK KAVEH
Published: December 2023

In recent decades, infrastructure aging, new social behavior, urban and rural environmental changes, and nature extreme events have increased in complexity. When disasters occur, saving lives, and providing access to emergency teams is a priority where every second saved is critical. Researchers in Structural Health Monitoring (SHM), government laboratories, and industry leaders are using sensors, field deployments, algorithms, and signal processing to assist and prioritize decisions. If the collection of data would be accelerated with near-real time interface with engineers in the field, emergency responders, safety, and maintenance could be integrated with machines in real-time, and new solutions could be advanced. This paper summarizes new work on human decisions exploring the concept of humanmachine- structure interfaces associated with structural dynamics and damage, to transform human decisions using new interfaces. The interface between human and structures is achieved with Augmented Reality (AR). The results include work in human-in-the-loop with application on near real-time computer vision, human-robot teaming, and a new infrastructure maintenance paradigm centered in augmenting the capabilities of humans in the field. The platform of human-robot teaming is further advanced in dynamics and control of humans using data obtained from robots and vice versa. Future research includes human-centered inspections, and humanmachine control theory.
MONITORING OF FREEZING WATER OR MELTING ICE IN AIRCRAFT FUEL TANKS AND FUSELAGES BY ACOUSTIC EMISSION
Authors: PFEIFFER HELGE , SEVENO DAVID , REYNAERT JOHAN , JORDAENS PIETER JAN , CEYHAN ÖZLEM , WEVERS MARTINE
Published: December 2023

It is a mostly overlooked phenomenon in physical chemistry that matter produces characteristic sound emissions when passing through a phase transition. The origin of this sound is not yet fully understood, but it is certain that sudden changes in volume, cracks, friction between crystallites and other sources must be considered, but a generally accepted theory of the "sound of phase transitions" is lacking. But even if the cause is not completely clear, this phenomenon can be used to detect the presence of these substances in technical structures. This is important, for example, in the case of water and ice in aircraft fuel tanks. Water arising from contamination and condensation is frequently found in fuel tanks and regular drainage procedure are important to guarantee the safety of systems and structures. While ice dispersed in the kerosene phase can seriously hinder the combustion process, blocks of ice can cause serious crack formation as in valves and tubes. A practical problem with all drainage procedures after flights at freezing conditions is the right time to start that process. Starting too early would mean that the remaining ice cannot be removed and waiting too long is an economic problem because it increases the aircraft's downtime. Unfortunately, there is no technology yet that tells mechanics when all the water has melted. It would be beneficial for maintenance teams to find the right time to drain, and acoustic emissions from the melting ice would be the ideal tool to determine this moment. For this purpose, acoustic sensors are attached to the skin of the tank walls, and the acoustic signals from the ice are intense enough to propagate through media, the aluminum sheets and coating. In this way, the completion of the ice melt is determined by the time at which the acoustic emission stops. We present measurements on a laboratory scale, results from a realistic climate chamber on a tank model and the first results from a campaign on an operational aircraft (Airbus A330). We were able to show that relevant amounts of melted ice can be reliably determined, e.g., 30 ml of water under the kerosene phase in a replica fuel tank generate about 200,000 distinguishable signals, in our case these signals are acoustic transients. This is quite sufficient to obtain the desired information about the state of the melting ice. In addition, to address other structures, results of ice melting and water freezing processes on an aircraft fuselage model are presented.
PHYSICS-INFORMED GAUSSIAN PROCESSES FOR WAVE LOADING PREDICTION
Authors: PITCHFORTH DANIEL J. , MILLS ROBIN S. , ROGERS TIMOTHY J. , TYGESEN ULF T. , CROSS ELIZABETH J.
Published: December 2023

The quantification of wave loading is an important step within the estimation of fatigue accrual within offshore structures. The direct measurement of wave loads can be both challenging and expensive, often requiring the installation of bespoke systems if at all possible. The estimation of wave loads based on data from other sensors, more commonly found on offshore structures (e.g. wave radars) is therefore highly desirable. This paper presents an experimental study of a monopile structure within a wave tank, instrumented with accelerometers, strain gauges, a force collar, wave gauges and a velocimeter subject to a range of wave conditions. Here the dataset is used to construct models which combine data-based Gaussian process NARX models with linear wave theory. The novel model structures presented rely on only wave gauge data as an input and achieve improved predictive performance over purely data-based approaches across a range of wave states.
TEMPERATURE-RESPONSIVE AND PASSIVE WIRELESS MECHANICAL METAMATERIAL SENSORS
Authors: NAIDU VISHNU R. , PARK YUJIN , LOH KENNETH J.
Published: December 2023

Knowing the location and environmental conditions of sailors that have fallen overboard can greatly facilitate open water search and rescue operations. Currently, active sensors that trigger an alarm when a sailor falls overboard exist, and it works by detecting a loss of signal from a transmitter. However, their applications have been limited because of the dependence on a working battery, as well as the fact that sailor location cannot be tracked beyond the one-time loss-of-signal event. In this study, a passive, person-overboard sensing concept is proposed, and the focus is to demonstrate monitoring of seawater conditions. The passive sensor was designed by incorporating a temperature-responsive hydrogel with an auxetic star pattern unit cell geometry, which transforms from a two- to three-dimensional geometry when immersed in low temperature liquid. First, the passive sensor was formed by incorporating a temperature-responsive hydrogel at opposite ends of the star pattern. The time-dependent swelling and de-swelling behavior of the copolymer hydrogel was characterized to understand the mechanical strains induced after exposure to low temperature water. Second, the design of the star pattern geometry was optimized, and artificial imperfections in the form of notches were employed to allow shape transformation to take place at appropriate and minimal applied strains. The vision is that these shape morphing structures with integrated antennas can serve as passive sensors, which, when interrogated by a remote reader, can be used to monitor how long overboard sailors have been in a low-temperature open sea environment.
MULTIFUNCTIONAL CHARACTERIZATION OF 3D PRINTED STRUCTURAL BATTERY COMPOSITES FOR BATTERY HEALTH MONITORING
Authors: CHEN YUEKUN , DONG XIANGYANG
Published: December 2023

As a promising lightweight multifunctional material, carbon fiber structural battery composites have great potentials to enable longer service life and operating distance for the rapidly increasing mobile electric technologies. While simultaneously carrying mechanical loads and storing electrical energy, the developed multifunctional composites can achieve “massless” energy storage and further extend to sensing and energy harvesting for self-powered structural health monitoring. However, it is still very challenging to predict the state-of-health of structural battery composites due to a lack of understanding of underlying coupled mechanical-electrochemical phenomena during operation. In this study, we first use a novel 3D printing method to fabricate and tailor microstructure of the multifunctional carbon fiber composites. With an optimal electrode layer thickness of 0.4 mm, the stable specific capacity at 1C reaches over 80% of the theoretical capacity of the electrode active materials (lithium iron phosphate) with an average energy density of 152 Wh/kg observed. The corresponding flexural modulus and flexural strength are 8.7 GPa and 69.6 MPa, respectively. The state-of-health of 3D printed structural battery composites under electrochemical cycling and external mechanical loadings are also investigated. The mechanical performance is not affected by the electrochemical charge-discharge processes. The structural battery composites under three-point bending testing show good capacity retention with rapid degradation of electrochemical performance observed near fracture point. The findings from this study not only provide insights for monitoring the state-of-health of structural battery but also show mechanical-electrochemical coupling as a potential way of self-powered structural health monitoring through the 3D printed multifunctional composites.
IDENTIFYING THE LOCATION OF CRACKS IN INTELLIGENT CARBON BASED TRC ELEMENTS
Authors: GABEN MAHDI , GOLDFELD YISKA
Published: December 2023

The goal of the study is to develop an identification procedure that identifies the location of cracks within textile reinforced concrete (TRC) elements by using their smart self-sensory capabilities. To answer this goal the investigation offers to adopt the principles of the time domain reflectometer (TDR) analysis and to explore the changes of the spectrum of the impedance. In order to use the concept, the study considers the electrical characterization of the sensory carbon yarns, mainly the dependency of the impedance with the yarn’s length and offers a calibration procedure. It was found that the procedure has the capabilities to identify all cracking events but also involved additional false alarm scenarios. It is further demonstrated that only the location of the first crack was accurately identified.
NON-LINEAR SIGNATURE IN ULTRASONIC PULSE- ECHO SIGNAL FOR STRUCTURAL HEALTH MONITORING OF FATIGUE INDUCED COMPOSITE STRUCTURES
Authors: AHMED HOSSAIN , SADAF ASEF ISHRAQ , BANERJEE SOURAV
Published: December 2023

Experimental evaluation of material state damage due to frequency varied fatigue loading has been reported in this article by estimating the non-linearity in ultrasonic signals in CFRP composite structures. In recent years, researchers have been utilizing the non-linearity in Lamb wave propagation for structural health monitoring, and thus it is becoming a powerful technique for non-destructive evaluation. Unlike isotropic and homogeneous materials, the damage state modeling of composite structures is complex due to their heterogeneous arrangement of material constituents, especially in fatigue induced loading cycles. Although established for metals and alloys, the quantification of material state of carbon fiber reinforced viscoelastic polymer composites due to dynamic loading environment is still under an active research area. This research evaluates the non-linearity effect in stress relaxation using high frequency (~25 MHz) ultrasonic pulse-echo signals. A set of tensile test specimen as per ASTM standard is prepared and fatigue loads are applied at constant time intervals. During these intervals, scanning acoustic microscope is used to generate and capture pulse-echo signals. The change of second and third order non-linearity parameter of ultrasonic pressure waves are correlated with the fatigue induced internal stresses and damage accumulations. Initial investigation indicates that the higher order non-linearity is a function of applied fatigue loading frequency and the remaining life of the composite structure.
LUGÁN: arte, tecnología y erotismo.
Authors: Merino Martínez Aitor
Published: December 2023

A lo largo de este artículo analizaremos cuáles fueron los elementos que convirtieron a Luis García Núñez —pintor constructivista— en LUGÁN —creador de objetos audio-visotáctiles—. Una de las principales características de la producción de LUGÁN fue su oposición al régimen ocular-centrista, por lo que a lo largo de su carrera exigió al público emplear no solo la visión en la contemplación de sus creaciones artísticas, sino también el oído, el tacto, e incluso el olfato. Para ello, fue fundamental la incorporación en sus esculturas tanto de elementos tecnológicos como de la electricidad misma. Por otro lado, 20 años antes de que Nicolas Bourriaud expusiese los principios de la estética relacional, los trabajos de LUGÁN buscaban ya la creación de un vínculo no solo con el público, sino también entre el propio público.
«Rèquiem a la memòria de Salvador Espriu» (Xavier Benguerel, 1989): hermenéutica y simbolismo musical en el referente poético de una misa de difuntos.
Authors: Ramos Contioso Sara
Published: December 2023

El estreno de ‘Rèquiem a la memòria de Salvador Espriu’, el cinco de octubre de 1990 en el Palau de la Música Catalana de Barcelona, permite a Xavier Benguerel afrontar la composición de un modelo religioso de naturaleza funeral. El carácter conmemorativo de este trabajo, dedicado a la memoria de Salvador Espriu, justifica un planteamiento en el que la estructura ritual de la misa tridentina convive con la elección de siete poemas del escritor catalán. Esta personalización del género integra el simbolismo poético con el argumento religioso y expone un conjunto de elementos musicales destinados a diferenciar el componente profano como ruptura meditativa en la estructura litúrgica del réquiem. Este artículo pretende estudiar la estética musical de los movimientos centrados en la poesía de Espriu. Para ello se propone una metodología inicial basada en el examen de los textos y su reflexión sobre la muerte, para posteriormente tratar de justificar los recursos musicales que Benguerel plantea sobre ellos. La valoración de la adecuación al texto, así como de la proximidad musical del compositor a la finalidad dramática de Espriu conforma el apartado conclusivo final. Su resolución busca la ratificación del carácter funeral de ‘Rèquiem a la memòria de Salvador Espriu’ y la identificación de sus particularidades constructivas como referentes característicos del estilo de Benguerel.
La demonización del erotismo femenino y la enfermedad mental en la poética de Anne Sexton y Alda Merini: crítica de género
Authors: Anguita Martínez Víctor
Published: December 2023

Este trabajo se presenta como un análisis discursivo, con una perspectiva de género, de los poemas “Her Kind” de Anne Sexton y “Amai teneramente” de Alda Merini, con la intención de verificar la posible existencia de un imaginario diabólico relacionado con la sumisión o transgresión femenina. A través del análisis de las elecciones léxicas de las autoras analizaremos la concepción diabólica del impulso sexual de la mujer y de la disidencia, prestando especial atención a la simbología herética y brujeril. El análisis de las metáforas buscará en todo momento recuperar la relación implícita de la postura de las autoras frente a las expectativas de género.
Electric Vehicle Scheduling in Public Transit with Capacitated Charging Stations
Authors: de Vos Marelot H. , van Lieshout Rolf N. , Dollevoet Twan
Published: December 2023

This paper considers the scheduling of electric vehicles in a public transit system. Our main innovation is that we take into account that charging stations have limited capacity, while also considering partial charging. To solve the problem, we expand a connection-based network in order to track the state of charge of vehicles and model recharging actions. We then formulate the electric vehicle scheduling problem as a path-based binary program, whose linear relaxation we solve using column generation. We find integer feasible solutions using two heuristics: price-and-branch and a diving heuristic, including acceleration strategies. We test the approach using data from the concession Gooi en Vechtstreek in the Netherlands, containing up to 816 trips. The diving heuristic outperforms the other heuristic and solves the entire concession within seven hours of computation time with an optimality gap of less than 3%.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0253 .
A Real-Time Control Policy to Achieve Maximum Throughput of an Online Order Fulfillment Network
Authors: Levin Michael
Published: December 2023

Several major companies operate large online order fulfillment systems to ship goods from fulfillment centers through a distribution network to customer destinations in response to purchase orders. These networks make several types of decisions in real-time to serve customers. First, when a customer places an order, when and where (which fulfillment center) is it fulfilled from? Second, once an order has been packaged, how is it moved through the network to get to the customer? Making optimal decisions can yield significant cost savings or improvements in customer service. Unfortunately, these are large optimization problems, and are furthermore subject to uncertainty in the products and destinations of customer orders and the inventory replenishment of the fulfillment centers. This uncertainty makes the problem difficult to solve to optimality. Although the problem can be modeled as a Markov decision process, solving it exactly using standard computational methods is not possible due to the curse of dimensionality. We propose an alternative approach to this problem. We define a relatively simple real-time control policy and prove that it serves all customer demand if at all possible. This proof is achieved using Lyapunov drift techniques to relate the real-time control performance to the average performance necessary to serve all customers on average. Correspondingly, we characterize the average network performance, which may be used for network topology design while the control policy adapts to real-time stochasticity. We demonstrate the performance and stability properties on a numerical example based on hundreds of Amazon facility locations in the United States. The max-pressure control and greedy policies perform similarly at low demands, but at higher demand the throughput properties of the max-pressure control manifest as improvements in throughput and customer service metrics.

Funding: Financial support from the National Science Foundation [Grant 1935514] is gratefully acknowledged.

Supplemental Material: The e-companion is available at https://doi.org/10.1287/trsc.2023.0096 .
Introduction to the Special Issue on Machine Learning Methods and Applications in Large-Scale Route Planning Problems
Authors: Winkenbach Matthias , Spinler Stefan , Pachon Julian , Konduri Karthik
Published: December 2023

In this paper, we introduce the Special Issue on Machine Learning Methods and Applications in Large-Scale Route Planning Problems, which draws its inspiration from the academic community’s positive reception of the 2021 Amazon Last Mile Routing Research Challenge. We provide a structured overview of the papers featured in this special issue, and briefly discuss other noteworthy contributions to the research challenge. Further, we point the reader to a number of peer-reviewed publications outside of this special issue that directly or indirectly emerged from the research challenge. We conclude by highlighting a number of important priorities for future research into applications of machine learning to real-world route planning problems.
A rare case of immunoglobulin G4-related disease presenting with coronary artery pseudotumor and aneurysm
Authors: Koowattanatianchai Sukrisd , Teawprasert Nichakarn , Limchareon Sornsupha , Kaolawanich Yodying
Published: December 2023

Immunoglobulin G4-related disease (IgG4-RD) is an autoimmune disease characterized by elevated serum IgG4 levels. It has the potential to affect multiple organs. Despite the diverse manifestations of IgG4-RD, the association with coronary artery disease (CAD) remains poorly understood due to limited evidence. We report the case of a 52-year-old male patient who exhibited typical angina upon exertion, accompanied by elevated serum IgG4 levels. Coronary computed tomographic angiography (CCTA) revealed the presence of pseudotumor formations surrounding and aneurysm changes affecting all coronary arteries, consistent with IgG4-RD. The patient was treated with prednisolone and azathioprine, with the possibility of additional rituximab therapy if symptomatology failed to improve. This case sheds light on the rare occurrence of IgG4-RD with coronary artery involvement and underscores the importance of recognizing this unique clinical entity for appropriate management and further research.
Complications secondary to the use of SGLT2 inhibitors in oncological patients: a series of 5 cases
Authors: Posado-Domínguez Luis , Figuero-Pérez Luis , Amores-Martin María Aranzazu , Reguera-Puertas Pablo , Martín-Galache María , Del Barco-Morillo Edel , Fonseca-Sánchez Emilio
Published: December 2023

Sodium-glucose cotransporter-2 (iSGLT2) inhibitors, which include dapagliflozin, canagliflozin and empagliflozin, are a class of drugs initially used in the oral treatment of diabetes, heart failure and renal failure. They target the reabsorption of glucose in the kidney. Although they bring benefit to patients with these conditions and in general produce few adverse effects, in some cases, iSGLT2 can cause serious adverse effects such as metabolic acidosis, and fungal or bacterial urinary infections. Oncology patients, who in general have a weak immune system and are usually treated with chemotherapy and/or immunotherapy, are more susceptible to this type of adverse events than other patients. For this reason, it is necessary to adequately select the patients eligible to receive this type of drug and evaluate the potential benefits for them. In this series of five cases, we present two cases of metabolic acidosis, two cases of bacterial urinary sepsis, and one case of fungal urinary sepsis that occurred in patients admitted to the Medical Oncology Department of the University Hospital of Salamanca in 2023.
Temáticas neoliberais em livros didáticos de ensino de alemão
Authors: Lira Favacho Caspary Rayanne , Arantes Poliana Coeli Costa
Published: December 2023

O presente artigo tem como objetivo discutir a presença de componentes neoliberais, como temáticas, por exemplo, em materiais, legislações e, sobretudo, em livros didáticos de ensino de alemão. Selecionamos o Kursbuch volume A1.1 da coletânea Menschen, a fim de procedermos a um estudo de caso, estabelecendo investigação sobre a presença de discursos neoliberais no contexto de aprendizagem de língua. Desse modo, utilizaremos a perspectiva pêcheuxtiana de Análise do Discurso (Pêcheux, 1975, 1983) e as análises sobre o poder baseadas em Foucault, discutidas a partir de imagens de aprendizes por Arantes (2018). Além disso, referenciais teóricos que se ocupem em tematizar as relações de poder construídas e perpetuadas através de discursos, como Foucault (2002) e Van Dijk (2018 [2008]), ajudarão a investigar atividades e a influência de suas formulações na produção do aprendiz, assim como a atual discussão sobre o neoliberalismo na educação e seus efeitos.
Relações entre cultura, multiletramentos e cognição
Authors: Martins Daiane Aparecida , Cordeiro Isabel Cristina
Published: December 2023

As escolas do campo em suas ideologias procuram formar alunos conscientes de seus papéis na sociedade, levando em conta sua história, sua cultura e as particularidades de cada comunidade, na qual essas instituições estão inseridas. Todavia, por inúmeros fatores, parte desses objetivos acabam se perdendo. O texto a seguir, por meio de pesquisa bibliográfica, principalmente em autores como Caldart (2011), Rojo (2012) e Martins (2019), busca investigar quais seriam as relações entre um trabalho com a pedagogia dos multiletramentos, os aspectos culturais de valorização do homem do campo e os processos cognitivos dos alunos inseridos na realidade da escola do campo. Como resultados e relações, a pesquisa argumenta que a cultura pode ser o elo entre a cognição, os multiletramentos e a valorização das práticas sociais que acontecem no contexto camponês.
Da insurgência da mulher no discurso da canção
Authors: Lima Fernanda Fernandes Pimenta de Almeida , Faria Natália Costa Azevedo de
Published: December 2023

Neste trabalho, analisamos sentidos de resistência da mulher na canção Meu Bem (Alvarenga et al., 2020), à luz do postulado da Análise do Discurso francesa e de algumas concepções que norteiam os estudos do letramento. Com isso, refletimos sobre o caráter relacional do poder e os efeitos de sentidos que emergem nos enunciados dessa canção. Destes, ecoam vozes insurgentes a modelos pré-estabelecidos que impuseram à mulher e ao seu corpo condições de existência, geralmente conduzidas pelo querer alheio. Observamos, nesse contexto, como o gênero canção possibilita ao sujeito escolar uma formação crítica, como efeito de seu vínculo com a experiência multissemiótica da leitura enquanto prática de resistência aos ditames sobre a aparência e a existência da mulher.
Liberdade de expressão e o estado democrático
Authors: Gonçalves Lemos Bruno , Freire Dorow Clóris Maria
Published: December 2023

Objetiva-se analisar a liberdade de expressão enquanto um acontecimento discursivo e inerente à cidadania em uma sociedade democrática. Elencaram-se, como corpus específico de análise, alguns discursos relacionados à tática de ação coletiva black bloc. Com base nos pressupostos teóricos e nas metodológicos da Análise de Discurso (AD), mormente, sob o viés da teoria de Pêcheux (1997) e Orlandi (2013), busca-se analisar os seus efeitos de sentido e os ideológicos. Foram destacadas materialidades discursivas do livro Mascarados, nas quais se formam embates discursivos: de um lado os sujeitos black blocs; de outro os sujeitos policiais. Logo, há discursos com formações discursivas e ideológicas opostas atinentes ao mesmo objeto de pesquisa, sobretudo acerca de um dos efeitos de sentido emergidos na análise: a violência simbólica.
Um cotejo entre Base Nacional Comum Curricular (BNCC) e as Diretrizes Curriculares do Estado do Paraná
Authors: Vasconcelos Ellen Petrech
Published: December 2023

O presente artigo tem como objetivo estabelecer o cotejo entre dois documentos norteadores da educação, sendo eles a Base Nacional Comum Curricular (BNCC) e as Diretrizes Curriculares do Estado do Paraná. Em nossa análise, daremos enfoque à concepção de língua adotada, pois esse é um aspecto central para a compressão de seus posicionamentos com relação ao ensino de Língua Portuguesa. Para tanto, utilizaremos a metodologia do cotejo que nos permite ir muito além da mera comparação entre documentos. Contaremos também com o aporte teórico de Bonini e Costa-Hubes (2019), Rossi e Souza (2019), Pina e Gama (2020) e Souza (2010). Iremos retomar o processo de formatação dos documentos, apresentar a concepção de língua adotada por eles e, posteriormente, abordaremos as influências das teorias neoliberais na educação e na BNCC. A partir do cotejo entre os documentos normativos, constatou-se a que a BNCC sofre fortes influências das teorias neoliberais na sua elaboração, o que reflete na concepção de ensino de língua portuguesa adotada.