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Highlights Additive manufacturing encounters significant barriers to its broader application in large‐scale production. This research seeks to mitigate critical limitations, including a trade‐off between impregnation speed and quality in filament preparation and inconsistent fiber distribution in continuous carbon filaments (CCFs), mainly attributed to the rounding process of unidirectional tapes and insufficient interlayer adhesion. A novel lab‐scale impregnation line was engineered to address these challenges, facilitating the production of CCFs using three distinct types of carbon fiber in conjunction with recycled glycol‐modified poly(ethylene terephthalate) (rPETG) resin. This new lab‐scale process produces uniform fiber distribution within PETG matrix and prevents S‐shaped distortions typically observed in conventionally rounded tapes. The type of carbon fiber sizing influences the impregnation process and tensile strength of the CCFs. Specifically, CCFs with flexible sizing demonstrated a 15% reduction in tensile strength due to fuzz formation during impregnation. These CCFs were subsequently employed in 3D printing applications, with the fabricated composite components subjected to interlaminar shear strength (ILSS) testing. The study concludes that recycled PETG is a viable additive manufacturing material when combined with appropriately sized carbon fibers. Additionally, it highlights the advantages of omitting the rounding stage, which enhances the quality of CCF and optimizes production efficiency. A lab‐scale direct melt impregnation system was designed in this study. The impact of different sizing types on carbon fibers was investigated. 3D‐printed continuous fiber filaments were prepared. New lab‐scale process produces uniform fiber distribution within PETG matrix. S‐shaped distortions observed in conventionally rounded tapes were prevented. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sizing is the surface treatment of glass fibres (GFs) to protect them from wear, handle with ease and to create a good interface with the polymer matrix. This paper reports on the discernible procedure for the synthesis of epoxy-compatible amino silane sizing formulation for E-GF and its efficacy based on inter-laminar shear strength (ILSS) and flexural strength of in-house sized GF (SGF) woven roven mat (WRM) reinforced epoxy composites and compared to commercially available sized WRM [0°/90°]. The formulations of sizing were prepared by varying the proportions of aminopropyltriethoxy silane (APS, coupling agent) and polydimethylsiloxane (PDMS, anti-foam agent), for a fixed proportion of film former, surfactant and lubricant. Commercially available sized GF WRM were heat cleaned prior to sizing with prepared formulations. Interestingly, sizing with formulation of 0.65 wt% APS and 0.35 wt% of PDMS, coded as S6, showed homogeneous coating morphology and the loss on ignition (LOI) is comparable to commercially available SGF. Also, Fourier transform-infrared spectroscopy of SGF6 indicated the formation of silanol interphase by the presence of bands corresponding to Si–O–Si and Si–OH functional groups. The contact angle with epoxy hardener solvent by sessile drop method demonstrated good wetting favourable for better interphase with epoxy matrix. Thermogravimetric analysis indicated that sizing pick up and thermal stability were best for S6 formulation SGF. The mechanical testing shows that S6-sized WRM composite (SWC) yielded the best ILSS and flexural strength due to the effect of better wetting and good interfacial adhesion between SGF and matrix as revealed from fractography. The discernible recipe formulation and the better mechanical properties exhibited by SWC-reinforced SGF WRM sized with S6 comparable to that of commercial GF WRM epoxy composite indicate plausible industrial applications. [ABSTRACT FROM AUTHOR]

Copyright of China Textile Leader is the property of China Textile Information Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this article, dust explosion phenomena and the status of research conducted on silos are reviewed. Dust explosions cause loss of life and property in many industrial facilities. There are many recorded dust explosion cases in our country as well as in the world. For example, in our country, in 2023, a dust explosion occurred in the TMO Kocaeli General Directorate (Derince Port Silo), in which 2 people died and great material damage occurred, as reflected in the national press. When we look at the various dust explosion cases that have occurred in the world, it is understood that they mostly occur in silos used for storage in the agricultural and food sectors. Licensed warehouses have been established in many regions of our country in order to store basic and processed agricultural products that can be standardized with the Agricultural Products Licensed Warehousing Law No. 5300, which came into force after being published in the Official Gazette on 17/02/2005, in safe and healthy conditions in warehouses belonging to licensed warehouse enterprise and continues to be established. It is important to understand the many factors affecting dust explosion, such as dust dispersion, properties, discharge, etc., and to design silos according to these factors. These effects are tried to be determined and understood through experimental or CFD simulations. [ABSTRACT FROM AUTHOR]

Energy hubs （EHs） can effectively facilitate the consumption of renewable energy with high uncertainty. Still， the existing EH planning methods have not fully considered the correlation between siting and sizing. Hence， this study introduces an alternate optimization method considering the supply-demand balance. Firstly， utilizing graph theory and weighted similarity， the study defines the energy moment （EM）， a concept that represents the energy transmission cost， and proposes an optimal partitioning criterion for energy internet system with minimum total EM as the goal. Subsequently， the supply-demand balance index within each EH is calculated based on the time-series energy interaction information of the energy supply and demand entities. The paper then proposes a sizing strategy for multi-energy coupling units within EH， aiming to maximize the average supply-demand balance of the entire energy internet system. On this basis， the paper constructs an alternate optimization model for EH siting and sizing based on K-means clustering， and achieves an optimal solution through iteration of EHs. Finally， case studies are presented， and their results indicate that the proposed method can significantly improve the accuracy and economy of EH planning.

One of the main objectives of weaving production is the production of high quality fabrics and the search for ways to increase the productivity of weaving machines in order to improve the economic performance and competitiveness of the enterprise. In the production conditions of RUPTE "Orsha Linenmill" weaving machines Picanol OptiMax 190 are installed for the production of a range of household fabrics from low linear density yarn, most of which are exported. To ensure the quality of pure linen fine fabrics and the production of fine yarn, long flax fibre No. 11–14 and above is required. However, due to a number of reasons, the quality and quantity of incoming domestic raw materials cannot guarantee stable technological efficiency of production preparation and weaving processes, which is provided by the uniformity of flax and flax-containing yarn and its tensile properties. The aim of the research is to reduce warp breakage in weaving by determining rational production parameters on the loom and the choice of the sizing agent in order to increase the productivity of the loom in the production of linen fabrics with low surface density. In the article the properties of wet spinning yarn of 30 tex linear density made of long linen fibre are studied, the features of Karl Mayer SMR-SP-10-1800/800 SMR-SP-10-1800/800 sizing machine and Picanol OptiMax 190 rapier weaving machine are studied, the selection of modern sizing agent was made in order to increase machine productivity and reduce warp breakage during weaving of the most elite and marketable article – linen fabric with surface density of 120 g/m2. The changes in the technology made it possible to reduce the equipment downtime by reducing the number of warp breaks from 0.95 to 0.76 breaks per 1 running meter of fabric, to increase the coefficient of utilisation and to increase the annual volume of fabrics produced.

Nowadays, the installation of renewable energy sources (RESs) is increasing rapidly in residential areas and is gaining growing interest. This is mainly due to the continuous increase in energy prices and the decrease of RESs installation costs for residential consumers. Among all these sources of green energy, solar and wind energy are the most dominants. The production of these two sources is strongly correlated to meteorological variables (e.g., solar radiation, wind) which are characterized by an intermittent nature. Therefore, the integration of these sources increases the concern of power quality in the electrical system. In order to mitigate this problem, battery energy storage systems (BESSs) were adopted as one of the viable solutions. Their fast response capability and geographical independence can improve energy efficiency and reliability in the power system. In addition to all these benefits, a BESS can further reduce consumer’s electricity bill by storing excess RESs’ generation and allowing price arbitrage. The high prices of BESSs and their high maintenance costs have manifested the installation of shared BESSs in residential communities. This type of installation is more financially advantageous to the consumers than the individual one by the fact that they share all the costs between them. However, for both types of installations, a proper planning must be done in order to determine the optimal characteristics of the BESS that will guarantee an optimal operation. This involves determining the optimal size, placement and operation of the BESS. Numerous methods have been proposed in literature to find the optimal planning and operation of individual and shared BESSs. This paper presents a comprehensive review in which recent planning and management approaches are analyzed. All studies included in this review are detailed and classified according to several criteria, such as the objective functions considered, the techniques used, and the limitations.

Highlights The goal of this project was to recycle the waste forming in the production of a flexible, multilayer food packaging film. The film consists of five layers, two polyamides containing three different polymers, a polyethylene and two adhesive layers of maleated polyethylene. The type of the components and the exact composition are not disclosed because they represent proprietary information. The key to recycling is the selection of an appropriate strategy and target product. In this case, glass fiber reinforced PA composites were produced with an acceptable property profile. The properties of the recycled product are comparable to those of commercial composites available on the market. The crucial question was the selection of the glass fiber grade with the appropriate sizing. The selection was further complicated by the possible interaction of the functionalized polymer with the sizing of the fiber. The implementation of the solution is feasible technologically, the properties of the product are comparable to those available on the market, and its price is very advantageous. An engineering material can be produced from flexible multilayer packaging waste. The properties of the recycled product are comparable with those on the market. The selection of the glass fiber is crucial for mechanical properties. The solution is feasible technologically and the final price is competitive. [ABSTRACT FROM AUTHOR]

The rapid growth of EVs relies on the development of supporting infrastructure, e.g., charging stations (CSs). The sizing problem of a CS typically involves minimizing the investment costs. Therefore, a flexible and precise sizing strategy is crucial. However, the existing methods suffer from the following issues: (1) they do not consider charging station deployments based on the charging stack; (2) existing sizing strategies based on smart charging technology consider a single scenario and fail to meet the demand for flexible operation under multiple scenarios in real-life situations. This paper proposes a novel CS sizing framework specific for charging stacks to overcome these challenges. Specifically, it first addresses the charging-stack-based CS sizing problem, and then it proposes the corresponding multiscenario constraints, i.e., exclusive and shared, for capacity-setting optimization. In addition, a novel quality of service (QoS) formulation is also proposed to better relate the user QoS levels to the CS sizing problem. Finally, it also explores the relationship between the investment costs and the total power of the needed charging stack under three business models. Extensive experiments show that the proposed framework can offer valuable guidance to CS operators in competitive environments. [ABSTRACT FROM AUTHOR]

This research aims to explore how functionally active structures affect the physical, mechanical, thermal, and fire-resistant properties of elastomeric compositions using ethylene–propylene–diene rubber as a base. The inclusion of aluminosilicate microspheres, microfibers, and a phosphorus–boron–nitrogen–organic modifier in these structures creates a synergistic effect, enhancing the material's heat-insulating properties by strengthening coke and carbonization processes. This results in a 12–19% increase in heating time for unheated sample surfaces and a 6–17% increase in residual coke compared to existing analogs. Microspheres help counteract the negative impact of microfibers on composition density and thermal conductivity, while the phosphorus–boron–containing modifier allows for controlling the formation of the coke layer. [ABSTRACT FROM AUTHOR]

Accurately sizing vehicle components is an impactful step in the aircraft design process. However, existing methods of sizing brushless DC (BLDC) motors for small unmanned aerial systems (SUAS) ignore how cooling affects motor size. Moreover, the literature methods do not predict a notional motor's electrical constants, namely winding resistance, torque constant, and figure of merit. We developed a sizing algorithm that predicts the optimal mass and electrical constants using a combination of sizing, efficiency, and thermal models. The algorithm works for radial-flux BLDC motors with masses up to 800 g. An experimental teardown of seven motors informed the algorithm's sizing models. The teardown motors varied in mass (24–600 g) and geometry (stator aspect ratio of 1.4–9.0). Validated against an independent catalog of 30 motors, the sizing models predicted mass and resistance within 10% and 20% of catalog specifications, respectively. Validated against experimental data, the full algorithm predicted mass, efficiency, and temperature within 20%, 5%, and 10% accuracy, respectively. The algorithm also captured how lowering mass would increase losses and temperature, which the literature models ignore. The algorithm can help users develop more viable concepts that save costs in the long run. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study was to evaluate the suitability of current sizing systems adopted by brands, for an athletic female population and try to identify areas of improvement in current sizing and grading methods used. This information can be used to engineer accurately fitting lower-body sports compression leggings for the target demographic. Size and shape data of sixty-three athletic females was collected using 3D body scanning. The data was compared to size charts of three commercially available sports compression leggings manufactured by different brands as well as Alvanon's UK sizing and grading standards. Results show that athletic females are not catered for by current products. 28 women (44.44%) fell between sizes for at least one measurement across the three brands. Participant's measurements indicate differing body shapes to the standard 'hourglass' shape presented by the Alvanon UK sizing standards, used by companies as a basis for their sizing systems. [ABSTRACT FROM AUTHOR]

The use of natural fibers as an alternative to synthetic fibers for reinforcing composites is increasing. However, the poor interfacial adhesion between natural fibers and polymer matrices limits their applications. Several approaches have been considered to improve fiber-matrix adhesion via chemical and/or physical treatment. However, the effectiveness of these treatments varies based on the type of fiber, its source, and its composition. Thus, it is imperative to understand the effectiveness of treatment conditions. In this study, we investigated the influence of alkali treatment and fiber sizing on the chemical, thermal, morphological, and mechanical properties of coir fibers and the interface between coir fiber and polypropylene matrix. It was found that using a 5 wt% sodium hydroxide solution for 6 h at room temperature was the optimal treatment condition that led to an improvement in tensile strength by 58%, tensile modulus by 71%, and elongation at break by 37% compared to untreated fibers, and an increment in interfacial shear strength (IFSS) between coir fibers and polypropylene matrix by 32%. The alkali treatment removed the fiber surface impurities, made the fiber surface rough, and enhanced the fiber crystallinity. Sizing of the alkali-treated fiber led to an improvement in IFSS by 87% with no modification of the fiber's mechanical properties. [ABSTRACT FROM AUTHOR]

When it comes to computing the values of variables defining the preliminary sizing of an airship, a few standardized approaches are available in the existing literature. However, when including a disruptive technology in the design is required, sizing procedures need to be amended, so as to be able to deal with the features of any additional novel item. This is the case of atmospheric ionic thrusters, a promising propulsive technology based on electric power, where thrusters feature no moving parts and are relatively cheap to manufacture. The present contribution proposes modifications to an existing airship design technique, originally conceived accounting for standard electro-mechanical thrusters, so as to cope with the specific features of new atmospheric ionic thrusters. After introducing this design procedure in detail, its potential is tested by showing results from feasibility studies on an example airship intended for a high-altitude mission. Concurrently, the so-obtained results allow the demonstration of the sizing features corresponding to the adoption of atmospheric ionic thrusters at the current level of technology, comparing them to what is obtained for the same mission when employing a standard electro-mechanical propulsion system. [ABSTRACT FROM AUTHOR]

The count, location, and size of shrimp larvae are important observations for their intensive breeding, which could evaluate the culture density, growth, and yield. Recent works on the counting of dense aquatic objects in an image are mainly accomplished by the density map regression based on convolutional neural network (CNN). These regression methods only give the estimated density map and the corresponding count, but cannot locate and size the objects accurately. To realize the noninvasive counting, locating, and sizing during aquatic breeding, we propose a novel detection architecture in computer vision for the larvae of Cherax quadricarinatus. In particular, a new shrimp larvae counting network (SLCNet) using the density map regression is designed to output the estimated density map of the shrimp larvae image and predict the corresponding number of the shrimp larvae. The local peak filtering (LPF) is applied to the estimated density map to locate the coordinates of every shrimp larva. We then use the K-nearest neighbor (KNN) and the bounding box search to find the fitting bounding boxes of the shrimp larvae in sparse regions and calculate the body length of the shrimp larvae in the fitting bounding boxes with the aid of the least squares regression method. Compared with typical CNN-based counting models, the mean absolute error and root mean square error of the proposed SLCNet are 4.13 and 5.75, respectively, and the counting accuracy is up to 98.57%. Then, we perform the detection of the location and size of the shrimp larvae using the density map estimated by the SLCNet. The locating and sizing accuracy can reach 90.6% (i.e., F1 value) and 90.28%, respectively. It proves that this detection architecture could be used as technical support for subsequent studies on larva growth and behavior recognition. [ABSTRACT FROM AUTHOR]

Extending the public electricity grid to rural or peri-urban areas is sometimes very costly and unprofitable due to their remoteness, low population density and sometimes difficult accessibility. In view of this, and in the concern of a sustainable development, the autonomous PV and/or wind power systems is increasingly used. However, these fluctuating source systems remain unreliable due especially to their intermittent nature, what justifies the integration of battery storage systems to them. They are also still expensive, particularly in the African context, limiting their access to the greatest number of the population. In addition to these problems of cost and reliability, the issue of optimal sizing of such systems is essential. In this paper, energy storage technologies, performance criteria, basic energy production and storage models, configuration types, sizing and management techniques discussed in the literature for the study of stand-alone solar and/or wind power systems in isolated sites are reviewed. The findings of the present study reveals that electrochemical battery is the main technology used for energy storage in stand-alone PV-wind systems due in particular to their maturity compared to the other storage technologies. However, it also shows that while batteries are the most widely used energy storage technology for solar and wind power systems, they are still expensive. The paper also revealed that traditional methods of optimal sizing and management of autonomous solar and wind power generation systems are being used less and less, in favor of artificial intelligence methods, due mainly to their limited flexibility and inability to solve complex problems.

The sizes and shapes of nanoparticles play a critical role in their chemical and material properties. Common sizing methods based on light scattering or mobility lack individual particle specificity, and microscopy-based methods often require cumbersome sample preparation and image analysis. A promising alternative method for the rapid and accurate characterization of nanoparticle size is charge detection mass spectrometry (CDMS), an emerging technique that measures the masses of individual ions. A recently constructed CDMS instrument designed specifically for high acquisition speed, efficiency, and accuracy is described. This instrument does not rely on an ion energy filter or estimates of ion energy that have been previously required for mass determination, but instead uses direct, in situ measurements. A standardized sample of ∼100 nm diameter polystyrene nanoparticles and ∼50 nm polystyrene nanoparticles with amine-functionalized surfaces are characterized using CDMS and transmission electron microscopy (TEM). Individual nanoparticle masses measured by CDMS are transformed to diameters, and these size distributions are in close agreement with distributions measured by TEM. CDMS analysis also reveals dimerization of ∼100 nm nanoparticles in solution that cannot be determined by TEM due to the tendency of nanoparticles to agglomerate when dried onto a surface. Comparing the acquisition and analysis times of CDMS and TEM shows particle sizing rates up to ∼80× faster are possible using CDMS, even when samples ∼50× more dilute were used. The combination of both high-accuracy individual nanoparticle measurements and fast acquisition rates by CDMS represents an important advance in nanoparticle analysis capabilities.

Vance Thompson,1,2 Arthur B Cummings,3 Xiaoying Wang4– 6 1Vance Thompson Vision, Sioux Falls, SD, USA; 2Department of Ophthalmology, University of South Dakota Sanford School of Medicine, Vermillion, SD, USA; 3Wellington Eye Clinic, Dublin, Ireland; 4Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, People’s Republic of China; 5NHC Key Laboratory of Myopia, Fudan University, Shanghai, People’s Republic of China; 6Shanghai Research Center of Ophthalmology and Optometry, Eye & ENT Hospital, Fudan University, Shanghai, People’s Republic of ChinaCorrespondence: Vance Thompson, Vance Thompson Vision, 3101 W. 57 th St, Sioux Falls, SD, SD 57108, USA, Tel +1 480-684-4851, Email vance.thompson@vancethompsonvision.comAbstract: More than 2 million implantable collamer lenses (ICLs) have been implanted worldwide. With a central port to improve aqueous flow through the ICL, the latest iteration of this phakic intraocular lens (pIOL) has been shown to have stable outcomes with very low rates of adverse events. However, correct planning and ICL size selection continue to be important to achieve an optimal vault. Shallow or excessive vaults are not complications in and of themselves but may increase the risk of complications. Historically, surgeons have relied on measurements of anterior chamber depth (ACD) and manual, caliper-measured white-to-white (WTW) distance to select the ICL size. New diagnostic and imaging technologies such as optical coherence tomography (OCT) and ultrasound biomicroscopy (UBM) provide additional opportunities for visualization and measurement of the intraocular dimensions involved in phakic intraocular lens implantation, including sulcus-to-sulcus (STS) and angle-to-angle (ATA) diameters. This paper reviews various approaches to ICL planning and sizing that have been published in the peer-reviewed literature, all of which produce acceptable results for predicting vault and size selection. Surgeons may also want to identify a methodology for patient evaluation and ICL size selection that best aligns with their personal preferences, diagnostic technology, and familiarity with analytical optimization tools.Plain Language Summary: Phakic intraocular lenses (pIOLs) are one method for correcting nearsightedness, with or without astigmatism. This category of refractive surgery has been growing rapidly in the US and around the world. Implantation of the implantable collamer lens (ICL), one type of pIOL, is safe and effective, with stable outcomes and low adverse event rates. When complications do occur, they are typically associated with an inappropriate vault, or distance between the implant and the natural lens. Preoperative planning and accurate ICL sizing are required to achieve an optimal vault and varies, depending on the diagnostic technology available to the surgeon. This paper reviews the current approaches to ICL planning and sizing in order to provide guidance to surgeons implanting this pIOL.Keywords: phakic IOL, vault, sizing, white-to-white, sulcus-to-sulcus, angle-to-angle

Integrating wind power plants into the electricity grid poses challenges due to the intermittent nature of wind energy generation. Energy storage systems (ESSs) have shown promise in mitigating the intermittent variability associated with wind power. This paper presents a distributionally robust optimization (DRO) model for sizing energy storage systems to dispatch wind power plants. The variable wind power is formulated as a moment-based ambiguity set. Dispatchability is described by the expected value of the insufficient power of wind power relative to the dispatch command, which is a sum of nonlinear functions and is taken as the optimal index. A deterministic semi-definite positive model is derived to solve the problem effectively. Numerical studies are conducted to demonstrate the effectiveness and advantages of the proposed method. [ABSTRACT FROM AUTHOR]

The growing deployment of distributed resources significantly affects the distribution grid performance in most countries. The optimal sizing and placement of these resources have become increasingly crucial to mitigating grid issues and reducing costs. Particle Swarm Optimization (PSO) is widely used to address such problems but faces computational inefficiency due to its numerical convergence behavior. This limits its effectiveness, especially for power system problems, because the numerical distance between two nodes in power systems might be different from the actual electrical distance. In this paper, a scalable bilevel optimization problem with two novel algorithms enhances PSO's computational efficiency. While the resistivity-driven algorithm strategically targets low-resistivity regions and guides PSO toward areas with lower losses, the connectivity-driven algorithm aligns solution spaces with the grid's physical topology. It prioritizes actual physical neighbors during the search to prevent local optima traps. The tests of the algorithms on the IEEE 33-bus and the 69-bus and Norwegian networks show significant reductions in power losses (up to 74% for PV, wind, and storage) and improved voltage stability (a 21% reduction in mean voltage deviation index) with respect to the results of classical PSO. The proposed network-oriented PSO outperforms classical PSO by achieving a 2.84% reduction in the average fitness value for the IEEE 69-bus case with PV, wind, and storage deployment. The Norwegian case study affirms the effectiveness of the proposed approach in real-world applications through significant improvements in loss reduction and voltage stability. [ABSTRACT FROM AUTHOR]

Continuous in-field robotic and automated systems are challenged by the need for a continuous supply of power. This off-grid power supply can be diesel, gasoline, propane, or alternative energy sources like solar or wind. This study investigates the required solar panel arrays and energy storage capacities for an off-grid solar-battery power supply system. This study used 22 years of historical weather data from Lexington, Kentucky, and processed it with the National Renewable Energy Laboratory's System Advisor Model to model hourly energy output from solar panel arrays of 2 kW, 3 kW, 4 kW, 5 kW, 10 kW, 15 kW, and 20 kW. This was combined with an energy storage model (simulated battery capacities of 5 kWh, 10 kWh, 15 kWh, 20 kWh, 30 kWh, 40 kWh, 50 kWh, and 60 kWh) and an energy use model (simulated daily energy demands of 3.6 kWh, 6 kWh, 12 kWh, 18 kWh, and 24 kWh) to determine which systems could operate over the entire 22 years without reaching critical minimum levels. For a 3.6 kWh daily energy demand, 32 combinations of solar panel arrays and battery capacities remained above critical levels, while this was only 12 combinations for a 6 kWh daily energy demand and no combination could support larger energy demands. An example a feasible system to support a 6 kWh energy demand is one that uses a 15 kW panel array (42 standard panels with an approximate system hardware cost of $22,650) and 30 kWh of energy storage capacity (which with lead acid batteries would cost $11,661 and require a volume of 300 L). There is a tradeoff between solar panel array size and battery capacity so other feasible systems can be realized by increasing one to make up for reductions in the other variable. Additionally, limiting system operation to March through October can reduce the size of the required panel array (to between 33% to 67% of the original size) or energy storage capacity (to between 40% to 67% of the original capacity) for a given daily energy load. The size of the solar battery system could be further decreased by adding an emergency generator that uses no more than 50 kg of propane annually. Battery capacities could be reduced by 17% to 38% compared to the original system, and the solar panel arrays could be reduced by 13% to 15% compared to the original. Specific reduction amounts depended on the specific configuration of the original system and the daily load level that had to be supported. A system that only operated from March through October with a backup generator could also support the 12 and 18 kWh daily energy demands, which could not be supported by the original system. Even with limiting operation to March through October and using an emergency generator, the minimal battery capacity was at least 2.5 times larger than the daily energy demand, and the solar panel array had to be large enough that the nominal output would provide the daily energy demand in 3 hours of full sun. However, because of the trade-off relationship, these minimums cannot be attained together. While continuous in-field robotic deployments show promise for improving agriculture, it will be critical to design with energy efficiency in mind and the off-grid power supply for wide-spread use across agricultural lands. [ABSTRACT FROM AUTHOR]

A new highly effective sizing reagent based on grafted collagen copolymers has been proposed for cotton yarn. The copolymers were synthesized by reacting an aqueous solution of collagen with acrylic monomers—acrylic, matacrylic acids, and their amides in the presence of potassium persulfate. Based on Scanning electron microscopy ‐ Energy dispersive (SEM‐EDS) analysis data, the composition of the copolymers was determined. Unsaturated acids are more actively grafted onto collagen than their amides. When a polymer film is formed from a solution of a collagen copolymer with (meth)acrylic acid, microcracks appear on the surface of the sample; microcracks are absent in films of copolymers with (meth)acrylamide. Films of copolymers, especially methacrylamide, are quite flexible and contribute to a significant improvement in the properties of the yarn. The tensile strength of yarn sized with copolymers increases by 20%–65% compared to unsized yarn, and by 13%–38% compared to yarn sized with a starch solution. At the same time, the relative tensile elongation of the experimental yarn improves by 14%–58%, while this property of starch‐size yarn deteriorates by 14%–22% compared to unsized yarn. The complete removal of graft copolymers from the surface of the yarn in the process of biochemical desizing using the enzyme protease is shown. Highlights: Graft copolymerization of (meth)acrylamide with collagen was carried out.Grafting is initiated by the interaction of collagen with potassium persulfate.The synthesized copolymers are effective sizing reagents for cotton yarn.The copolymer with poly(meth)acrylamide forms a flexible and stable film.The protease enzyme completely removes the size from the surface of the yarn. [ABSTRACT FROM AUTHOR]

Renewable energy is an emerging trend to replace fossil fuels as a primary energy source. However, the intermittency of sources and high investment costs inhibit the full-scale adoption of renewable energy as the principal energy producer. This study presented a stand-alone hybrid renewable energy system, comprising solar panels and wind turbines as the primary energy source, with batteries and a diesel engine integrated as a backup system. Attempting to minimize the annualized total cost of investment and carbon emission, this study applied a new optimization algorithm, specifically the improved flower pollination algorithm, to acquire a techno-economically feasible design of a stand-alone hybrid renewable energy system. Performance comparison with the flower pollination algorithm showed that the proposed improved flower pollination algorithm could converge faster to the optimal solution in single-objective optimization problems. While minimizing both annualized total cost and carbon emission, the configurations of improved flower pollination algorithm were more dominant and evenly distributed than flower pollination algorithm. Lastly, the sensitivity analysis indicated that the annualized total cost of the hybrid renewable energy system was highly dependent on solar radiation, but not on wind speed. [ABSTRACT FROM AUTHOR]

Isolated mini-grids (MG) can be an efficient option for rural electrification worldwide. Nonetheless, a large share of MG fail after a few years and inadequate sizing has been identified as a major risk. Academia, public authorities and funding agencies tend to consider the sizing of mini-grids mostly from a technical and economic angle, looking to optimize performance for MG developers and operators with tools such as HOMER. This paper proposes a different approach. We study the strategies adopted by different MG stakeholders to deal with their own uncertainties and constraints in the sizing process. Based on field work in Kenya, we detail how MG funders and regulators transfer risks to private MG developers and operators. As a result, the latter face risks regarding demand estimation, funding and regulatory aspects when sizing MGs. In turn, they adapt their methods and business models, sometimes transferring risks to end users. While flexible sizing might be a solution, we show that regulatory and funding issues limit MG modularity, leading low-income customers to eventually bear the consequences of ill-suited sizing.

Abstract There is a necessity to use digital data and tools when developing children’s products. The present study was designed to provide digital methods to guide product development and problem-solving when using 3D body scans and face mask simulations for 6-year-olds. First, key facial measurements were evaluated to better understand the variables that might affect face mask sizing for children for the selected age group. Then the findings were used to optimize the size and fit of a cloth face mask design. Next, the fit of the digital, optimized face mask design was tested on 44 head scans from Size North America by using subjective and objective fit assessment techniques. Study findings suggested that width and length-related measurements are critical for children’s face masks. Body mass index (BMI) and ethnicity were also found to be the main factors for identifying size ranges in the selected age group. As BMIs increase, face mask sizes should increase. Additionally, the results indicated a need to use a larger database of children of all ethnicities to design an inclusive facemask that would provide a comfortable and protective fit for different facial proportions. Although the results cannot be generalized due to the case study approach of the present research and its focus on methods development, they can provide manufacturers, designers, and researchers with guidelines on how to develop proper sizing and use digital data to conduct functional fit analysis for facemasks.

Energy management strategies and optimal power source sizing for fuel cell/battery/super capacitor hybrid electric vehicles (HEVs) are critical for power splitting and cost-effective sizing to meet power demand for a good drive range, less energy loss and consumption, and minimal fuel cell and battery degradation for hybrid power sources. This paper presents a comprehensive review of the energy management techniques and their integration with energy source sizing, mainly for fuel cell/battery/supercapacitor hybrid electric vehicles. The paper discussed the benefits of integrating an energy management strategy (EMS) and the sizing of hybrid energy sources. Predictive based energy management strategies such as Artificial Neural Network (ANN), Reinforcement Learning (RL), and Model Predictive Control (MPC) were briefly examined. In addition, the paper reviewed hybrid algorithms or techniques for energy management strategies, that could be the combination of rule-based with a predictive, rule based with real-time and predictive with real-time, and predictive with learning based algorithms to give a good energy management strategy for fuel cell/battery/supercapacitor HEVs to achieve the optimal objective functions. The results show, that in terms of the size of the fuel cell, the evaluation of power demand-based and state of charge (SoC)-based methods used for large capacity batteries and smaller capacity batteries, reveals that the SoC-based method is appropriate for real-time energy management, while small capacity batteries have higher degradation. Fuel economy was improved with RL for battery engine hybrid vehicles than when Dynamic Programming (DP) was used. When the EMS was compared using dynamic programming (DP), Pontryagin’s minimum principle (PMP), and Equivalent Consumption Minimization Strategy (ECMS), the results show that ECMS is more efficient for online optimization than PMP and DP. Further results show that RL-based EMSs help to reduce energy losses and also increases the system efficiency, and help to reduce battery degradation as compared to when rule-based EMSs are used.

Hybrid Energy Systems (HES) combine multiple energy sources to maximize energy efficiency. Due to the unpredictability and dependence on the weather, integrating renewable energy sources (RES) is a viable option for distributed distribution (DG). To minimize environmental impact and meet the increasing energy demand–supply gap, scientists need to find alternative energy sources. Several studies have confirmed that HES is economically viable in remote areas, particularly in off-grid applications. Despite several improvements over the past few years, existing HES control systems are complex, costly, less reliable, and not sufficiently efficient. The purpose of this paper is to present the most common challenges faced by stand-alone hybrid energy systems and how the artificial intelligence (AI) technique has improved them. AI techniques are widely used in HES, and this study addressed how AI can solve classification, forecasting, networking, optimization, and control problems. This study provides an overview of the recent history of HES critical challenges in energy management, sizing, demand side management, and storage management; additionally, we have addressed several conceptual/theoretical problems, antecedents, and consequences that may be of interest or require further research. Companies must ensure their systems perform effectively and pay for their investments. Regardless of the system, failures and defects should be diagnosed and repaired as soon as possible. This can be achieved by increasing the system’s efficiency and preventing early-stage damage. Researchers and project managers who work on hybrid systems will find this paper to be an invaluable resource.

Delamination due to an inferior adhesion between reinforcement material and matrix in carbon fiber-reinforced thermoplastic (CFRTP) composites is a crucial problem to be solved. To this end, this study aims to overcome poor wettability between reinforcing phase, i.e., carbon fiber (CF), and thermoplastic matrix, i.e., polyetherether ketone (PEEK). Herein, CF's surface was tailored by application of different polymeric sizing agents which have different chemical structures. Morphology and topology analyses were performed by Scanning Electron Microscope and 3D laser scanning, respectively. Later, a variety of wettability results were obtained by the sessile drop method used in Contact Angle (CA) measurements for CFs throughout application of each sizing agent applied by dip coating. Sizing materials were designed such that the chemical structure of CF's surface could exhibit compatibility with the matrix itself. Consequently, complete wettability (CA: 0°) was achieved for CFs sized by HPEEK (CF/hydroxylated PEEK (HPEEK)) and the surface free energy (SFE) of CF was enhanced from 5.43 to 72.8 mJ/m2 while the SFE of the PEEK matrix is 40.1 mJ/m2. Moreover, sizing by HPEEK improved the average surface roughness of CF by 32% which enables optimized adhesion. Afterward, repetitive tensile tests were carried out to observe effects of improved interfacial interlocking on the mechanical properties of the final CFRTP composite. Stress–strain curves revealed that the tensile strength of CFRTP improved from 473 to 508 MPa through the sizing of CF by HPEEK whereas pristine PEEK has a much smaller tensile strength (98 MPa) than the aforementioned CF-reinforced composites. The sizing of carbon fiber's surface by HPEEK resulted in an enhanced adhesion with the PEEK matrix. Since the chemical structure and physical properties of sizing agent and matrix are compatible, potential debonding between them was eliminated. Thus, the improved wettability led to a substantial increase in the mechanical strength of the final TP composite. [ABSTRACT FROM AUTHOR]

Hybrid renewable energy systems (HRES) are gaining high interest in supplying electric energy for remote communities. Energy storage systems (ESS) are utilized by green autonomous HRESs to accommodate the variability of renewable resources such as wind and solar energy systems. The lack of any traditional energy source is adding a great reliability challenge which should be compensated using expensive ESS. This challenge can be avoided by using a pumped hydro energy storage system (PHES) in harmony with batteries. The PHES is an excellent option to be used in NEOM city due to the perfect topographical characteristic of this site. The minimum cost of energy and the highest reliability is used as an objective for sizing the proposed entire green HRES. Using smart grid principles (SGP) and demand‐side management (DSM) in the design and operation stages will minimize system size and cost, which can result in a significant reduction in consumer bills. As a result, this paper introduces an innovative DSM based on a dynamic tariff. The suggested DSM technique was developed utilizing a unique fuzzy logic that takes into account the present and day‐ahead ESS situations to intelligently determine the ideal tariff for the lowest cost and maximum reliability of the HRES. This paper introduces a modified grey wolf optimization (MGWO) technique to shorten convergence time while preserving the best accuracy. The suggested MGWO is assessed against 10 swarm optimization techniques. The payback period of the project is 7 years. The findings acquired from this unique program demonstrated its superiority, with conversion times reduced by 22% to 80% when compared to previous optimization procedures. Furthermore, as compared to the flat rate pricing tariff, the usage of the dynamic tariff lowered the LCOE by 53%. [ABSTRACT FROM AUTHOR]

The intermittent nature of power generation from photovoltaics (PV) requires reliable energy storage solutions. Using the storage system outdoors exposes it to variable temperatures, affecting both its storage capacity and lifespan. Utilizing and optimizing energy storage considering climatic variations and new storage technologies is still a research gap. Therefore, this paper presents a modified sizing algorithm based on the Golden Section Search method, aimed at optimizing the number of cells in an energy storage unit, with a specific focus on the unique conditions of Denmark. The considered energy storage solutions are Lithium-ion capacitors (LiCs) and Lithium-ion batteries (LiBs), which are tested under different temperatures and C-rates rates. The algorithm aims to maximize the number of autonomy cycles—defined as periods during which the system operates independently of the grid, marked by intervals between two consecutive 0% State of Charge (SoC) occurrences. Testing scenarios include dynamic temperature and dynamic load, constant temperature at 25 °C, and constant load, considering irradiation and temperature effects and cell capacity fading over a decade. A comparative analysis reveals that, on average, the LiC storage is sized at 70–80% of the LiB storage across various scenarios. Notably, under a constant-temperature scenario, the degradation rate accelerates, particularly for LiBs. By leveraging the modified Golden Section Search algorithm, this study provides an efficient approach to the sizing problem, optimizing the number of cells and thus offering a potential solution for energy storage in off-grid PV systems. [ABSTRACT FROM AUTHOR]

This study focuses on the development of a pilot-scale sizing line, including its initial design and installation, operational phases, and optimization of key process parameters. The primary objective is the identification of critical parameters for achieving a uniform sizing onto the fibres and the determination of optimal conditions for maximum production efficiency. This investigation focused on adjusting the furnace desizing temperature for the removal of commercial sizing, adjusting the drying temperature, as well as optimizing the corresponding residence time of carbon fibres passing through the furnaces. The highest production rate, reaching 1 m sized carbon fibres per minute, was achieved by employing a desizing temperature of 550 °C, a drying temperature of 250 °C, and a residence time of 1 min. Furthermore, a range of sizing solutions was investigated and formulated, exploring carbon-based nanomaterial types with different surface functionalizations and concentrations, to evaluate their impact on the surface morphology and mechanical properties of carbon fibres. In-depth analyses, including scanning electron microscopy and contact angle goniometry, revealed the achievement of a uniform coating on the carbon fibre surface, leading to an enhanced affinity between fibres and the polymeric epoxy matrix. The incorporation of nanomaterials, specifically N2-plasma-functionalized carbon nanotubes and few-layer graphene, demonstrated notable improvements in the interfacial shear properties (90% increase), verified by mechanical and push-out tests. [ABSTRACT FROM AUTHOR]

China's pursuit of carbon peak and carbon neutrality relies heavily on the widespread adoption of electric vehicles (EVs), necessitating the optimal location and sizing of charging stations (CSs). This study proposes a model for minimizing the overall social cost by considering CS construction and operation costs, EV user charging time costs, and associated carbon emissions costs. An improved quantum genetic algorithm, integrating a dynamic rotation angle and simulated annealing elements, addresses the optimization problem. Performance evaluation employs test functions and a case study using electric taxi trajectory data from Shenzhen. Findings reveal that higher charging power does not always yield better outcomes; appropriate power selection effectively reduces costs. Increasing the number of CSs beyond a threshold fails to significantly reduce carbon emission costs but enhances demand coverage. [ABSTRACT FROM AUTHOR]

There is a necessity to use digital data and tools when developing children's products. The present study was designed to provide digital methods to guide product development and problem-solving when using 3D body scans and face mask simulations for 6-year-olds. First, key facial measurements were evaluated to better understand the variables that might affect face mask sizing for children for the selected age group. Then the findings were used to optimize the size and fit of a cloth face mask design. Next, the fit of the digital, optimized face mask design was tested on 44 head scans from Size North America by using subjective and objective fit assessment techniques. Study findings suggested that width and length-related measurements are critical for children's face masks. Body mass index (BMI) and ethnicity were also found to be the main factors for identifying size ranges in the selected age group. As BMIs increase, face mask sizes should increase. Additionally, the results indicated a need to use a larger database of children of all ethnicities to design an inclusive facemask that would provide a comfortable and protective fit for different facial proportions. Although the results cannot be generalized due to the case study approach of the present research and its focus on methods development, they can provide manufacturers, designers, and researchers with guidelines on how to develop proper sizing and use digital data to conduct functional fit analysis for facemasks. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to explore the effects of the ciliary sulcus angle (CSA) on accurate prediction of the vault after phakic implantable collamer lens (EVO ICL Model V4c) using the KS formula. Methods: Patients were classified according to the size of CSA: group A, narrow angle (CSA < 30°); group B, normal angle (CSA = 30–90°); and group C, wide angle (CSA > 90°). Further, differences between the actual vault dimensions at 3 months postoperatively and the preoperatively predicted vault dimensions in the three groups were analyzed. Results: This study included 223 eyes of 223 individuals. In groups A–C, the difference in the preoperative vault dimensions of the three groups predicted with the KS formula was not statistically significant (P = 0.056). The actual vault dimensions at 3 months postoperatively were significantly different between the three groups (P < 0.001). Moreover, the difference between the actual and predicted vaults by the KS formula was statistically significant (P < 0.001). In the 3 months, after surgery, the percentages of patients with a low vault (< 250 μm) were 0%, 3%, and 29% in groups A, B, and C, respectively. Further, the percentages of patients with an ideal vault (250–750 μm) in the postoperative period were 66%, 84%, and 71% in groups A, B, and C, respectively. Finally, the percentages of patients with a high vault (> 750 μm) in the postoperative period were 34%, 13%, and 0% in groups A, B, and C, respectively. Notably, the distribution of the vault among the three groups was statistically significant (P < 0.001). Conclusion: The size of CSA significantly affects the predictiveness of the vault by the KS formula, with the most pronounced effect on the angles < 30° and > 90°. Therefore, CSA should be considered when selecting the lens size using the KS formula preoperatively. Clinical Trial Registration number: ChiCTR2200065501. [ABSTRACT FROM AUTHOR]

In this study, comprehensive analyses were used to evaluate the physical and chemical properties of basalt fibers, employing a variety of instruments. Additionally, heat treatment and solvent treatment methods were used to eliminate the sizing present on fiber surfaces. The heat treatment process involved determining the optimal temperature and duration required to remove the sizing from the basalt fibers. The appearance, chemical composition, and crystal structure of the original fibers were examined, including those subjected to heat treatment and those treated with solvents. These treated fibers were then incorporated into concrete to create basalt fiber-reinforced concrete (BFRC) specimens for mechanical tests, which assessed their compressive, flexural, and splitting tensile strengths. The results revealed that heat treatment at 300 °C for 180 min effectively removed the sizing on the basalt fibers, and the heat-treated basalt fibers exhibited uniform dispersion inside the BFRC specimens. In addition, solvent treatment primarily removed the soluble components of the sizing. The mechanical properties of specimens with sizing-removed basalt fibers were better than the specimens with original basalt fibers and the benchmark specimens. Crucially, the mechanical test results demonstrated that BFRC incorporating heat-treated basalt fibers exhibited a superior mechanical performance compared to BFRC incorporating original fibers or fibers subjected to the solvent treatment. [ABSTRACT FROM AUTHOR]