Art In Modeling Research Articles

3D technologies in STEAM education

The article presents the application of 3D technologies in STEAM education through a conducted scientific research, highlighting the role of 3D modeling and 3D printing as an innovative approach in achieving an interdisciplinary learning model. The research included the following stages: preparation for designing a detailed 3D steam locomotive model; analysis of process difficulties; giving students and lecturers the opportunity to perform a specific modeling task, using basic primitives from solid geometry, as well as a questionnaire to analyze and evaluate the skills and knowledge of the participants in the 3D modeling field. In this context, the preparation process of a 3D steam locomotive model for educational purposes, using Autodesk 3ds Max software, is presented, and the 3D printing technology FDM is examined. We issued a challenge to the participants in the research to design a non-complex 3D model, using unfamiliar 3D modeling software Blender, within a limited time. The questionnaire covered topics in education, science, art, STEAM, and 3D modeling. The goal is to showcase the role of the integration of 3D technologies in educational environments with the idea of developing key skills and knowledge in learners.

A seven-step guide to spatial, agent-based modelling of tumour evolution.

Spatial agent-based models are frequently used to investigate the evolution of solid tumours subject to localized cell-cell interactions and microenvironmental heterogeneity. As spatial genomic, transcriptomic and proteomic technologies gain traction, spatial computational models are predicted to become ever more necessary for making sense of complex clinical and experimental data sets, for predicting clinical outcomes, and for optimizing treatment strategies. Here we present a non-technical step by step guide to developing such a model from first principles. Stressing the importance of tailoring the model structure to that of the biological system, we describe methods of increasing complexity, from the basic Eden growth model up to off-lattice simulations with diffusible factors. We examine choices that unavoidably arise in model design, such as implementation, parameterization, visualization and reproducibility. Each topic is illustrated with examples drawn from recent research studies and state of the art modelling platforms. We emphasize the benefits of simpler models that aim to match the complexity of the phenomena of interest, rather than that of the entire biological system. Our guide is aimed at both aspiring modellers and other biologists and oncologists who wish to understand the assumptions and limitations of the models on which major cancer studies now so often depend.

Graphic Modeling of Chinese Marine Folk Art

Chinese marine folk art modeling is a broad and diverse field, with different forms and styles of expression in different regions. The so-called flat modeling is a two-dimensional plane work composed of two elements, length and width, created by folk artists in coastal areas, whose expressive themes and modeling styles are related to the sea. These works usually depict themes such as marine life, fishermen's life, marine legends and myths, marine flora and fauna, etcetera, and use traditional craft techniques such as painting, embroidery and paper-cutting, which preserves the simplicity and primitive charms of folk art. While exhibiting China's maritime culture, these works also reflect the attitudes and aesthetic concepts of the people of China's coastal areas.

Interval Type-3 T-S fuzzy system for nonlinear aerodynamic modeling

This paper presents an aircraft related application of interval type-3 (IT3) T-S fuzzy system for nonlinear aerodynamic modeling from recorded flight data. The theoretical base developed for design of IT3 T-S fuzzy system is utilized and longitudinal aerodynamic coefficients are modeled. These longitudinal aerodynamic coefficients are related with lift force, drag force and pitching moment. The flight data used for simulation belongs to ATTAS aircraft which is operating in quasi steady stall maneuver flight condition. The applicability of IT3 fuzzy system for modeling data uncertainties are demonstrated by adding the external noise in recorded data and making uncertainties associated with unvarying and missing data. The IT3 T-S fuzzy modeling method can suitably characterize the complex and nonlinear behavior of the aircraft in the presence of uncertainty and unsteadiness created due to aerodynamic / propulsive / structural interactions, separated air flow and mass properties changes etc. The performance comparison of generated IT3 T-S fuzzy aerodynamic model is also carried out with other state of the art modeling methods, the proposed fuzzy model shows good prediction capability in presence of various form of data uncertainties with associated noise. It is also noticed that as noise content in data increases, the percentage improvement in accuracy (in comparison with other fuzzy models) also appears. However, this improvement is based on nature of application and data. For clean data, the performance of IT3 fuzzy system is almost equivalent to other modeling methods, but with the increase of noise content and uncertainty in data, the performance improvement of IT3 fuzzy system enhances. Thus, performance of the IT3 fuzzy systems becomes more appealing when, uncertainty arises in the data in form of noise or missing/unvarying data points.

World Art Market: Realities and Trends

The purpose of the article is to reveal the main components that led to the success of sales of digital and classical artworks through the analysis of current realities and trends in the global art market. To provide buyers (collectors), sellers, investors of artworks with a general picture of the development of the contemporary art market. The research methodology is based on the application of a systematic approach to the study of the art market of digital and classical artworks on the analysis of aggregate methods, in particular: art historal, analytical, empirical, historical, comparative, synthesis, and modelling. The scientific novelty lies in the use of digital platforms in sales in the global art markets, the peculiarities of conducting virtual auctions for sales using digital technologies. This has led to an increase in sales of digital and classical works of art in the art market. The practical recommendations to all players (buyers (collectors), sellers, and investors of the contemporary art market of artworks are proposed. Conclusions. Consequently, the emergence of a digital art market for the sale of artworks in a new virtual environment has led to a tenfold increase in the number of artists whose works have been presented on the global art market and who are currently actively participating in auction sales. Today's paculiarities include the commercialisation of the art market and the transition from classical art to Contemporary Art as the main trend and sales leader. The value of works sold by coontemporary artists reaches billions of dollars and is constantly growing. Despite the popularity of digital platforms with the ability to preview works of art through online viewing rooms (OVRs), many buyers and sellers still seek to participate in the sale directly and return to traditional offline events. This is especially true for the wealthiest private collectors who want to see an object for which they need to pay a significant amount of money. Sales trends in global art markets show that digital artworks cannot replace artworks on traditional media. Key words: virtual environment, information technology, NFT, blockchain, digital art, digital art market, cryptocurrency, transactions, digital platforms, contemporary art, trends, traditional media.

Application of Folk Art Modeling in Modern Art Design Based on Human-computer Interaction

Application of Folk Art Modeling in Modern Art Design Based on Human-computer Interaction

Computer Aided Art Modeling Design Method Based on Improved Genetic Algorithm

Computer Aided Art Modeling Design Method Based on Improved Genetic Algorithm

NFT as Leading Tool of Art in Representation of Visual Environment

The purpose of the work is to investigate the specifics of the impact of NFT technology on the state of art expertise in the organisation and implementation of virtual auction and gallery projects. The research methodology is based on the application of a systematic approach in the study of NFT technology on the analysis of aggregate methods, in particular art history, analytical, empirical, historical, comparative, synthesis, and modeling. The scientific novelty lies in the peculiarities of organising and conducting virtual galleries and auctions based on NFT technology in modern conditions. Practical and theoretical recommendations to specialists are developed for art critics for improving the methodological base, mastering new digital methods of auction and gallery activity in order to improve the level of qualification of art expert experts in the conditions of the unlimited dominance of digital technologies in the modern world. Conclusions. The rapid development of IT technologies in the modern world has led to a paradigm shift in traditional forms of organisation and conducting auction and gallery activities. This means that the art market is gradually moving from a traditional art market to a virtual one, where the exchange of classic works of art is replaced by the creation of semi-artistic samples of works of art by famous authors, which transform into a new reality through the prism of digital technologies, in particular, through NFT technologies. This, in turn, leads to the distortion of the classical vision of works of art and their devaluation. The creativity of world-renowned authors is presented in a new digital reality, where works of art go through different stages of their interpretation depending on the subjective vision of the creators of digital art. That is, we observe how the new generation tries to deny classical art and offers to use digital technologies to create their own digital works of dubious quality. At the same time, the involvement of the latest digital technologies helped to qualitatively improve and reliably protect property rights in the field of copyrights for works of art with the help of SEO, cryptocurrency, blockchain network and ensure the reliability of transactions during auctions.
 Key words: NFT, blockchain network, interpretation, digital art, virtual auctions and galleries, ownership, digital reality, cryptocurrency, transaction reliability.

A Comprehensive Review of Modeling and Optimization Methods for Ship Energy Systems

This paper presents a comprehensive literature review of the state-of-the art modeling and optimization methods for the power and propulsion systems of ships. Modeling is a tool to investigate the performance of actual systems by running simulations in the virtual world. There are two main approaches in modeling: physics-based and data-driven, which are both covered in detail in this survey paper. The output from the simulations might not be optimal in terms of certain performance criteria such as energy consumption, fuel cost etc. Hence, it is vital to optimize the systems considering the efficient interaction between the components, to yield the optimal performance for the integrated vessel’s powertrain. In this paper, the optimization case studies, for the ship energy systems, will be divided in terms of a) optimal design (topology and sizing), b) optimal control and energy management strategies, c) combined optimal design and control. Tables that summarize the literature review outcomes will also be presented at the end of each section. The main outcome is that limited literature is available for optimizations of ship powertrains using data-driven models, especially surrogate models. Surrogate-assisted optimizations for integrated ship energy systems can yield optimal solutions at fast computational speeds, with sufficient accuracy, even for complex, nested, multi-level, multi-objective optimizations.

Comparison of Data-Driven Modeling and Identification Approaches for a Self-Balancing Vehicle

This paper gives a systematic comparison of different state–of–the–art modeling approaches and the corresponding parameter identification processes for a self–balancing vehicle. In detail, a nonlinear grey box model, its extension to consider friction effects, a parametric black box model based on regression neural networks, and a hybrid approach are presented. The parameters of the models are identified by solving a nonlinear least squares problem. The training, validation, and test datasets are collected in full–scale experiments using a self–balancing vehicle. The performance of the different models used for ego–motion prediction are compared in full–scale scenarios, as well. The investigated model architectures can be used to improve both, simulation environments and model–based controller design. This paper shows the upsides and downsides arising from using the different modeling approaches. Videos showing the self–balancing vehicle in action are available at: https://tinyurl.com/mvn8j7vf

Characterization of Textile-Reinforced Mortar: State of the Art and Detail-Level Modeling with a Free Open-Source Finite-Element Code

Characterization of Textile-Reinforced Mortar: State of the Art and Detail-Level Modeling with a Free Open-Source Finite-Element Code

On modeling the multiscale mechanobiology of soft tissues: Challenges and progress.

Tissues grow and remodel in response to mechanical cues, extracellular and intracellular signals experienced through various biological events, from the developing embryo to disease and aging. The macroscale response of soft tissues is typically nonlinear, viscoelastic anisotropic, and often emerges from the hierarchical structure of tissues, primarily their biopolymer fiber networks at the microscale. The adaptation to mechanical cues is likewise a multiscale phenomenon. Cell mechanobiology, the ability of cells to transform mechanical inputs into chemical signaling inside the cell, and subsequent regulation of cellular behavior through intra- and inter-cellular signaling networks, is the key coupling at the microscale between the mechanical cues and the mechanical adaptation seen macroscopically. To fully understand mechanics of tissues in growth and remodeling as observed at the tissue level, multiscale models of tissue mechanobiology are essential. In this review, we summarize the state-of-the art modeling tools of soft tissues at both scales, the tissue level response, and the cell scale mechanobiology models. To help the interested reader become more familiar with these modeling frameworks, we also show representative examples. Our aim here is to bring together scientists from different disciplines and enable the future leap in multiscale modeling of tissue mechanobiology.

Research on the Creative Application of Origami Performance Techniques in Clothing

Abstract Origami has various manifestations and rich production techniques, and it is regarded as one of the indispensable contemporary art forms. In order to enrich the creative expressions of fashion design, this paper summarises the creative application forms of origami art in fashion design from the external and moulding characteristics of origami, studies the fabric characteristics through experimental verification, and summarises the applicable techniques of expression. The results show that the folding application forms of origami art and clothing modelling can be realised by using the expression methods of ironing and crimping, stitching texture moulding and repeated combination moulding, that is, pattern deformation folding application, fabric transformation folding application and modular combination folding application. The application of the folding form in clothing three-dimensional modelling and surface texture can give full play to the unique modelling beauty and artistic style of origami art and provide a reference for creative ideas in clothing design.

Jewelry Art Modeling Design Method Based on Computer-Aided Technology

In order to improve the effect of jewelry art modeling design, this paper applies computer-aided technology to jewelry art modeling design. Moreover, in order to solve the situation that the given data points do not form a topological rectangular grid, an interpolation algorithm based on triangular BB surfaces is specially studied in this paper. The algorithm automatically triangulates the given scattered data points to establish the topological relationship between the data points, and modified and optimized the triangulation algorithm according to the requirements of jewelry art modeling design. In addition, the improved algorithm can handle the triangulation problem of spatial data points well, and the triangulation speed is fast. The experimental verification shows that the jewelry art modeling design method based on computer-aided technology proposed in this paper can effectively improve the effect of jewelry art modeling design.

Parametric study and improved capacity model for RC beams strengthened with side NSM CFRP bars

Near Surface Mounted (NSM) fiber reinforced polymer (FRP) technique with rods/strips attached at the bottom face (B-NSM) has become widely used method for retrofitting concrete structures but has several practical limitations such as accessibility problems and premature debonding. A viable alternative by attaching the NSM FRP reinforcement at the side faces (S-NSM) has recently been presented and showed excellent effectiveness in limited research studies. In this study, a robust finite element (FE) model, featuring state-of-the art modelling techniques and nonlinear properties, is developed to study the flexural behaviour of reinforced concrete (RC) beams strengthened with S-NSM FRP bars. After validating its load, strain, and failure mode predictions with 6 full-size beam experiments, the model was used in an extensive parametric study on 108 new models, evaluating the effects of FRP bar diameter (df), strengthening length (SL), groove elevation (hg), tensile steel reinforcement ratio (ρs), and concrete compressive strength (fc’). In general, the beam ultimate load (Pu) increased with SL, df, ρs, and fc’. The beam ductility also seems to be affected by the studied parameters but in general was satisfactory, averaging 2.30 to 2.73. A regression-based formula was presented for the effective FRP bar length, beyond which the brittle concrete peel-off failure is prevented, and Pu becomes constant. A sectional analysis was also performed coupled with regression, resulting in the development of a simple equation to calculate the FRP strain at beam failure and consequently an improved analytical model for predicting Pu.

Graph-Based Dynamic Modeling of Two-Phase Heat Exchangers in Vapor Compression Systems

Vapor compression systems are a popular thermal management solution for high heat load applications because they benefit from the high heat transfer rate of two-phase fluid flow. However, model-based design and control of these systems proves challenging because of the complex and coupled hydro-thermal dynamics as the working fluid changes phase in the heat exchangers. When modeling these heat exchangers, there exists a strong tradeoff between model accuracy and computational complexity. While different techniques have aimed to reduce computational complexity of the model, they come at the cost of a decrease in accuracy. On the other hand, high fidelity models are computationally expensive to run. To bridge the gap between computational efficiency and accuracy, this work develops a novel multi-state graph-based dynamic modeling approach. The multi-state graph modeling approach is used to develop a dynamic model of a two-phase heat exchanger. The heat exchanger model is integrated into a vapor compression system model and the model behavior is verified against other models present in the literature. The results demonstrate that the multi-state graph model can accurately capture system dynamics within 1% of the current state of the art modeling approaches while providing valuable modularity for system level modeling. Additionally, the computational load can be made comparable to less accurate approaches.

A mechanistic model captures livestock trading, disease dynamics, and compensatory behaviour in response to control measures

Trade is a complex, multi-faceted process that can contribute to the spread and persistence of disease. We here develop novel mechanistic models of supply. Our model is framed within a livestock trading system, where farms form and end trade partnerships with rates dependent on current demand, with these trade partnerships facilitating trade between partners. With these time-varying, stock dependent partnership and trade dynamics, our trading model goes beyond current state of the art modelling approaches. By studying instantaneous shocks to farm-level supply and demand we show that behavioural responses of farms lead to trading systems that are highly resistant to shocks with only temporary disturbances to trade observed. Individual adaptation in response to permanent alterations to trading propensities, such that animal flows are maintained, illustrates the ability for farms to find new avenues of trade, minimising disruptions imposed by such alterations to trade that common modelling approaches cannot adequately capture. In the context of endemic disease control, we show that these adaptations hinder the potential beneficial reductions in prevalence such changes to trading propensities have previously been shown to confer. Assessing the impact of a common disease control measure, post-movement batch testing, highlights the ability for our model to measure the stress on multiple components of trade imposed by such control measures and also highlights the temporary and, in some cases, the permanent disturbances to trade that post-movement testing has on the trading system.

FLatt Pack: A research-focussed lattice design program

Lattice structures are an important aspect of design for additive manufacturing (DfAM). They enable significant component light-weighting and the tailoring of a wide range of physical responses; mechanical, thermal, acoustic, etc. In turn, lattice design relies on fundamental research to uncover useful structure-property relationships, such as the influence of cell geometry and volume fraction. A number of commercial computer-aided-design (CAD) programs exist that offer lattice generation, but these tend to prioritise product design. This paper describes the FLatt Pack program (or Functional Lattice Package), which was created to address the paucity of research-focussed lattice design software. It possesses a number of features with this in mind, including; (i) it is free to use for research, (ii) it is standalone software with minimal, and also free, dependencies, and (iii) it undergoes frequent and rapid development based on state of the art lattice information and modelling methods. FLatt Pack includes twenty-three lattice cell types covering a broad range of pore connectivity, structural anisotropy, and surface area; a clear GUI presenting the lattice design stages in a sequential manner; and the option to export designs in appropriate formats for AM and finite element (FE) simulation. The program also features conformal lattice generation in arbitrary shapes, arbitrary volume fraction grading, and resource-efficient computation through an adaptive spatial resolution based on the user’s design choices. The most recent version of FLatt Pack is freely available at: www.github.com/ian27ax/FLatt_Pack_dist .

Architectural model through the prism of cultural-historical tradition and new technologies

This article provides a comprehensive research of the architectural model as a cultural phenomenon in cultural-historical dimension since its origin to the latest technological solutions applied in modern architectural modeling. Research methodology is based on the structural-functional and semiotic approaches. The analysis of historical-cultural and modern development of architectural model reveals the five sociocultural functions fulfilled by the architectural model in professional activity, society and culture: professional planning and coordination of architectural project; presentation of the project to customer; commemoration of the outstanding results of human activity; educational engineering; art modeling, namely within the framework of the ensemble type of stenographic art.  It is demonstrated that since the beginning of the XXI century, the main function of architectural model – improvement of the project – intertwines with digital modeling for the most part. However, the presentational, commemorative, educational and artistic functions of the architectural model continue to be implemented in actual material, scaling up the distribution and improving the professional methods and techniques of implementation. Analysis is conducted on the role of 3D- printing for the development of modern architectural model. The conclusion is made that the architectural model is a universal form of retaining and transmitting cultural experience, the possibilities of which are not diminished by the advancement of digital technologies and virtual reality. The relevance of architectural model in modern world is associated with the unique quality of the phenomenon- to give a person an enticing illusion of symbolic appropriation of space. Digitalization of the society, professional activity, and education expands the needs for architectural modeling, and simultaneously provides new opportunities for implementation of a number of sociocultural functions of the architectural model on a new level.

Feasibility of Black-Box Time Domain Modeling of Single-Phase Photovoltaic Inverters Using Artificial Neural Networks

This paper introduces a new black-box approach for time domain modeling of commercially available single-phase photovoltaic (PV) inverters in low voltage networks. An artificial neural network is used as a nonlinear autoregressive exogenous model to represent the steady state behavior as well as dynamic changes of the PV inverter in the frequency range up to 2 kHz. The data for the training and the validation are generated by laboratory measurements of a commercially available inverter for low power applications, i.e., 4.6 kW. The state of the art modeling approaches are explained and the constraints are addressed. The appropriate set of data for training is proposed and the results show the suitability of the trained network as a black-box model in time domain. Such models are required, i.e., for dynamic simulations since they are able to represent the transition between two steady states, which is not possible with classical frequency-domain models (i.e., Norton models). The demonstrated results show that the trained model is able to represent the transition between two steady states and furthermore reflect the frequency coupling characteristic of the grid-side current.