Search results for: industrial division

Authors: Piotr K. Szewczyk, Arkadiusz Gradys, Sungkyun Kim, Luana Persano, Mateusz M. Marzec, Oleksander Kryshtal, Andrzej Bernasik, Sohini Kar-Narayan, Pawel Sajkiewicz, Urszula Stachewicz

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Piezoelectric polymers have received great attention in smart textiles, wearables, and flexible electronics. Their potential applications range from devices that could operate without traditional power sources, through self-powering sensors, up to implantable biosensors. Semi-crystalline PVDF is often proposed as the main candidate for industrial-scale applications as it exhibits exceptional energy harvesting efficiency compared to other polymers combined with high mechanical strength and thermal stability. Plenty of approaches have been proposed for obtaining PVDF rich in the desired β-phase with electric polling, thermal annealing, and mechanical stretching being the most prevalent. Electrospinning is a highly tunable technique that provides a one-step process of obtaining highly piezoelectric PVDF fibers without the need for post-treatment. In this study, voltage polarity and relative humidity influence on electrospun PVDF, fibers were investigated with the main focus on piezoelectric β-phase contents and piezoelectric performance. Morphology and internal structure of fibers were investigated using scanning (SEM) and transmission electron microscopy techniques (TEM). Fourier Transform Infrared Spectroscopy (FITR), wide-angle X-ray scattering (WAXS) and differential scanning calorimetry (DSC) were used to characterize the phase composition of electrospun PVDF. Additionally, surface chemistry was verified with X-ray photoelectron spectroscopy (XPS). Piezoelectric performance of individual electrospun PVDF fibers was measured using piezoresponse force microscopy (PFM), and the power output from meshes was analyzed via custom-built equipment. To prepare the solution for electrospinning, PVDF pellets were dissolved in dimethylacetamide and acetone solution in a 1:1 ratio to achieve a 24% solution. Fibers were electrospun with a constant voltage of +/-15kV applied to the stainless steel nozzle with the inner diameter of 0.8mm. The flow rate was kept constant at 6mlh⁻¹. The electrospinning of PVDF was performed at T = 25°C and relative humidity of 30 and 60% for PVDF30+/- and PVDF60+/- samples respectively in the environmental chamber. The SEM and TEM analysis of fibers produced at a lower relative humidity of 30% (PVDF30+/-) showed a smooth surface in opposition to fibers obtained at 60% relative humidity (PVDF60+/-), which had wrinkled surface and additionally internal voids. XPS results confirmed lower fluorine content at the surface of PVDF- fibers obtained by electrospinning with negative voltage polarity comparing to the PVDF+ obtained with positive voltage polarity. Changes in surface composition measured with XPS were found to influence the piezoelectric performance of obtained fibers what was further confirmed by PFM as well as by custom-built fiber-based piezoelectric generator. For PVDF60+/- samples humidity led to an increase of β-phase contents in PVDF fibers as confirmed by FTIR, WAXS, and DSC measurements, which showed almost two times higher concentrations of β-phase. A combination of negative voltage polarity with high relative humidity led to fibers with the highest β-phase contents and the best piezoelectric performance of all investigated samples. This study outlines the possibility to produce electrospun PVDF fibers with tunable piezoelectric performance in a one-step electrospinning process by controlling relative humidity and voltage polarity conditions. Acknowledgment: This research was conducted within the funding from m the Sonata Bis 5 project granted by National Science Centre, No 2015/18/E/ST5/00230, and supported by the infrastructure at International Centre of Electron Microscopy for Materials Science (IC-EM) at AGH University of Science and Technology. The PFM measurements were supported by an STSM Grant from COST Action CA17107.

Keywords: crystallinity, electrospinning, PVDF, voltage polarity

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Authors: Dimitra C. Banti, Gesthimani Liona, Petros Samaras, Manasis Mitrakas

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Municipal and industrial wastewaters are often treated biologically, by the activated sludge process (ASP). The ASP not only requires large aeration and sedimentation tanks, but also generates large quantities of excess sludge. An alternative technology is the membrane bioreactor (MBR), which replaces two stages of the conventional ASP—clarification and settlement—with a single, integrated biotreatment and clarification step. The advantages offered by the MBR over conventional treatment include reduced footprint and sludge production through maintaining a high biomass concentration in the bioreactor. Notwithstanding these advantages, the widespread application of the MBR process is constrained by membrane fouling. Fouling leads to permeate flux decline, making more frequent membrane cleaning and replacement necessary and resulting to increased operating costs. In general, membrane fouling results from the interaction between the membrane material and the components in the activated sludge liquor. The latter includes substrate components, cells, cell debris and microbial metabolites, such as Extracellular Polymeric Substances (EPS) and Sludge Microbial Products (SMPs). The challenge for effective MBR operation is to minimize the rate of Transmembrane Pressure (TMP) increase. This can be achieved by several ways, one of which is the addition of specific additives, that enhance the coagulation and flocculation of compounds, which are responsible for fouling, hence reducing biofilm formation on the membrane surface and limiting the fouling rate. In this project the effectiveness of a non-commercial composite coagulant was studied as an agent for fouling control in a lab scale MBR system consisting in two aerated tanks. A flat sheet membrane module with 0.40 um pore size was submerged into the second tank. The system was fed by50 L/d of municipal wastewater collected from the effluent of the primary sedimentation basin. The TMP increase rate, which is directly related to fouling growth, was monitored by a PLC system. EPS, MLSS and MLVSS measurements were performed in samples of mixed liquor; in addition, influent and effluent samples were collected for the determination of physicochemical characteristics (COD, BOD5, NO3-N, NH4-N, Total N and PO4-P). The coagulant was added in concentrations 2, 5 and 10mg/L during a period of 2 weeks and the results were compared with the control system (without coagulant addition). EPS fractions were extracted by a three stages physical-thermal treatment allowing the identification of Soluble EPS (SEPS) or SMP, Loosely Bound EPS (LBEPS) and Tightly Bound EPS (TBEPS). Proteins and carbohydrates concentrations were measured in EPS fractions by the modified Lowry method and Dubois method, respectively. Addition of 2 mg/L coagulant concentration did not affect SEPS proteins in comparison with control process and their values varied between 32 to 38mg/g VSS. However a coagulant dosage of 5mg/L resulted in a slight increase of SEPS proteins at 35-40 mg/g VSS while 10mg/L coagulant further increased SEPS to 44-48mg/g VSS. Similar results were obtained for SEPS carbohydrates. Carbohydrates values without coagulant addition were similar to the corresponding values measured for 2mg/L coagulant; the addition of mg/L coagulant resulted to a slight increase of carbohydrates SEPS to 6-7mg/g VSS while a dose of 10 mg/L further increased carbohydrates content to 9-10mg/g VSS. Total LBEPS and TBEPS, consisted of proteins and carbohydrates of LBEPS and TBEPS respectively, presented similar variations by the addition of the coagulant. Total LBEPS at 2mg/L dose were almost equal to 17mg/g VSS, and their values increased to 22 and 29 mg/g VSS during the addition of 5 mg/L and 10 mg/L of coagulant respectively. Total TBEPS were almost 37 mg/g VSS at a coagulant dose of 2 mg/L and increased to 42 and 51 mg/g VSS at 5 mg/L and 10 mg/L doses, respectively. Therefore, it can be concluded that coagulant addition could potentially affect microorganisms activities, excreting EPS in greater amounts. Nevertheless, EPS increase, mainly SEPS increase, resulted to a higher membrane fouling rate, as justified by the corresponding TMP increase rate. However, the addition of the coagulant, although affected the EPS content in the reactor mixed liquor, did not change the filtration process: an effluent of high quality was produced, with COD values as low as 20-30 mg/L.

Keywords: extracellular polymeric substances, MBR, membrane fouling, EPS

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Authors: M. Moreno, M. Alique, D. Otero, C. Delgado, P. Lacharmoise, L. Gracia, L. Pires, A. Moya

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Marine environments are increasingly threatened by heavy metal contamination, including mercury (Hg), lead (Pb), and cadmium (Cd), posing significant risks to ecosystems and human health. Traditional monitoring techniques often fail to provide the spatial and temporal resolution needed for real-time detection of these contaminants, especially in remote or harsh environments. SEAWIZARD addresses these challenges by leveraging the flexibility, adaptability, and cost-effectiveness of printed electronics, with the integration of microfluidics to develop a compact, portable, and reusable sensor platform designed specifically for real-time monitoring of heavy metal ions in seawater. The SEAWIZARD sensor is a multiparametric Lab-on-Chip (LoC) device, a miniaturized system that integrates several laboratory functions into a single chip, drastically reducing sample volumes and improving adaptability. This platform integrates three printed graphene electrodes for the simultaneous detection of Hg, Cd and Pb via square wave voltammetry. These electrodes share the reference and the counter electrodes to improve space efficiency. Additionally, it integrates printed pH and temperature sensors to correct environmental interferences that may impact the accuracy of metal detection. The pH sensor is based on a carbon electrode with iridium oxide electrodeposited while the temperature sensor is graphene based. A protective dielectric layer is printed on top of the sensor to safeguard it in harsh marine conditions. The use of flexible polyethylene terephthalate (PET) as the substrate enables the sensor to conform to various surfaces and operate in challenging environments. One of the key innovations of SEAWIZARD is its integrated microfluidic layer, fabricated from cyclic olefin copolymer (COC). This microfluidic component allows a controlled flow of seawater over the sensing area, allowing for significant improved detection limits compared to direct water sampling. The system’s dual-channel design separates the detection of heavy metals from the measurement of pH and temperature, ensuring that each parameter is measured under optimal conditions. In addition, the temperature sensor is finely tuned with a serpentine-shaped microfluidic channel to ensure precise thermal measurements. SEAWIZARD also incorporates custom electronics that allow for wireless data transmission via Bluetooth, facilitating rapid data collection and user interface integration. Embedded artificial intelligence further enhances the platform by providing an automated alarm system, capable of detecting predefined metal concentration thresholds and issuing warnings when limits are exceeded. This predictive feature enables early warnings of potential environmental disasters, such as industrial spills or toxic levels of heavy metal pollutants, making SEAWIZARD not just a detection tool, but a comprehensive monitoring and early intervention system. In conclusion, SEAWIZARD represents a significant advancement in printed electronics applied to environmental sensing. By combining flexible, low-cost materials with advanced microfluidics, custom electronics, and AI-driven intelligence, SEAWIZARD offers a highly adaptable and scalable solution for real-time, high-resolution monitoring of heavy metals in marine environments. Its compact and portable design makes it an accessible, user-friendly tool with the potential to transform water quality monitoring practices and provide critical data to protect marine ecosystems from contamination-related risks.

Keywords: lab-on-chip, printed electronics, real-time monitoring, microfluidics, heavy metal contamination

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Authors: Riccardo Fratini, Riccardo Santini, Jacopo Serafini, Massimo Gennaretti, Stefano Panzieri

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This paper presents a nonlinear differential model, for a three-bladed horizontal axis wind turbine (HAWT) suited for control applications. It is based on a 8-dofs, lumped parameters structural dynamics coupled with a quasi-steady sectional aerodynamics. In particular, using the Euler-Lagrange Equation (Energetic Variation approach), the authors derive, and successively validate, such model. For the derivation of the aerodynamic model, the Greenbergs theory, an extension of the theory proposed by Theodorsen to the case of thin airfoils undergoing pulsating flows, is used. Specifically, in this work, the authors restricted that theory under the hypothesis of low perturbation reduced frequency k, which causes the lift deficiency function C(k) to be real and equal to 1. Furthermore, the expressions of the aerodynamic loads are obtained using the quasi-steady strip theory (Hodges and Ormiston), as a function of the chordwise and normal components of relative velocity between flow and airfoil Ut, Up, their derivatives, and section angular velocity ε˙. For the validation of the proposed model, the authors carried out open and closed-loop simulations of a 5 MW HAWT, characterized by radius R =61.5 m and by mean chord c = 3 m, with a nominal angular velocity Ωn = 1.266rad/sec. The first analysis performed is the steady state solution, where a uniform wind Vw = 11.4 m/s is considered and a collective pitch angle θ = 0.88◦ is imposed. During this step, the authors noticed that the proposed model is intrinsically periodic due to the effect of the wind and of the gravitational force. In order to reject this periodic trend in the model dynamics, the authors propose a collective repetitive control algorithm coupled with a PD controller. In particular, when the reference command to be tracked and/or the disturbance to be rejected are periodic signals with a fixed period, the repetitive control strategies can be applied due to their high precision, simple implementation and little performance dependency on system parameters. The functional scheme of a repetitive controller is quite simple and, given a periodic reference command, is composed of a control block Crc(s) usually added to an existing feedback control system. The control block contains and a free time-delay system eτs in a positive feedback loop, and a low-pass filter q(s). It should be noticed that, while the time delay term reduces the stability margin, on the other hand the low pass filter is added to ensure stability. It is worth noting that, in this work, the authors propose a phase shifting for the controller and the delay system has been modified as e^(−(T−γk)), where T is the period of the signal and γk is a phase shifting of k samples of the same periodic signal. It should be noticed that, the phase shifting technique is particularly useful in non-minimum phase systems, such as flexible structures. In fact, using the phase shifting, the iterative algorithm could reach the convergence also at high frequencies. Notice that, in our case study, the shifting of k samples depends both on the rotor angular velocity Ω and on the rotor azimuth angle Ψ: we refer to this controller as a spatial repetitive controller. The collective repetitive controller has also been coupled with a C(s) = PD(s), in order to dampen oscillations of the blades. The performance of the spatial repetitive controller is compared with an industrial PI controller. In particular, starting from wind speed velocity Vw = 11.4 m/s the controller is asked to maintain the nominal angular velocity Ωn = 1.266rad/s after an instantaneous increase of wind speed (Vw = 15 m/s). Then, a purely periodic external disturbance is introduced in order to stress the capabilities of the repetitive controller. The results of the simulations show that, contrary to a simple PI controller, the spatial repetitive-PD controller has the capability to reject both external disturbances and periodic trend in the model dynamics. Finally, the nominal value of the angular velocity is reached, in accordance with results obtained with commercial software for a turbine of the same type.

Keywords: wind turbines, aeroelasticity, repetitive control, periodic systems

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

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Authors: Andrew Gennett

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Designing for fungal development means embracing the symbiotic relationship between the living system and built environment. The potential of mycelium post-colonization is explored for the fabrication of advanced pure mycelium products, going beyond the conventional methods of aggregating materials. Fruiting induction imparts desired material properties such as enhanced environmental resistance. Production approach allows for simultaneous generation of multiple products while scaling up raw materials supply suitable for architectural applications. The following work explores the integration of fungal environmental perception with computational design of built fruiting chambers. Polyporales, are classified by their porous reproductive tissues supported by a wood-like context tissue covered by a hard waterproofing coat of hydrobpobins. Persisting for years in the wild, these species represent material properties that would be highly desired in moving beyond flat sheets of arial mycelium as with leather or bacon applications. Understanding the inherent environmental perception of fungi has become the basis for working with and inducing desired hyphal differentiation. Working within the native signal interpretation of a mycelium mass during fruiting induction provides the means to apply textures and color to the final finishing coat. A delicate interplay between meeting human-centered goals while designing around natural processes of living systems represents a blend of art and science. Architecturally, physical simulations inform model design for simple modular fruiting chambers that change as fungal growth progresses, while biological life science principles describe the internal computations occurring within the fungal hyphae. First, a form filling phase of growth is controlled by growth chamber environment. Second, an initiation phase of growth forms the final exterior finishing texture. Hyphal densification induces cellular cascades, in turn producing the classical hardened cuticle, UV protective molecule production, as well, as waterproofing finish. Upon fruiting process completion, the fully colonized spent substrate holds considerable value and is not considered waste. Instead, it becomes a valuable resource in the next cycle of production scale-up. However, the acquisition of new substrate resources poses a critical question, particularly as these resources become increasingly scarce. Pursuing a regenerative design paradigm from the environmental perspective, the usage of “agricultural waste” for architectural materials would prove a continuation of the destructive practices established by the previous industrial regime. For these residues from fields and forests serve a vital ecological role protecting the soil surface in combating erosion while reducing evaporation and fostering a biologically diverse food web. Instead, urban centers have been identified as abundant sources of new substrate material. Diverting the waste from secondary locations such as food processing centers, papers mills, and recycling facilities not only reduces landfill burden but leverages the latent value of these waste steams as precious resources for mycelium cultivation. In conclusion, working with living systems through innovative built environments for fungal development, provides the needed gain of function and resilience of mycelium products. The next generation of sustainable fungal products will go beyond the current binding process, with a focus upon reducing landfill burden from urban centers. In final considerations, biophilic material builds to an ecologically regenerative recycling production cycle.

Keywords: regenerative agriculture, mycelium fabrication, growth chamber design, sustainable resource acquisition, fungal morphogenesis, soil fertility

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