An inertial coupled marine power generator for small boats

This paper proposes a device to harvest energy from the vertical motion of small boats and yachts. The device comprises a sprung mass coupled to an electrical generator through a ball screw. The mathematical equations describing the dynamics of the system are derived. The equations are used to determine the optimum device parameters, namely its mass, spring constant, ball screw lead, within practical constraints. Simulation results are presented to determine the maximum power that can be generated and the optimum load resistance as a function of boat vibration frequency

Dispersion behavior of torsional guided waves in a small diameter steel gas pipe

Condition monitoring of gas pipes has been an important issue for gas companies. Failure to accurately identify condition of gas pipes result in numerous problems. Also, producing a condition monitoring system for buried pipelines is challenging. Small pipes (with diameters less than 50 mm) are considered here as most of the literature focuses on larger pipes. Guided wave theory will be introduced alongside a numerical simulation of the relevant dispersion curves of the system. This paper investigates the feasibility of using torsional guided waves for inspecting defects in buried pipes with small diameters. The pipes are assumed to be lossless and hence the effect of attenuation is ignored in the calculations. Upon finding the theoretical guided wave characteristics, experiments were conducted to see if the aim could be achieved in a realistic scenario. A steel pipe with a diameter of 34 mm and wall thickness of 5.5 mm is considered. High reverberation levels at high frequency propagations due to mode conversion are studied. Having only a limited number of transducers could be a reason for high reverberation at high frequencies

Active vibration control (AVC) of a satellite boom structure using optimally positioned stacked piezoelectric actuators

In this paper, results for active vibration control predicted from experimental measurements on a lightweight structure are compared with purely computational predictions. The structure studied is a 4.5m long satellite boom consisting of 10 identical bays with equilateral triangular cross sections. First, the results from a Fortran code that is based on a receptance analysis are validated against the experimental forced response of the boom structure. Exhaustive searches are then carried out to find the optimum positions for one and two actuators. Finally, a genetic algorithm is employed to find high-quality positions for three actuators on the structure that will achieve the greatest reductions in vibration transmission. Having found these actuator positions, experiments are then carried out to verify the quality of the theoretical predictions. It was found that the attenuation achievable in practice for one, two and three actuators were, respectively, 15.1, 26.1 and 33.5 dB

Active vibration control (AVC) of a satellite boom structure using optimally positioned stacked piezoelectric actuators

In this paper, results for active vibration control predicted from experimental measurements on a lightweight structure are compared with purely computational predictions. The structure studied is a 4.5m long satellite boom consisting of 10 identical bays with equilateral triangular cross sections. First, the results from a Fortran code that is based on a receptance analysis are validated against the experimental forced response of the boom structure. Exhaustive searches are then carried out to find the optimum positions for one and two actuators. Finally, a genetic algorithm is employed to find high-quality positions for three actuators on the structure that will achieve the greatest reductions in vibration transmission. Having found these actuator positions, experiments are then carried out to verify the quality of the theoretical predictions. It was found that the attenuation achievable in practice for one, two and three actuators were, respectively, 15.1, 26.1 and 33.5 dB

A novel Kalman filter based technique for calculating the time history of vertical displacement of a boat from measured acceleration

This is the final version of the article. Available from Science and Engineering Publishing Company via the link in this record.Accelerometers are used to measure velocity and displacement in many applications such as ship motion, monitoring of civil and mechanical structure, seismology and machine condition monitoring. However, using direct numerical integration to calculate velocity and displacement from the acceleration signal is known to suffer from low frequency noise amplification and wind-up. In this paper, a Kalman filter based method is proposed for calculating displacement from measured acceleration. Integration wind-up is eliminated by incorporating an additional state variable, namely the integral of the displacement whose "measured" value is assumed to be equal to the known average value of the displacement. In many applications, such as those in marine environment, this average value can be assumed to be constant, usually conveniently assigned to be zero if non-linear behaviour and permanent deformations are deemed negligible. The paper describes the technique and investigates its performance under different conditions of amplitude and frequency of vibrations and sampling rate and validates it by conducting two laboratory experiments. In the first experiment the displacement of a small shaker is calculated from a relatively high frequency (tens of Hz) acceleration signal sampled at 1 kHz with a resolution of 1 g. The calculated displacement of the shaker is found to agree well with that measured using a high resolution laser. In the second experiment, the proposed method is applied to the calculation of the vertical displacement of a boat from a low frequency (less than 1 Hz) acceleration signal sampled at 5 Hz and a resolution of 0.01g. An experimental set up designed to mimic typical motion of a boat is used to validate the results. Although the method explained in this paper is used to calculate the vertical displacement of a boat, it can be applied for calculating the displacement in a wide range of applications with reciprocating movement.The authors wish to thank Mr Mike Russell for his financial support and for collecting boat motion data. They also wish to thank Mr L. Auboin for his help with collecting boat motion data and conducting simulated boat motion lab experiments. Thanks are also due to Dr Jamil Renno for facilitating the high-frequency vibration experiments

Enhancement of MEMS-based ultrasonic transducers for sensing applications using machine learning

This thesis presents an in-depth exploration of the integration of ultrasonic signal transmission, ultrasonic signal processing, and advanced fault detection methodologies, highlighting the synergy among these technologies through three interrelated studies. The first study introduces a high-precision airborne ultrasonic rangefinder system based on piezoelectric micromachined ultrasonic transducers (PMUTs). Utilizing both transmitters (Tx) and receivers (Rx) fabricated with highly sensitive piezoelectric beams, the system operates on the time-of-flight (ToF) principle, where ultrasonic waves travel between the Tx and Rx to detect obstacles or calculate distances. Enhanced by deep learning models—specifically convolutional neural networks (CNNs) with k-fold cross-validation—the rangefinder achieves superior accuracy compared to traditional methods, ensuring robust performance in diverse environments. This makes it suitable for applications in robotics, augmented reality, and industrial safety systems. The second study focuses on the application of ultrasonic signal processing for industrial fault detection, employing only the receiver (Rx). Concentrating on pipelines and motor systems, this research utilizes the Rx to detect mechanical faults by capturing ultrasonic signals and applying advanced feature extraction techniques in both time and frequency domains. Key features—including skewness, kurtosis and crest factor—are extracted, and dimensionality reduction methods like principal component analysis (PCA) and linear discriminant analysis (LDA) are employed to streamline the data. Machine learning classifiers such as k-nearest neighbors (KNN), support vector machines (SVM) and decision trees (DT) are used in conjunction with ensemble learning techniques like stacking and boosting to enhance accuracy and reliability in fault detection. The system's ability to detect and classify faults in real time is further validated by deploying the models on microcontroller units (MCUs), underscoring its potential for real-world applications. The third study explores the use of ensemble machine learning models for real-time fault detection using ultrasonics. Emphasizing scalability and efficiency, this research demonstrates the use of ultrasonic signals for monitoring industrial systems such as pipelines and rotating machinery. The Rx plays a central role in capturing ultrasonic signals, which are then processed and analyzed by machine learning algorithms to detect faults like leaks, blockages, and bearing failures. The study compares several ensemble learning models—including gradient boosting (GB), voting classifiers, and AdaBoost—and evaluates their performance using k-fold cross-validation. Deployment of these models on resource-constrained devices like ARM Cortex-M4F MCUs demonstrates the feasibility of real-time fault monitoring on embedded systems. This approach not only addresses current industrial needs but also paves the way for future innovations in wireless sensing and smart monitoring systems. In conclusion, the research presented in these studies underscores the promising role of ultrasonics, enhanced by machine learning, in augmenting industrial system efficiency, safety, and functionality. By integrating ultrasonic sensors with advanced machine learning techniques, the developed systems provide robust, real-time fault detection and diagnostics, offering significant improvements over traditional monitoring methods. The successful implementation of these technologies addresses pressing industrial challenges—such as early fault detection in pipelines and machinery—and lays the groundwork for future innovations in wireless sensing, embedded systems, and real-time monitoring across various sectors. This work establishes a strong foundation for ongoing research into more efficient, scalable solutions for industrial automation, predictive maintenance, and safety monitoring

Integrating pictorial and text information in search

Objective: To determine whether people are faster at searching/selecting pictures or text. Background: Previous research shows that people are quicker when presented with images rather than text. People process pictorial cues quicker than they process text cues. Method: Participants were shown a target image with either pictures or text and asked to locate the target in a search screen that also consisted of pictures or text, using a PC and mouse. There were four conditions that randomly appeared throughout the experiment, (picture/picture, text/text, text/picture, and picture/text). Results: The picture/picture condition resulted in the fastest response times, followed by the text/text, text/picture, and . picture/text. Conclusion: The results were clear, participants were quicker locating pictures than they were in locating text. Application: When trying to get quick responses in search, present picture images.Includes bibliographical references (leaves 23-24)California State University, Northridge. Department of Psychology

Electrosynthesis of nanocomposite thin films at immiscible liquid|liquid interfaces

Contemporary research on conductive thin film materials has expanded beyond its applications in solar cells, semiconductor devices, and optical coatings to include the development of biocompatible electrode materials and organic thin film transistors. This study focuses on the use of immiscible micro liquid|liquid interfaces between water|oil (w|o) or water|ionic liquid (w|IL) to generate free-standing thin films that incorporate metal nanoparticles (NPs) electrogenerated in situ by reducing a metal salt in the aqueous phase and a hydrophobic electron donor dissolved in the organic/ionic liquid phase. Following an exploration of recent advancements in electropolymerization at an electrified interface, which encompassed the synthesis of polymeric base networks, metal nanoparticles, and nanocomposite film formation, as well as the electrochemical processes at the interface between immiscible electrolyte solutions, four electron donors were examined: ferrocene, IL-modified ferrocene, 2,2′:5′,2′′-terthiophene (TT), and a specialized dithiafulvenyl-substituted pyrene (bis(dithiafulvenyl)pyrene). The research first focused on TT polymerization and the reduction of AuCl₄σ¯ to Au NPs to generate a flexible electrocatalytic composite thin film. The results showed that high aqueous phase pH facilitated the polymerization reaction and the half-wave potential of the electron transfer wave shifted to lower potentials, indicating improved thermodynamics. Furthermore, the study found that the capacitive nature of the interface increased, and the resistance towards simple ion transfer increased with increasing [TT], pH, and potential cycling. Later the metal salt was replaced with copper sulfate to study the formation of Cu NP/poly-TT nanocomposite thin films at different interfacial sizes. The data revealed that the film formed quickly, but the interfacial reaction did not proceed without an applied potential. Preliminary electrocatalysis results showed that the nanocomposite-modified large glassy carbon electrode had a >2× increase in CO₂ reduction currents compared to an unmodified electrode. Finally, the electropolymerization of bis(dithiafulvenyl)pyrene with KAuCl₄(aq) was studied. The study found that miniaturization of the immiscible micro liquid|liquid interface facilitated external potential control and limited the reaction pathway to heterogeneous electron transfer across the interface. This method of nanocomposite film generation provides a low overpotential, controlled alternative to large-scale film generation, making it an attractive option for materials chemistry, electrocatalysis, and as soft electrodes for bioimplantation. The chapter dedicated to conclusions and future work provides a comprehensive analysis of the findings and identifies potential avenues for future research in this field

Product portfolio analysis towards operationalising Science-Based Targets

The urge to limit the environmental impacts of human activities within the safe operating space of planetary boundaries to save the Earth is scientifically and politically agreed upon. Based on the Paris agreement, Science-Based Targets (SBTs) are set as Environmental Impact (EI) targets for companies to help them operate within the planetary boundaries. This research aims to develop a dynamic decision support tool for decision making on strategic directions of product families that satisfy not only their profit targets but also their environmental impact targets (SBTs). The proposed methodology applies a suggested framework to assess the Future-oriented Environmental Impact of product families, including a technology prediction model (logistic model) to capture market changes and the consequences of market changes on the EIs of product families. The proposed methodology also includes a Total Profit model and optimisation model (genetic algorithm) to allocate SBTs to product families. Moreover, the application of two suggested matrices, including relative Future-oriented Environmental Impact – Total Profit matrix and the Environmental Impact Reduction Requirement ratio – Total Profit matrix, offers strategic directions to product families towards operationalising SBTs

Inhibitory of Newly Synthesized 3-BrPhOXTs on Corrosion of Stainless Steel in Acidic Medium

Newly synthesized 3-(3-bromophenyl)-2-imino-2,3-dihydrobenzo[d]oxazol-5-yl 4-methylbenzenesulfonate (3-BrPhOXTs) inhibitoRY effect on the corrosion of stainless steel L316 (SS) in sulfuric acid was investigated by means of potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). According to electrochemical results, excellent inhibiting properties for SS corrosion in sulfuric acid has been obtained. The adsorption of 3-BrPhOXTs onto the SS surface followed the Langmuir adsorption model with the free energy of adsorption DG0 ads of –8.94 kj mol–1.KEYWORDS: Organic inhibitor, adsorption, stainless steel, impedance