Digital Model Research Articles

Linking past insights with contemporary understanding: an ontological and knowledge graph approach to the transmission of ancient Chinese classics

Ancient Chinese classics embody and transmit the intellectual heritage of China across generations. These texts, rich in enduring ideas, narratives, and insights, have been passed down through a lengthy historical process. While digital modeling of cultural heritage has advanced, research that integrates both the unique characteristics of these classics and their transmission processes remains limited. This study introduces ClaOnto, an ontology specifically designed for ancient Chinese classics. It captures the various versions of these texts and their interrelations, contents, related individuals, locations, periods, and languages. It also emphasizes the processes and evaluations involved in their transmission. This contributes to a more nuanced understanding and increased awareness of preserving ancient classics. ClaOnto comprises three modules: Basic Information, Transmission Information, and Evaluation Information. Its development involved adapting and enhancing existing mature ontologies, as well as designing new concepts and relationships to articulate the knowledge and intangible values transmitted through these classics across generations. Additionally, by employing methods such as data mining, text analysis, and data visualization, this study outlines a workflow for implementing this ontology-based knowledge graph, demonstrated using the Tao Te Ching as a case study. The methodological enhancement enriches the analysis of how the intangible value in classics manifests through transmission.

Uncertainty analysis of digital twin model of mine ventilation system

The digital twin model of mine ventilation system (DTMVS) plays an important role in intelligent safety management. However, the uncertainty of the ventilation resistance coefficient, which is the core parameter of the model, makes it challenging to accurately construct a DTMVS. In this study, Latin Hypercube Sampling (LHS) and ventilation resistance coefficient estimation models (VRCEMs) are used to analyze the uncertainty. First, the LHS method was used to explore the effect of uncertainty in the simulated airflow by continuously increasing the level of uncertainty in the ventilation resistance coefficients. Subsequently, the ventilation resistance coefficients were estimated using the VRCEMs, and the uncertainty of the ventilation resistance coefficient and the simulated airflow was analyzed. The results showed that the ventilation resistance coefficients with a 5% coefficient of variation can cause the DTMVS to lose 34% of the real airflow data points. The degree of uncertainty in the ventilation resistance coefficients estimated by the VRCEM-GA (VRCEM using genetic algorithm) and VRCEM-DE (VRCEM using differential evolution algorithm) methods was enhanced by 27.4% and 4.4%, respectively, compared with VRCEM-ES (VRCEM using evolutionary strategy algorithm). The VRCEM-ES model had the least influence on the uncertainty of the simulated airflow of DTMVS. The simulated airflow of the DTMVS constructed based on VRCEMs fluctuated normally within the confidence interval. VRCEMs had a higher sensitivity to the ventilation resistance coefficients of branches with low coefficients of variation.

Development and Validation of Concept of Innovative Method of Computer-Aided Monitoring and Diagnostics of Machine Components

The monitoring and diagnostic system has been suggested as a non-destructive diagnostic method. The structure and operation of the suggested system can be described by the concept of digital shadow (DS). One of the main DS subsystems is a set of sensors properly placed on the monitored object and coupled with a discrete data processing model created in Matlab/Simulink. The discrete model, as another important DS subsystem of the monitored facility, transfers information about its technical condition to the operator based on data recorded by the sensor system. The digital monitoring model processes the recorded data in the form of the object’s response to actions caused by its operating conditions. This work formalized a mathematical model determining the coupling of the digital model with the sensors placed on the monitored object. The formulated method using DS, due to its sensitivity, enables the detection of the damage in the object at an early stage. The tests allowed for detecting the regularities enabling the determination of the area of damage to the shaft and its size.

Development of the Digital Field Experience Model to Engage Adult Extension Audiences Synchronously Online

Development of the Digital Field Experience Model to Engage Adult Extension Audiences Synchronously Online

Potential of the upcoming Biomass P-band radar mission for digital terrain modelling beneath dense tropical forests: first accuracy assessment

Abstract. P-band radar surveys can be used to produce digital elevation models (DEMs) at ground level in dense tropical forest areas. However, the previous performance studies were carried out on DEMs derived from high-resolution synthetic aperture radar (SAR) acquisitions, while the upcoming Biomass space mission should provide DEMs at a coarser resolution due to a frequency bandwidth of 6 MHz in range. The aim of this study is to predict the quality of the DEM products derived from Biomass data through dense forest. A DEM was produced in a slant range geometry at a 15-m mesh size using SAR tomography. It was compared to the reference LiDAR survey in terms of elevation and slope, and the statistical distribution of the corresponding error was analysed with regards to the radar off-nadir angle and to the local slope and aspect. The results show that the DEM elevation has no systematic error despite the presence of forest, and it has an RMS error of 3 meters. The DEM slope has a mean error of 2° and an RMS error of 6°. The behaviour of these errors for different terrain slopes and aspects will allow to predict the quality of Biomass DEMs on a variety of terrestrial landscapes.

Pre-Planning and Post-Evaluation Approaches to Sustainable Vernacular Architectural Practice: A Research-by-Design Study to Building Renovation in Shangri-La’s Shanpian House, China

The renovation and revitalization of vernacular architecture are pivotal in sustainable rural development. In regions like Shangri-La, traditional structures not only safeguard cultural heritage but also provide a foundation for enhancing local communities’ living conditions. However, these villages face growing challenges, including infrastructure decay, cultural erosion, and inadequate adaptation to modern living standards. Addressing these issues requires innovative research approaches that combine heritage preservation with the integration of contemporary functionality. This study employs a research-by-design approach, focusing on the Shanpian House as a case study, to explore how pre-planning and post-evaluation methods can revitalize traditional vernacular architecture. The pre-planning phase utilizes field surveys and archival research to assess spatial, cultural, and environmental conditions, framing a design strategy informed by field theory. In doing so, it evaluates how traditional architectural elements can be preserved while introducing modern construction techniques that meet current living standards. The post-evaluation phase, conducted through questionnaires and semi-structured interviews, assesses user satisfaction, focusing on the impact of architectural esthetics, structural stability, and material choices. Key findings from an OLS regression highlight the strong positive correlation between architectural style, structural choices, and cultural relevance with resident satisfaction. The research emphasizes that design elements such as structural details, materials, and infrastructure upgrades are critical in shaping perceptions of both functionality and cultural identity. Interestingly, the model reveals that improving architectural esthetics, alongside modern indoor features such as network connectivity, has a significant impact on enhancing overall resident satisfaction (significance level: 0.181). This study contributes to the broader discourse on sustainable building renovation by demonstrating how traditional architecture can be thoughtfully adapted for contemporary use and also proposes a paradigm shift in the renovation of historic buildings, advocating for a balance between preservation and modernization. The application of sustainable materials, digital modeling, and innovative construction techniques further ensures that these traditional structures meet the demands of modern civilization while maintaining their cultural integrity.

Digital-twin-based multi-scale simulation supports urban emergency management: a case study of urban epidemic transmission

ABSTRACT Improving emergency management capabilities is vital for sustainable cities. However, urban emergency management is a complex, giant system that interacts between urban virtual and real spaces, requiring simulation in the virtual space and feedback to the real space. The digital twin model can potentially play an important role in this process, but still faces significant challenges in terms of modeling, simulation, and visualization. In this study, we propose a digital-twin-based multi-scale simulation method and take epidemic transmission as a case study. First, an entity-oriented unified urban database integrating multi-source urban data was constructed as the digital twins of urban human settlements for emergency modeling. Then, a multi-scale urban emergency simulation method in 3D geographic environment was proposed to support emergency simulation for multi-level urban management units. Moreover, an adaptive fusion rendering of emergency information and 3D scene was proposed to support the refinement of emergency visualization. An experimental case study on epidemic risk estimation was conducted through thousands of outbreak scenarios. The results demonstrate that the proposed method can establish the digital twins of urban human settlements, where modeling, simulation, and visualization of emergency at multi-scales can be carried out, thus enhancing the efficacy and efficiency of emergency management.

Heat transfer characteristics of petroleum coke particle packed bed: An experimental and CFD simulation study

AbstractDue to the complexity of the internal pore structure of petroleum coke loose particle‐packed beds, measuring their thermal conductivity has always been a challenging problem. This work independently developed an experimental apparatus for testing the thermal conductivity of petroleum coke particle‐packed beds and constructed a forward calculation model for the heat transfer process, which was based on one‐dimensional unsteady heat transfer. Using the Sparse Nonlinear OPTimizer (SNOPT) algorithm, a mathematical relationship between the thermal conductivity λ of the coke bed, temperature T, and equivalent particle diameter dp was established through inverse modeling. Concurrently, a digital model of the petroleum coke particle packed bed was derived utilizing three‐dimensional computed tomography (CT) scanning technology, and a pore‐scale gas–solid radiation heat transfer model was formulated based on CFD simulation technology, thereby further elucidating the heat transfer mechanism within the petroleum coke particle packed bed. The research results indicate that the temperature predicted by the established thermal conductivity model aligns well with experimental data. Further CFD simulation studies demonstrate that a smaller particle size leads to a larger temperature difference between the wall and the center of the packed bed, while a higher gas velocity results in a smaller temperature difference, with a linear correlation observed between these two factors. At high temperatures, thermal radiation between particles in the porous petroleum coke‐packed bed plays a dominant role. The research outcomes can offer significant theoretical support for a profound analysis of the heat transfer behavior of petroleum coke‐packed beds within a vertical shaft calciner.

Evaluating process parameters of SLS part of polyamide-12 recycled powder using RSM

Abstract Selective laser sintering (SLS) is a highly flexible rapid prototyping (RP) technology which can use a wide range of powdered materials to generate high quality complex geometries directly from digital models. The SLS process uses a laser to sinter selected areas of powdered materials to produce solid objects layer by layer, according to the 2D data obtained from CT scan or MRI imaging techniques. This paper presents research work for evaluating the effect of process parameters on impact toughness and surface roughness of the part manufactured on Farsoon SS402P SLS from recycled ageing FS 3300PA which is PA-12 based powder and standard operating parameters using Response Surface Methodology (RSM) design of experiments. Impact tests have been performed as per the ASTM D6110 standard using recommendations from ISO 179-2. According to the results, effect of process parameters are successfully analyzed by employing impact toughness and surface roughness tests. Based on the results of the ANOVA analysis, impact toughness increases with increasing laser power (4.467 j/cm2 at 72.5 watts). Similarly, it is also clear from the results that the region with the lowest laser power, high layer thickness, and 90-degree orientation had the lowest surface roughness (3.46 μm).

Directional wave spectrum estimation through onboard measurement data utilizing B-spline basis functions

The utilization of digital twin technology, which integrates real-world measurement data with a digital representation of the vessel, is garnering increasing attention within the realm of structural integrity management. Due to limitations in sensor deployment on ships, the integration of the digital twin framework, which merges measurement data with the ship's digital design model, becomes crucial for ensuring the effectiveness of structural integrity management. This investigation introduces a methodological approach for estimating localized responses at unmeasured locations, leveraging both measurement and design datasets. To approximate the response at unobserved sites, the directional wave spectrum is initially determined utilizing the least squares method, thereby, minimizing the disparity between the estimated and measured response spectra. The methodology notably incorporates cubic B-spline interpolation specifically to smooth the directional wave spectrum deployed on the heading-frequency domain. This deliberate choice of employing cubic B-spline interpolation underscores the emphasis on achieving a refined and continuous representation of the directional wave spectrum, thus enhancing the accuracy and reliability of the estimation process. To validate the proposed methodology, synthetic pseudo-measurement data derived from the wave spectrum and RAO of a 13,000 TEU container ship are employed. Subsequently, the directional wave spectrum is estimated utilizing the pseudo-measurement data, and the estimated directional wave spectrum, in conjunction with the Response Amplitude Operator (RAO), is harnessed to approximate the response spectrum at the location where sensors are not installed.

Automated self-adjustment of array probe with a robotic ultrasonic test system

Ultrasonic testing of objects with complex geometries often requires the use of a robotic arm to position the probe perpendicular to the local surface. Using immersion makes it possible to test these objects with standard ultrasonic linear array probes. Here, the probe positions and orientations provided by the robot are used for merging the locally acquired image data into a 3D-reconstruction. The quality of this reconstruction is highly dependent on the alignment of the position of the physical probe with the position used in the digital model. For common industrial tools, the tool center point (TCP) is usually acquired using geometric features of the tools. However, for ultrasonic arrays in immersion, there is a water standoff between the probe and the test object, therefore the TCP is in free space in front of the array and cannot be acquired with the common method. To overcome this challenge, we propose a method that allows the robotic ultrasonic system to automatically self-adjust the position and orientation of the ultrasonic probe using a test block made of steel with defined geometric features as a target for referencing. For each of the six degrees of freedom, a scan and adjustment routine are established using the data based on the actual ultrasound characteristics of the probe. Given a coarse pre-definition of the tool position and the known target test block, minimal human interaction is required to supervise the adjustment method, leading to higher quality reconstructions than with manual adjustment.

Experimental prototype of mesh antenna based on digital twin technology

The ring mesh antenna plays an important role in the field of aerospace communication owing to its excellent performance characteristics, but faces the challenge of decreasing profile accuracy due to environmental and structural failures during in-orbit operation. Digital twin, a promising technology, can effectively monitor and adjust the antenna surface accuracy. In other words, by creating a digital model of the physical entity, real-time monitoring and adjustment can be made to maintain the electrical performance of the antenna. In this paper, a digital twin system for an experimental prototype of a ring mesh antenna is proposed. Firstly, we introduce the preliminaries of digital twin technology. Secondly, we propose a system framework based on a five-dimensional digital twin model. Then, a digitization software and a visualization interface are developed. Finally, according to efficiency analysis and simulation results, the feasibility of the system was verified. We demonstrate its effectiveness in terms of real-time monitoring and automatic mesh adjustment functions, and significantly improve the efficiency of the adjustment process. It provides a reference with significant value for the application of digital twin technology in the field of aerospace communication, which significantly advances the development of this field.

Digital Models and 3D Biomechanics Analysis in Orthodontics. Part 1: Vector Calculations

Biomechanics is essential for optimizing orthodontic appliances and controlling dental movement. Charles J. Burstone pioneered a three-dimensional (3D) approach in orthodontics, advocating for a shift beyond appliance-focused methods. Initially, biomechanics studies were constrained to two-dimensional (2D) analysis due to the complexities of 3D evaluation. Despite progress in computational tools and digital modeling, orthodontic biomechanics has largely maintained a 2D orientation. This paper advances orthodontic biomechanics into 3D, re-evaluating concepts previously limited to 2D frameworks. A dedicated software, DDP-Ortho (Ortolab, Poland), is introduced to enable orthodontists to analyze and resolve biomechanical challenges in 3D, facilitating appliance designs with precise 3D force systems. The representation and calculation of force vectors and moments in 3D are detailed, emphasizing the inherent complexity absent computational support. Key processes such as vector subtraction and addition, fundamental for assessing and refining orthodontic force systems, are explained. Additionally, the vector split (couple replacement) method, previously described in 2D, is extended to 3D, addressing the unique constraints and challenges of this approach. These tools promise to refine the accuracy and effectiveness of orthodontic treatments, setting the stage to examine the interactions between 3D force systems and dental movement, which will be addressed in a subsequent paper, to broaden the potential of contemporary orthodontic therapy.

Research on evaluation technology for fuel tank inerting system based on task profile

Abstract The flammable and explosive characteristics of aviation fuel have always made the safety of aircraft fuel tanks a focus of attention in the aviation industry. At present, all aircraft test flights in our country require the completion of the evaluation of the fuel tank inerting subsystem, which has put forward clear requirements for the measurement of oxygen concentration in aircraft fuel tanks, and corresponding technical indicators have been developed based on the usage of civil and military aircraft. This article establishes a digital model of the aircraft fuel tank inerting system based on AMEsim software, verifies the accuracy of the model through literature data, and uses the digital model to study the variation law of oxygen concentration in the fuel tank. The temporal variation of oxygen concentration in the gas-phase space of aircraft fuel tanks is analyzed under different nitrogen-rich gas concentrations, nitrogen-rich gas flow rates, fuel tank loading rates, and aircraft descent rates. Based on the temporal variation of oxygen concentration, a reference is provided for formulating flight test methods.

Investigating the effects of variable pulse charging on temperature during charging of battery electric vehicles

This study investigates the efficacy of variable pulse charging (VPC) on charging 18,650 secondary battery packs (12 V, 20 Ah) with NMC chemistry. VPC, a modern technique applied to secondary battery charging, aims to mitigate effects like a thermal runaway and thermal propagation caused by increased charging temperature. VPC involves varied duty factors (10 % to 90 %), charging rates (0.5C, 1C, 1.5C), and an optimal switching frequency determined through frequency response analysis. Its digital model is based on in situ electrochemical impedance spectroscopy measurements and MATLAB/Simulink simulations. At charging rates of 0.5C (10 A), 1C (20 A), and 1.5C (30 A), the temperature of the battery pack reaches 42.46 °C, 57.87 °C, and 70.37 °C, respectively. However, implementing VPC at a 50 % duty factor yields temperature reductions of 3.66 °C, 5.06 °C, and 5.42 °C, respectively. Similarly, employing VPC at a 10 % duty cycle results in temperature reductions of 11.2 °C, 17.7 °C, and 19.1 °C, respectively. The results indicate a significant reduction in charging temperature compared to constant current charging. Furthermore, the 1C condition is validated using a custom-made dual active bridge DC-DC variable pulse charger. In conclusion, applying optimal frequency-based VPC with specific duty factors demonstrates the potential to reduce temperature elevation during battery pack charging significantly.

Application and Challenges of BIM Technology in China's Integrated Utility Tunnels

In the context of rapid urbanization, integrated utility tunnels present an innovative solution by consolidating various pipelines into a unified underground system, improving construction efficiency and urban management. This paper explores the role of Building Information Modeling (BIM), a breakthrough technology that enhances project design, simulation, and construction efficiency through digital modeling. BIM technology is optimizing utility tunnel construction by enabling better planning, monitoring, and collaboration through 3D and 4D modeling. Using a PESTEL analysis framework, this study evaluates BIM's application in integrated utility tunnels in China and its potential for advancing the digital transformation of urban infrastructure. The research reveals how BIM can enhance the informatization and intelligence of utility tunnels and discusses the future opportunities and challenges for its expansion in China's urbanization efforts.

Fast prediction of compressor flow field based on a deep attention symmetrical neural network

Accurate and rapid prediction of compressor performance and key flow characteristics is critical for digital design, digital twin modeling, and virtual–real interaction. However, the traditional methods of obtaining flow field parameters by solving the Navier–Stokes equations are computationally intensive and time-consuming. To establish a digital twin model of the flow field in a transonic three-stage axial compressor, this study proposes a novel data-driven deep attention symmetric neural network for fast reconstruction of the flow field at different blade rows and spanwise positions. The network integrates a vision transformer (ViT) and a symmetric convolutional neural network (SCNN). The ViT extracts geometric features from the blade passages. The SCNN is used for deeper extraction of input features such as boundary conditions and flow coordinates, enabling precise flow field predictions. Results indicate that the trained model can efficiently and accurately reconstruct the internal flow field of the compressor in 0.5 s, capturing phenomena such as flow separation and wake. Compared with traditional numerical simulations, the current model offers significant advantages in computational speed, delivering a three-order magnitude speedup compared to computational fluid dynamics simulations. It shows strong potential for engineering applications and provides robust support for building digital twin models in turbomachinery flow fields.

Digital twin water conservancy early warning system based on physical level and numerical simulation in intelligent water conservancy construction

Abstract. In 2023, the Central Committee of the Communist Party of China and The State Council issued the Overall Layout Plan for the Construction of Digital China, emphasizing the construction of a smart water conservancy system with digital twin basins as the core. The Guangxi Zhuang Autonomous Region government has clearly proposed to actively build a "digital twin Pinglu Canal", and attaches great importance to the construction of digital twin platform application services during the construction of the Western land-Sea New Passage (Pinglu) canal. Aiming at the problems such as unsatisfactory early warning effect, inaccurate data and imprecise model of existing smart water conservancy technology, this paper proposes a digital twin system for disaster early warning based on physical level and numerical simulation technology, establishes a visual digital water conservancy model and digital twin smart water conservancy cloud platform, and combines multi-physics field and multi-dimensional coupling algorithm to respond to technical pain points. To achieve scientific and accurate monitoring and intelligent management, and contribute to the construction of digitally empowered Pinglu Canal.

A model for sustainable development: Advancing digital food retailing

The technological revolution has driven food retail towards self-service technologies (SSTs). The supermarket concept thrived due to consumer convenience and direct food access. This qualitative study explored the modernization of food retail through new technologies, focusing on Canadian stakeholders’ perceptions. Using a grounded theory approach, it aimed to create a sustainable digital food system model addressing social and moral food access aspects. Findings revealed that digitalization in food retail is driven by economic motives and stakeholders’ desire for collaboration and partnership to support food access.

Digital operations research models for intelligent machines (industry 4.0) and man-machine (industry 5.0) systems

Digital operations research models for intelligent machines (industry 4.0) and man-machine (industry 5.0) systems