Paint Systems Research Articles

A Survey System for Artificial Intelligence-Based Painting Using Generative Adversarial Network Techniques

The purpose of this paper is to construct an evaluation system for AI painting software based on generative adversarial network (GAN) technology, which optimizes the performance of the related software in terms of functionality, ease of use, system performance, and safety. The results of the questionnaires are statistically analyzed. In addition, an exploratory factor analysis was conducted to extract the data of the study, which were ultimately used to calculate the weight and importance of each index using the fuzzy hierarchical analysis method. This study constructed an evaluation system for AI painting software based on GAN technology, including 16 indicators of functionality, 16 indicators of ease of use, 7 indicators of system performance, and 8 indicators of safety, respectively, whose alpha coefficients were 0.882, 0.962, 0.932, 0.932, and 0.932, respectively. In addition, the accumulated explanatory variances of their coefficients were 84.405%, 84.897%, 84.013%, 72.606%, 73.013%, and 72.606%, respectively. It is clear that the items included in each of the indicators are homogeneous, with a high degree of internal consistency. This paper suggests that the development of AI painting software focusing on functionality, ease of use, system performance, and safety can enhance the market competitiveness of the software.

A Spray-Deposited Modified Silica Film on Selective Coatings for Low-Cost Solar Collectors

Solar collectors represent an attractive green technology for water heating, where sunlight is efficiently absorbed by a selective coating and the generated heat is transferred to water. In this work, the improvement and scale-up of an electrodeposited black nickel selective coating with a modified silica (MS) film deposited by spray pyrolysis are reported. The MS material was prepared by the sol–gel method using tetraethyl orthosilicate with the addition of n-propyl triethoxysilane to obtain a porous film with an adequate refractive index and enhanced flexibility. The reflectance of electrodeposited selective coatings was characterized with and without the MS film and compared to a commercially available coating of black paint. The MS film increased the solar absorptance from 89% to 93% while maintaining a much lower thermal emittance than the painted coating. The reflectance of the MS film remained unchanged after prolonged thermal treatment at 200 °C (200 h). The fabrication process was scaled up to 193 cm × 12 cm copper fins, which were incorporated in commercial-size flat-plate solar collectors. Three complete collectors of an area of 1.7 m2 were fabricated and their performance was evaluated under outdoor conditions. The results show that the electrodeposited selective coating with the MS film outperformed both the commercial black paint system and the system without the modified silica film.

Evaluation of the anticorrosive painting procedure with reused abrasive for surface preparation – a case study

Atmospheric corrosion is a relevant cause of failure for many metallic structures. Its aggressiveness depends on environmental factors such as relative humidity, salinity, and contaminants. Anti-corrosion paint is the most used technique to minimize this problem, and surface preparation is a fundamental step for suitable paint adhesion. Abrasive blasting can remove oxides and old paint and texture the surface for receiving a new coating. An alternative to reduce costs is reusing abrasive particles to make the process more sustainable. In this investigation, an paint system was qualified through tests in its current environment. The influence of reused abrasives on the painting process by the paint layer’s thickness and its adhesion to the substrate was evaluated. Samples blasted with new and reused abrasives were prepared to evaluate the surface preparation process, allowing surface roughness measurements and incrustation analysis. It was possible to observe that the layers of paint were thin and not uniform, had approximately 155 μm thick, and defects such as pinholes. Reusing the abrasive did not affect the surface average roughness, which was 9.4 ± 2.5 μm. Abrasive incrustation and other contaminants such as Na, P, K, S, and Cl were found on new and reused abrasive surfaces. Recommendations for improvement and suggestions for changing the process were possible to assess.

Determination of volatile organic compounds (VOCs) in indoor work environments by solid phase microextraction-gas chromatography-mass spectrometry

Volatile organic compounds (VOCs) are continuously emitted into the atmosphere from natural and anthropogenic sources and rapidly spread from the atmosphere to different environments. A large group of VOCs has been included in the class of air pollutants; therefore, their determination and monitoring using reliable and sensitive analytical methods represents a key aspect of health risk assessment. In this work, an untargeted approach is proposed for the evaluation of the exposure to volatile organic compounds of workers in an engine manufacturing plant by GC–MS measurements, coupled with solid-phase microextraction (SPME). The analytical procedure was optimized in terms of SPME fiber, adsorption time, desorption time, and temperature gradient of the chromatographic run. For the microextraction of VOCs, the SPME fibers were exposed to the air in two different zones of the manufacturing factory, i.e., in the mixing painting chamber and the engine painting area. Moreover, the sampling was carried out with the painting system active and running (system on) and with the painting system switched off (system off). Overall, 212 compounds were identified, but only 17 were always present in both zones (mixing painting chamber and engine painting area), regardless of system conditions (on or off). Finally, a semi-quantitative evaluation was performed considering the peak area value of the potentially most toxic compounds by multivariate data analyses.

Features of artistic presentation of images of people's leaders in the context of the development of the system of realistic painting in China in the XX – early XXI century

Features of artistic presentation of images of people's leaders in the context of the development of the system of realistic painting in China in the XX – early XXI century

Weathering tests to investigate the durability of anti-corrosion coatings and on-site repair materials

Steel structures are exposed to multiple environmental impacts that lead to reduced durability. Organic paint systems are a resilient mechanism to protect hydraulic steel structures from corrosion. Coatings lead to a decreased corrosion progress at damaged areas. In this work, we investigated the time dependency of undercoating corrosion in the neutral salt spray test in detail by conducting a long-term experiment. Thereby, the fundamental model of corrosion progress was investigated, leading to an increased reliability in approval procedures of coatings and in the choice of test parameters.Additionally, repair materials for on-site repair of damaged coatings were investigated in weathering tests to compare their performance with conventional coatings. These materials are used for short-term repairs of small damaged areas in order to postpone replacement of ailing structures, thus enhancing the durability of steel structures.

Analysis of automotive paint layers on plastic substrates using chemical imaging μ-FTIR and O-PTIR microspectroscopy.

Automobile paint chips are a crucial piece of trace evidence for forensic investigators. This is because automotive paints are composed of multiple layers, including the primer, basecoat, and clearcoat, each of which has its own chemical composition that can vary by vehicle make, model, year, and manufacturing plant. Thus, Fourier-transform infrared (FTIR) spectral databases for automobile paint systems have been established to aid law enforcement in, for example, narrowing search parameters for a suspect's vehicle. Recently, car manufacturers have implemented primers on plastic substrates that are much thinner (~5 μm) than those on metal substrates, making it more difficult to manually separate for analyses. Here, we evaluated FTIR microspectroscopy (μ-FTIR) and optical photothermal infrared spectroscopy (O-PTIR) to chemically image cross sections of paint chips without manually separating the layers. For μ-FTIR, transmission and transflection modes provided the highest quality spectra compared to reflection and μ-ATR analyses. Point analysis was preferable to chemical imaging, as peaks were identified in the point (MCT) detector's lower spectral range that was below the imaging (FPA) detector's cutoff, such as those associated with titanium dioxide. Reduced spectral range can lead to a similar issue in O-PTIR analyses depending on instrument configuration. However, its complementary Raman spectra showed strong titanium dioxide peaks, providing an alternate means of identification. Both techniques are likely to become more relevant as they are non-destructive and avoid manual separation of the layers. O-PTIR is particularly well-suited for analysis of the thin primer layer due to its superior spatial resolution.

Wall Painting Robot

Abstract: The automation of wall painting processes has garnered significant attention due to its potential to enhance efficiency, safety, and quality in the construction industry. This project focuses on developing an Automated Wall Painting system for both interior and exterior surfaces. The system employs readily available components such as Arduino Uno, NodeMCU, L293N HBridge Motor Driver, DC Motors, and other essential elements to achieve its objectives. The system comprises two primary components: the base and the support. The support component houses essential elements such as photoelectric seansors, paint spray mechanism, spray motor, and reservoir. Meanwhile, the base component incorporates four wheels, each driven by a DC motor, an obstacle sensor, and a 12V DC lead-acid battery for power supply. Upon activation, the system initiates the stepper motor, which drives the linear motion necessary for the support's back-and-forth movement along the wall surface. Simultaneously, the spray motor activates to ensure synchronized operation with the support motion, facilitating uniform paint application. This project addresses the challenges associated with manual wall painting, including labor intensiveness, safety concerns, and repetitive tasks. By automating the painting process, it aims to streamline operations, reduce labor dependency, and improve overall efficiency in construction projects. The system's simplicity, portability, and predictable performance make it a viable solution for enhancing productivity and safety in wall painting applications.

Research on service life prediction and decorative properties of acrylic paint in Vietnam's marine atmosphere by acceleration test

Vietnam is located in a tropical climate zone, especially coastal climates that quickly destroy coating materials that protect steel structures. Therefore, the service life of coatings is always of concern to manufacturers and users. This article presents the results of surveying changes in gloss, color and service life prediction of acrylic paint by accelerated tests, that have simulated according to marine tropical conditions, which are correlated with the atmosphere at Dam Bay station (Hon Tre Island, Nha Trang city, Khanh Hoa province, Vietnam). Gloss is determined according to ISO 2813:2014, and color change is determined according to standard ASTM E308-12. The service life of the acrylic paint system is determined according to standard GOST 9.401-2018. Calculation results based on accelerated test data show that the corrosion time of the acrylic paint system reaches Ri 3 (according to ISO 4628-3:2016 assessment), the service life of acrylic paint Tar 5366 is 2.91 years, and acrylic paint AR-752 is 2.66 years.

Making It Last: Training Conservators in Sustainable Solutions for Treating Outdoor Painted Sculpture

ABSTRACT Outdoor painted sculptures (OPSs) are a regular feature of public spaces and private collections throughout the world. Their painted finishes can appear deceptively simple, but their esthetic is a subtle combination of color, texture, and reflectance, making them challenging to care for and repair. OPSs are exposed to direct sunlight, rain, wind, pollutants, human interactions, and biological debris from plants and animals. Conservation of these artworks is a matter of preserving an artist’s esthetic intent, rather than the original paint system, which will inevitably need to be replaced. This paper discusses the development of the Getty Conservation Institute workshop Treatment Strategies for OPS, to develop skills in this specialized area of conservation. The full repainting of an artwork is expensive, laborious, logistically challenging, and includes the use of chemicals and processes with significant carbon footprints: improving the economic and environmental sustainability of these treatments has become imperative. The workshop teaches participants strategies that help stave off full repainting, such as working with specialized painters for lasting localized repairs, removing graffiti without altering the sculpture’s finish, and creating regular maintenance programs that help prevent deterioration.

Construction of a painting image classification model based on AI stroke feature extraction

Abstract A large number of digital painting image resources cannot be directly converted into electronic form due to their differences in painting techniques and poor preservation of paintings. Moreover, the difficulty of extracting classification features can also lead to the consumption of human time and misclassification problems. The aim of this research is to address the challenges of converting various digital painting image resources into electronic form and the difficulties of accurately extracting classification features. The goal is to improve the usefulness and accuracy of painting image classification. Converting various digital painting image resources directly into electronic format and accurately extracting classification features are challenging due to differences in painting techniques and painting preservation, as well as the complexity of accurately extracting classification features. Overcoming these adjustments and improving the classification of painting features with the help of artificial intelligence (AI) techniques is crucial. The existing classification methods have good applications in different fields. But their research on painting classification is relatively limited. In order to better manage the painting system, advanced intelligent algorithms need to be introduced for corresponding work, such as feature recognition, image classification, etc. Through these studies, unlabeled classification of massive painting images can be carried out, while guiding future research directions. This study proposes an image classification model based on AI stroke features, which utilizes edge detection and grayscale image feature extraction to extract stroke features; and the convolutional neural network (CNN) and support vector machine are introduced into image classification, and an improved LeNet-5 CNN is proposed to achieve comprehensive assurance of image feature extraction. Considering the diversity of painting image features, the study combines color features with stroke features, and uses weighted K-means clustering algorithm to extract sample features. The experiment illustrates that the K-CNN hybrid model proposed in the study achieved an accuracy of 94.37% in extracting image information, which is higher than 78.24, 85.69, and 86.78% of C4.5, K-Nearest Neighbor (KNN), and Bi directional Long short-term Memory (BiLSTM) algorithms. In terms of image classification information recognition, the algorithms with better performance from good to poor are: the mixed model > BiLSTM > KNN > C4.5 model, with corresponding accuracy values of 0.938, 0.897, 0.872, and 0.851, respectively. And the number of fluctuation nodes in the mixed model is relatively small. And the sample search time is significantly shorter than other comparison algorithms, with a maximum recognition accuracy of 92.64% for the style, content, color, texture, and direction features of the image, which can effectively recognize the contrast and discrimination of the image. This method effectively provides a new technical means and research direction for digitizing image information.

Drawing a satisfying picture: An exploratory study of human-AI interaction in AI Painting through breakdown–repair communication strategies

Artificial intelligence (AI) painting represents a burgeoning field in AI-generated content; however, there is limited research on users’ preferences and biases concerning AI painting compared to traditional forms of art. This study seeks to shed light on the communication and interaction dynamics between painters and AI tools in the process of creating a satisfactory image. A self-report study involving 52 volunteers and 312 reports was conducted, analyzing users’ communication strategies amid AI painting-related communication breakdowns. The investigation aimed to unveil users’ experiences, behavioral patterns, psychological motivations, and needs. The study identified three primary communication barrier categories in AI painting and proposed 10 corresponding repair strategies. It established a user experience framework within the evolving dynamics of user interaction, encompassing behavioral patterns and psychological motivations. Users’ perceptions of the AI painting system significantly impacted the interaction process, leading to an anthropomorphic view of the system as a “potential assistant” and the continuous use of effective strategies to “train” the AI painting system. Conversely, perceiving the system as a “flawed collaborator” prompted the adaptive expectation strategy. Persistent repair failures may lead to users attributing responsibility to the limitation of AI system, culminating in interaction termination. The study also explores the influence of user interaction experiences, including user background and interaction efficiency. By modeling users’ behavior patterns and underlying psychological cognitions, this research enhances the understanding of user psychology and preferences, an understanding that can be used to improve the efficiency of human–computer communication.

In-situ Zn-Al layered double hydroxide conversion coatings prepared on galvanized steels by a two-step electrochemical method

Zn-Al layered double hydroxide (LDH) pretreatment layer was prepared by a novel two-step electrochemical method on galvanized steel surface from a precursor solution containing Al3+-only. In the first step, anodic currents are applied to Zn deposit to produce Zn2+ in solution near the substrate surface. Cathodic currents are then applied to ensure the cathodic deposition of LDH film. The obtained LDH coatings not only provide excellent adhesion to the metal surface, but also enhance the adhesion between metal substrate and the top epoxy coatings. The “LDH/epoxy” painting system can protect galvanized steel from rusting for at least 150 days.

Self‐healing characteristics of superabsorbent polymers in epoxy coating for corrosion inhibition of carbon steels

AbstractThis study evaluated the self‐healing characteristics of superabsorbent polymers (SAP) in epoxy polyamide paint systems applied using brush application. The SAP underwent preliminary characterization to determine its primary properties and was then incorporated into the epoxy primer at different percentages. The epoxy‐SAP coating systems then underwent various tests to evaluate their self‐healing capability. Excellent adhesion is obtained with the coating system composed of initial epoxy primer, epoxy‐SAP layer, final epoxy primer, and an epoxy enamel topcoat. Electrochemical impedance spectroscopy (EIS) reveals that the addition of SAP increased the charge transfer resistance and pore resistance and decreased the double layer capacitance of the coating system in a span of 5 h, confirming the self‐healing of the coating. Maximum corrosion protection for 5 h is obtained between 15 to 20 wt% SAP. Lastly, it is determined through long‐term immersion tests that the addition of SAP in the coating significantly decreases the rust formation; however, the coating starts to peel off due to the swelling of SAP after 2–3 days.

Novel cool roofing technology system with sustainable design for attic temperature reduction

The penetration of increasing solar gain towards the building deteriorates the building's thermal quality and raises cooling demand. In particular, the roof receives the most solar gain. The roof system reformation is urged to improve the roof system's heat capacity and conserve building energy. This paper introduced a novel cool roofing system to replace the traditional roof system. The proposed novel cool roofing applications merged: (i) lightweight foam concrete, (ii) hollow concrete slab, (iii) white cooling paint and (iv) active reflective insulation system powered by solar energy. The discovery of the proposed system was evaluated with experimental chambers exposed to the outdoor environment. Under intense sunlight, the internal roof surface was 30.6 % cooler (50.5 °C to 35.0 °C). The mean attic temperature achieved was 33.9 °C under a field where the daily maximum recorded surrounding temperature is 43.0 °C. In contrast with a bare roof at 41.9 °C, the proposed design demonstrated a 19.2 % lower solar gain, achieving a sub-ambient structure. Besides that, the cooling demand simulation generated similar cooling demand savings (20 %). Significantly, this comprehensive cool roofing system exhibited a considerable and constructive outcome in cooling the buildings by achieving sustainable development to create a better and more environmental future for all.

ARSIP: Automated Robotic System for Industrial Painting

This manuscript addresses the critical need for precise paint application to ensure product durability and aesthetics. While manual work carries risks, robotic systems promise accuracy, yet programming diverse product trajectories remains a challenge. This study aims to develop an autonomous system capable of generating paint trajectories based on object geometries for user-defined spraying processes. By emphasizing energy efficiency, process time, and coating thickness on complex surfaces, a hybrid optimization technique enhances overall efficiency. Extensive hardware and software development results in a robust robotic system leveraging the Robot Operating System (ROS). Integrating a low-cost 3D scanner, calibrator, and trajectory optimizer creates an autonomous painting system. Hardware components, including sensors, motors, and actuators, are seamlessly integrated with a Python and ROS-based software framework, enabling the desired automation. A web-based GUI, powered by JavaScript, allows user control over two robots, facilitating trajectory dispatch, 3D scanning, and optimization. Specific nodes manage calibration, validation, process settings, and real-time video feeds. The use of open-source software and an ROS ecosystem makes it a good choice for industrial-scale implementation. The results indicate that the proposed system can achieve the desired automation, contingent upon surface geometries, spraying processes, and robot dynamics.

Implementation of intelligent painting systems in art education as a way of developing student self-efficacy and involvement: Post Lingnan Painting Spirit

Implementation of intelligent painting systems in art education as a way of developing student self-efficacy and involvement: Post Lingnan Painting Spirit

Diving into micro- and macroscopic properties of egg-tempera paint based on Sienna pigment

Egg-tempera painting was a pictorial technique widespread in the Middle Ages. In this work, Sienna earth and yolk have been used to formulate tempera paints according to historical recipes. Micro- and macroscopic properties were investigated to understand the interactions between the pigment and the binder. The pigment, inorganic part of the paint, was characterized by X-Ray Diffraction (XRD), thermal analysis (TG-DTA), Fourier Transform Infrared (FT-IR) Spectroscopy, granulometry, as well as Scanning Electron Microscopy (SEM). Then lecithin adsorption onto pigment particles was probed to understand yolk interaction with Sienna earth, pure kaolinite and goethite particles. NMR-Relaxometry was used to investigate the behavior and accessibility of the mineral surfaces to yolk and water. Macroscopic rheological properties of the paint systems were finally investigated.

The Wisdom of Bacchus: Emblematic, Iconographic and Literary Allusions in the Hermitage Painting by P. P. Rubens

The painting “Bacchus” by Peter Paul Rubens (State Hermitage Museum, St Petersburg) has frequently attracted the attention of both local and foreign researchers. In this article, we question the interpretation of the painting as a simple allegory of the autumn grape harvest and the celebration of production of young wine. Bacchanalian subjects since Antiquity have been loaded with additional meanings associated with regeneration and creative potentials. The latter aspect was picked up and developed by Renaissance artists. Rubens followed often that tradition. L. D. Davis saw in the Hermitage painting a metaphor of the creative method of the Flemish painter, who trusted intuitive impulses more than rigid rules. We share partially this point of view, but we propose to consider the named work in a broader sense than that scholar did. It seems to us that Rubens presented in “Bacchus” his allegorical self-portrait, emphasizing his love of life and his philosophical emancipation. Thus, the Flemish artist expressed his opposition to moralizing and short-sighted opinions in contemporary culture and his desire to return to the breadth of the Renaissance vision. As a consequence, the allusions contained in his painting to “The Andrians” by Titian, some emblems by Andrea Alciato, as well as the new Rubens interpretation of Comus, an ancient character, which John Milton used in his didactic mask a few years before the creation of Hermitage work, — don’t seem accidental. The portly Bacchus in the painting is presented as the lord of earthly diversity and boundless abundance, at the same time he is a wise mentor-judge, indicating how to properly handle all this wealth open to human race. The concept of the boon as the right disposal of freedom and desires, reflected in iconographic system of the Hermitage painting, fits with the ideas of Plato’s dialogue “Feast”.

Paint surface estimation and trajectory planning for automated painting systems

Paint surface estimation and trajectory planning for automated painting systems