Visual Simulation Research Articles

Towards the design of a smart warehouse management system for spare parts management in the oil and gas sector

IntroductionThe oil and gas production industry requires rapid changing. As oil and gas companies around the world are called upon to decarbonize, several sectors within the industry are attempting to find new ways of working to achieve decarbonization. One of those sectors is spare parts warehousing. During the past decades of oil and gas production, spare parts warehousing has not been prioritized in optimization measures. Warehouses have been filled with material, all activities have been performed manually, and financial expenditure has been high. Now, a large oil and gas production company in Norway is looking to optimize its spare parts warehousing to streamline its logistics activities and increase sustainability.MethodThis study addresses the optimization ambitions of the company and proposes key design elements of a smart warehouse management system using Industry 4.0 technology implementation. The study is conducted by performing a review of relevant literature and company ambitions, before embarking on a qualitative design measure to contribute to the company’s innovative success.ResultsThe study proposes optimization of the warehouse activities goods receipt, issuing of stocked goods, and inventory count. Additionally, the digital supply chain of tomorrow and the technical architecture of a track and trace system in the warehouse is suggested.DiscussionThe study’s results can be used in practical implications and provide a foundation for future research. Future research is suggested to include extensive visual simulations, practical implementation studies, and studies on long-term effects of implementation.

Intraocular lens simulator using computational holographic display for cataract patients.

To develop and validate a holography based vision simulator for the demonstration of expected postoperative vision corresponding to monofocal and multifocal intraocular lenses (IOL) to cataract patients before surgery. An artificial eye model is used to measure the optical performance of different IOL types. The resultant aberrations and degradations are then modeled using phase holograms and shown to subjects on a holographic display. We measure the contrast and resolution loss, halos around the light sources, and point spread function (PSF) corresponding to three different IOLs. We tested the holography based vision simulator on 13 healthy subjects and 6 cataract patients. Monofocal, bifocal, and trifocal IOLs exhibited a contrast decrease of 5%, 42%, and 45% and a resolution limit of 4.49, 4.00, and 4.00 lp/mm (using 0.05 MTF criteria), respectively. Monofocal IOLs have the best resolution and contrast at the optimal focus distance, and multifocal lenses offer extended depth-of-field but exhibit prominent halos and reduced contrast/resolution. We confirmed that the visual functions of IOLs could be successfully modeled using phase holograms and simulated using a holographic display without using a physical IOL. Patients can experience the effects of different IOL options prior to surgery, which helps with IOL selection, expectation management, and patient satisfaction.

Retraction Note: Design of optical sensors based on computer vision in basketball visual simulation system

Retraction Note: Design of optical sensors based on computer vision in basketball visual simulation system

Visual simulation of intraocular lenses: from on-bench performance to computational and experimental validations

Visual simulation of intraocular lenses: from on-bench performance to computational and experimental validations

Retraction Note: Simulation of machine vision based on light detection sensors in aerobics judgment assistance system

Retraction Note: Simulation of machine vision based on light detection sensors in aerobics judgment assistance system

Procedure Design and Reliability Analysis for Prediction of Surface Subsidence of a Metal Mine Induced by Block Caving Method—A Case Study of Pulang Copper Mine in China

Surface subsidence resulting from block caving mining causes considerable environmental and economic harm in mining areas, highlighting the critical need for accurate predictions of surface subsidence. Given the unique features of the block caving technique and the resemblance between the released ore pillars and the mining processes, this paper developed a lightweight model to forecast surface settlement utilizing the probability integration approach to address the issue of predicting surface settlement in metallic mines. This study focuses on the Pulang Copper Mine, situated in the northeast of Shangri-La County within the Yunnan Province, as a case example. This mine employs the block caving method, which results in substantial surface subsidence. A visual mining simulation program is designed to combine the ore mining plan with the prediction model, manage the ore output of each mining point in batches, treat the ore pillars released in the planning cycle as strip work, and simulate and calculate the surface area above the ore pillars settlement value. The calculated values of surface subsidence induced by ore drawing are then interpreted as the downward displacement of the surface subsidence beneath the strip workings. Furthermore, to verify the reliability of the model, three-dimensional laser point cloud data of the Pulang Copper Mine in recent years were collected, and the differences between the predicted surface and the measured surface were calculated and analyzed.

Optimization method of cable structure demolition driven by digital twin evolution model

The large-span cable structure has the problems of complex component connection, cumbersome demolition process and difficult process coordination, which lead to high construction safety risk and low efficiency. Moreover, the optimization of the construction process scheme is difficult, and the convergence and visualization of the finite element analysis are insufficient, which hinders the construction efficiency. This study proposes a cable structure demolition optimization method driven by the digital twin (DT) evolution model. From the perspective of virtual-real mapping, the DT evolution process of cable structure demolition is clarified. The virtualization method of physical demolition process is formed by integrating visual modeling, simulation modeling and data modeling. Taking full account of the temporal and spatial evolution of the demolition process, a DT evolution model of the demolition process is established. Starting from the information flow, component flow, control flow and their relationship, the problems existing in the process of demolition execution are analyzed. Driven by the twin evolution process, a data mapping method for the demolition process is proposed. The safety risk is characterized by the mechanical properties (MPs) of the structure, and the expression language of the data association relationship is established. The particle swarm optimization back propagation neural network (PSO-BPNN) is improved, and an intelligent analysis method of MPs in the whole process of demolition is proposed. The best construction scheme is obtained by integrating the changes in MPs between the various demolition steps. The information of the demolition evolution process is divided into functional modules, and a DT platform is developed to efficiently guide the actual construction. Taking the demolition process of a cable truss experimental model as an example, the effectiveness of the proposed method is verified. The research results show that the DT evolution model can accurately map the actual demolition process. The deep learning method analyzes the mechanical properties of the structure and obtains the best construction scheme quickly and accurately. The development and application of the twin platform improves the degree of visualization and realizes the efficient guidance of the virtual model to the actual construction.

Non-native language comprehenders encode implied shapes of objects in memory

Barsalou (1999) proposes that conceptual knowledge is represented by mental simulations containing perceptual information derived from actual experiences. Although a substantial number of studies have provided evidence consistent with this view in native language comprehension, it remains unclear whether the non-native language comprehension processes also include mental simulations. The current study successfully replicates the shape match effect in sentence-picture verification (Zwaan et al., 2002) for non-native English language comprehenders, indicating native-like visual simulations. In addition, participants displayed better delayed recognition memory when the shape of the depicted objects matched the shape that was implied by the sentence than when it did not, suggesting that visual simulations were generated spontaneously in naturalistic non-native language comprehension. Additional correlational analyses revealed no relationship between English proficiency and the size of the match effect.

Application of indoor thermal energy cycle and visual communication simulation scene based on Machine vision and optical image enhancement

Traditional thermal analysis methods have limitations in complex environments, and innovative technologies are urgently needed to improve the accuracy of indoor thermal monitoring and optimization. In this paper, machine vision and optical image enhancement technology are combined to simulate the indoor heat energy cycle process to achieve more efficient heat management and visual communication, so as to improve the energy utilization efficiency and residential comfort of buildings. In this paper, a high-resolution camera is used to capture real-time images of indoor environment, image quality is enhanced by image processing algorithm, and heat distribution characteristics are extracted. The machine learning model is used to analyze the dynamic changes of the thermal energy cycle, and the visual model of the indoor thermal energy cycle is constructed by combining the fluid dynamics theory. The experimental results show that the proposed method can effectively identify and display the key areas of indoor heat circulation and their changing trends. The simulation results show that the optical enhanced images can show different temperature regions more clearly, directly reflect the heat flow situation, and have a high agreement with the actual measurement data. Therefore, the indoor thermal energy cycle simulation method based on machine vision and optical image enhancement not only improves the accuracy and real-time performance of thermal energy analysis, but also provides visual support for indoor environmental management.

Design of a Simulation and Evaluation System for Athlete Technical and Tactical Training Based on Virtual Reality Technology

In order to avoid the influence of external environmental factors on athletes’ physical fitness and technical tactics, the author proposes the design and research of an integrated simulation training system for athletes’ physical fitness and technical tactics based on virtual reality. The hardware unit of the design system includes a 3D scanner module, VR glasses module, locator module, tracker module, and wireless transceiver device. The software module introduces virtual reality technology and designs a visual simulation module, trained object detection module, trained object tracking module, and overall control module. The simulation experiment results show that compared with existing systems, the training scene output clarity and frame rate of the designed system are better, and the thread switching time and signal mixing time are shorter, which fully proves that the designed system has higher operating efficiency and better application performance.

Study on the environmental benefits of truck parking space for trucks waiting to enter freight terminal - A case study of Gangchen Logistics Park

The gathering effect of trucks at freight terminals and the high emission characteristics of trucks themselves lead to long-term truck queues and serious environmental pollution problems at freight terminals. Repeated stopping and following trucks aggravate the environmental pollution in the terminal. This paper proposes a scheme to plan truck parking spaces during waiting for trucks to enter the freight terminal in order to reduce the repeated stopping of trucks and to quantify the environmental benefits of truck parking spaces in the process. The truck admission process was simulated using the Visual Simulator (VISSIM). The simulation output provided vehicle operating data that was converted into operating mode distribution data using the Python calculation module. Then, the model parameters, including the operating mode distribution, were entered into the Motor Vehicle Emission Simulator (MOVES) to calculate the simulation scenario. Gangchen Logistics Park, for example, statistics of the park's 10 months of freight data, the design of freight volume gradually increased by 11 groups of admission simulation experiments, the simulation learned that the park queuing significant, more than 90% probability of queuing, queuing up to a maximum of 203 vehicles, the average queue of 61 vehicles. Then according to the actual road conditions in the park, add a parking lot in the VISSIM simulation. Signal sensing is realized by calling the COM interface of VISSIM through Python to guide the vehicles to park in order and enter the park. Eleven sets of simulation control experiments after designing and planning parking spaces are designed to calculate the pollutant emissions for each simulation scenario separately. The analysis of the emission measurement results shows that the emissions of CO, HC, NOX, and PM10 can be reduced by 1.90%, 7.90%, 9.42%, and 10.55% at the average level of the park's cargo volume. At the park's maximum cargo volume, it is possible to reduce HC, NOX, and PM10 emissions by about one-third. Truck parking space in the truck waiting to drive into the freight terminal process has obvious environmental benefits, queuing significant freight terminals should be reasonably planned truck parking spaces to reduce the freight terminal exhaust emissions pollution.

Application of BIM and Virtual Reality of System Integration Design and Development in Medical Building Projects: A Case Study in China

Design outcomes in the Medical Building Projects (MBPs) must satisfy the demand of the medical staff and stakeholders. However, they often do not have the relevant engineering expertise, so the design team is prone to misunderstandings when communicating with them using traditional two-dimensional (2D) Computer-Aided Design (CAD) drawings. The medical staff may not readily visualize and understand the design and then provide feedback to the designer through professional medical requirements or advice, which results in the need to redesign and carry out additional work during the design phase, thus delaying the progress of the MBPs. To address these challenges, this study aims to develop an integrated system based on BIM, advanced rendering engines, and VR technology for use in non-immersive and immersive VR environments. Moreover, in this study, the integrated system was applied to the infection-building project of the People's Hospital of Qingbaijiang District, Chengdu City, and semi-structured interviews were distributed to 16 engineers, designers, contractors, and medical staff who had been involved in the whole project to validate the practicality and effectiveness of the integrated system. The results indicate that this system integration is an efficient visual communication and simulation tool in medical design. Key advantages include enhanced communication efficiency between the design team and medical stakeholders, improved visual interaction, and streamlined decision-making processes within a 3D VR/BIM environment. The successful implementation of this integrated system is expected to significantly aid design teams and stakeholders in effectively managing medical design tasks in future projects.

Efficacy of a new video observational training method (intensive visual simulation) for motor recovery in the upper limb in subacute stroke: a feasibility and proof-of-concept study.

To demonstrate the feasibility and efficacy of a new video-observation training method (intensive visual simulation) to improve upper limb function. Small sample, randomized, evaluator-blind, monocentric study. Seventeen early subacute ischaemic stroke patients with complete hemiplegia were randomly assigned to the therapeutic group (n = 8) or control group (CG, n = 9). Thirty sessions of intensive visual simulation combined with corrected visual feedback (therapeutic group) or uncorrected visual feedback (control group) were performed over 6 weeks on top of a standard rehabilitation programme. 400-point hand assessment test (400p-HA). Box and Blocks (B&B), Purdue Pegboard test, Minnesota. The 400p-HA test improved significantly from T0 to 6 months for both groups, with a significant difference between groups at 3 months (MW-UT p = 0.046) and 4 months (MW-UT p = 0.046) in favour of the therapeutic group. One-phase exponential modelling of 400p-HA showed a greater plateau for the therapeutic group (F test p = 0.0021). There was also faster recovery of the ability to perform the B&B tests for the therapeutic group (log-rank test p = 0.03). This study demonstrated the feasibility and potential efficacy of an intensive visual simulation training programme to improve upper limb function in subacute stroke patients. A larger study is needed to confirm these results.

Executing realistic earthquake simulations in unreal engine with material calibration

Earthquakes significantly impact societies and economies, underscoring the need for effective search and rescue strategies. As AI and robotics increasingly support these efforts, the demand for high-fidelity, real-time simulation environments for training has become pressing. Earthquake simulation can be considered as a complex system. Traditional simulation methods, which primarily focus on computing intricate factors for single buildings or simplified architectural agglomerations, often fall short in providing realistic visuals and real-time structural damage assessments for urban environments. To address this deficiency, we introduce a real-time, high visual fidelity earthquake simulation platform based on the Chaos Physics System in Unreal Engine, specifically designed to simulate the damage to urban buildings. Initially, we use a genetic algorithm to calibrate material simulation parameters from Ansys into the Unreal Engine’s fracture system, based on real-world test standards. This alignment ensures the similarity of results between the two systems while achieving real-time capabilities. Additionally, by integrating real earthquake waveform data, we improve the simulation’s authenticity, ensuring it accurately reflects historical events. All functionalities are integrated into a visual user interface, enabling zero-code operation, which facilitates testing and further development by cross-disciplinary users. We verify the platform’s effectiveness through three AI-based tasks: similarity detection, path planning, and image segmentation. This paper builds upon the preliminary earthquake simulation study we presented at IMET 2023, with significant enhancements, including improvements to the material calibration workflow and the method for binding building foundations.

Simultaneous rare earth sulfate transformation and carbon dioxide mineralization

The wet metallurgical process route for recovering rare earth elements usually uses sulfuric acid. To obtain marketable individual rare earth products, converting rare earth sulfates to chlorides is essential. Conventional chemical precipitation and solvent extraction methods result in significant amounts of ammonia wastewater and greenhouse gas emissions. Therefore, we propose a novel process that integrates CO2 mineralization with rare earth sulfates transformation. By utilizing a base-catalyzed mechanism with trioctylamine (TOA), CO2 is effectively employed for selective precipitation of more than 95 % of rare earths from magnesium and calcium under optimized conditions. Subsequently, dissolution in hydrochloric acid allows for enrichment of the concentration of rare earths up to 188.3 g/L. The reaction mechanism is examined through Visual MINTEQ simulations and various analytical techniques. This process not only offers a sustainable approach to rare earth sulfates transformation but also contributes to carbon capture, utilization, and sequestration efforts.

A lightweight visualization tool for protein unfolding by collision detection and elimination

The experiments involving protein denaturation and refolding serve as the foundation for predicting the three-dimensional spatial structures of proteins based on their amino acid sequences. Despite significant progress in protein structure engineering, exemplified by AlphaFold2 and OmegaFold, there remains a gap in understanding the folding pathways of polypeptide chains leading to their final structures. We developed a lightweight tool for protein unfolding visualization called PUV whose graphics design is mainly implemented by OpenGL. PUV leverages principles from molecular biology and physics, and achieves rapid visual dynamics simulation of protein polypeptide chain unfolding through mechanical force and atom-level collision detection and elimination. After a series of experimental validations, we believe that this method can provide essential support for investigating protein folding mechanisms and pathways.

Retraction Note: Computer vision technology based on image optical processing in visual packaging art design simulation

Retraction Note: Computer vision technology based on image optical processing in visual packaging art design simulation

Thermal energy resource utilization and sample image restoration technology based on Machine vision simulation in interior design

With the rise of sustainable building design, the traditional design methods are often unable to fully consider the optimal allocation and application of thermal energy resources. This study aims to explore the application of heat resource utilization and sample image restoration technology based on machine vision simulation technology in interior design, and provide practical solutions for optimizing indoor environment. In this paper, machine vision technology is used to monitor and model indoor space in real time, and heat energy flow and distribution under different design schemes are simulated. At the same time, the influence of different designs on thermal energy utilization efficiency is analyzed by using sample image restoration technology. In the study, a set of comprehensive evaluation indexes was established, which comprehensively considered the factors of heat efficiency, indoor comfort and energy consumption. The experimental results show that the simulation technology based on machine vision can accurately predict the indoor heat distribution and identify the best design scheme. At the same time, the sample image restoration technology significantly improves the evaluation accuracy of heat utilization efficiency. Through these methods, the optimized design scheme has higher thermal energy utilization than the traditional design, and significantly improves the indoor comfort. This study shows that the combination of machine vision simulation and sample image restoration technology can effectively improve the utilization efficiency of thermal energy resources in interior design, and provide new ideas and methods for sustainable building design.

Design and Coupled Moisture-Thermal Transfer Simulation of Opposite Cross-Section Polyethylene Terephthalate Knitted Fabric with Hygroscopic Quick-Drying Capability.

In addition to sportswear and outdoor equipment, moisture-absorbent quick-drying fabrics are also widely used in everyday clothing and home textiles. In this study, three types of weft-knitted fabrics were designed using Coolmax fiber and polypropylene fiber. The Coolmax/PP fabric exhibits good stretchability with a strain of 180.5% and achieves a high cumulative individual transfer capability of 691.6%, with a water absorption rate of 50.2%/s. The moisture conductivity gradient presented good moisture and heat conductivity in a simulated human body temperature environment using an infrared camera. Furthermore, mathematical modeling was constructed and visual simulation analysis was conducted to explore moisture-thermal transfer behavior. The simulation results closely align with experimental data, providing insights into designing flexible and wearable quick-drying fabrics for thermal management.

Electro-Optically Configurable Synaptic Transistors With Cluster-Induced Photoactive Dielectric Layer for Visual Simulation and Biomotor Stimuli.

The integration of visual simulation and biorehabilitation devices promises great applications for sustainable electronics, on-demand integration and neuroscience. However, achieving a multifunctional synergistic biomimetic system with tunable optoelectronic properties at the individual device level remains a challenge. Here, an electro-optically configurable transistor employing conjugated-polymer as semiconductor layer and an insulating polymer (poly(1,8-octanediol-co-citrate) (POC)) with clusterization-triggered photoactive properties as dielectric layer is shown. These devices realize adeptly transition from electrical to optical synapses, featuring multiwavelength and multilevel optical synaptic memory properties exceeding 3 bits. Utilizing enhanced optical memory, the images learning and memory function for visual simulation are achieved. Benefiting from rapid electrical response akin to biological muscle activation, increased actuation occurs under increased stimulus frequency of gate voltage. Additionally, the transistor on POC substrate can be effectively degraded in NaOH solution due to degradation of POC. Pioneeringly, the electro-optically configurability stems from light absorption and photoluminescence of the aggregation cluster in POC layer after 200°C annealing. The enhancement of optical synaptic plasticity and integration of motion-activation functions within a single device opens new avenues at the intersection of optoelectronics, synaptic computing, and bioengineering.