Visualization Tests Research Articles

Enhancing Cognitive Fit: Exploring the Potential of Mixed Reality for Developing Mental Rotation Skills

Mixed Reality is a promising venue for spatial ability training, allowing participants to engage in problem-solving through gesture-based interactions with holographic objects. 3-D measurement of learning in Mixed Reality environments may result in a better cognitive fit than 2-D. This mixed-method study measures and enhances mental rotation ability and investigates user experience in Mixed Reality. To assess mental rotation ability, we adapted the Purdue Spatial Visualization Test:Rotation for Microsoft HoloLens 2, creating a measurement tool for our Mixed Reality-based training program, Holomental. Comparing 2-D and 3-D tests, we explored how stimulus dimensionality influences accuracy and cognitive load. Our findings indicate that Holomental enhances mental rotation performance, both in 2-D and 3-D. Cognitive load in the 3-D test was lower than in the 2-D test. Semi-structured interviews revealed participants’ appreciation for the representational and interactional affordances of the training environment. This study provides valuable insights into the effectiveness of 3-D spatial training, with implications and suggestions for future design considerations.

Study of the effect of pore properties of microporous layer on water transport process in proton exchange membrane fuel cell

Aiming at the “water flooding” phenomenon inside the Gas Diffusion Layer (GDL) of the Proton Exchange Membrane Fuel Cell (PEMFC), this paper visualizes the effects of the pore properties and gradient structure of the microporous layer (MPL) on water transport. Specifically, we visualize the impact of pore properties and gradient structure on water transport. For this purpose, a liquid water capillary finger advancement visualization test platform is constructed to analyze the evolution of liquid water in the porous medium and reveal the effects of single porosity, single pore diameter, gradient porosity, and gradient pore diameter of the MPL on the liquid water transport. Moreover, the time of the non-wetting liquid touching the top, the maximum spreading length, and the residual volume in the MPL are analyzed to evaluate the drainage capacity. The results highlight that the microporous layer's smaller porosity and pore size could limit the interface's extended width between the microporous and gas diffusion layers. Additionally, the residual volume of non-wetting liquid is 21.6 % less in the case of φ = 0.3 than for φ = 0.45, and the residual volume of non-wetting liquid is 11.8 % less in the case of d = 0.82 mm compared to d = 2.45 mm. Furthermore, the residual volume of the microporous layer in the Catalyst layer (CL) side of the microporous layer is 11.8 % less than that in the case of d = 2.45 mm. Finally, we conclude that when the pore gradient law is opposite, it is unfavorable for liquid water discharge.

Comparative Analysis of Augmented Reality in Engineering Drawing Course: Assessing Spatial Visualization and Cognitive Load with Marker-Based, Markerless, and Web-Based Approaches

This study investigates the integration of augmented reality (AR) into engineering education, with a specific focus on its impact on spatial visualization abilities and the cognitive load in the context of an engineering drawing course. The research employs a structured approach, involving three experimental groups utilizing marker-based (MBAR), markerless (MLAR), and web-based AR (WBAR) applications, in comparison to a control group receiving traditional instruction. The primary objective is to rigorously assess the comparative effectiveness of these instructional approaches in enhancing spatial visualization skills and reducing the cognitive load of undergraduate engineering students. Spatial visualization, a vital cognitive skill for engineering disciplines, is evaluated using the Purdue Spatial Visualization Test: Rotations (PSVT-R) questionnaire. The cognitive load of students is assessed with the help of a questionnaire comprising items related to mental load and effort. This study not only quantifies the impact of AR applications but also highlights subtle differences among the various AR modalities. The findings suggested that the group that used marker-based AR had better improvement in their spatial ability and felt less cognitive load compared to those who utilized markerless AR and web-based AR.

Automatic Detection of Concrete Surface Defects Using PRE-TRAINED CNN and Laser Ultrasonic Visualization Testing

In recent years, nondestructive testing for civil engineering structures has become increasingly important. Ultrasonic testing is one of nondestructive inspection methods for civil structures. However, the inspection of civil engineering structures takes much time because of the extensive scope of the inspection. Moreover, in the field of nondestructive testing, there are also concerns about a future shortage of inspectors, so that an innovative effective nondestructive method needs to be developed. This study proposes an automatic defect detection approach using pre-trained convolutional neural network for laser ultrasonic visualization testing. The effectiveness of the proposed method is confirmed by applying it to a concrete structure with a surface defect. Grad-CAM demonstrates that the created CNN model in this study accurately predicts the position of a surface defect of concrete specimens.

Evaluation of cavitation phenomena in three-way globe valve through computational analysis and visualization test

A three-way valve has a multi-port structure with three openings, which allows control of the fluid direction. However, owing to the complicated trim shape of the internal flow, an irregular fluid flow occurs, which hinders precise fluid flow control. In severe cases, cavitation induces mechanical damage owing to abrupt changes in the fluid direction. In this study conducted a computational fluid dynamics (CFD) analysis was performed to estimate the localized cavitation around the bottom plug of the three-way valve. To quantify localized cavitation, the percentage of cavitation (POC) was derived using the vapor volume fraction (VVF). The POC, defined by the cavitation occurrence zone with VVF > 0.5 divided by the volume of the cavitation danger zone, was 34.90%. Cavitation at this POC level could cause mechanical damage; therefore, a size optimization was performed. The lengths of the optimized waist and tail regions of the bottom plug were obtained wherein the POC level decreased by 19.06%. In addition, experiments were conducted using a flow visualization test setup. The experimental results were quantified into the POC employing the image gradients method, and the results were in good agreement with the CFD analysis.

Biomimetic Soft Robotic Jellyfish for Lentic Ecosystem Monitoring

Environmental monitoring of lentic ecosystems is well suited for swarm robotics applications since they can operate autonomously and cover large regions. For such a task, a locomotion mechanism is necessary for traversal. Due to the challenging nature of underwater environments, researchers often draw inspiration from nature to improve robot mechanical performance. A box jellyfish in a good inspiration due to their efficient jet propulsion. Soft and smart materials are helpful in mimicking their propulsion because they can perform flexible and complex movement. Shape memory alloy (SMA) springs have been used for this purpose, but their slow actuation rate is a well-known disadvantage. This project aims to improve cycle rate and thus swim speed by implementing a bistable spring configuration into a soft robotic jellyfish. The bistable mechanism stores energy slowly in the expansion of the elastic silicone bell, then releases it suddenly in a contraction which propels the robot forwards with a higher force than would be possible with direct SMA actuation. Additionally, the antagonistic arrangement of SMA springs reset each other and produce the same outward expansion on both up and down stroke, improving cycles speeds by removing the need for a dedicated reset stroke which is typically required before using the springs again. Also, increasing the number of spring pairs does not interfere with the actuation, meaning cycle rates can be further improved by cycling which pair of springs is active. The proof-of-concept device operates at a frequency of 0.4 Hz, and produces enough thrust while tethered to swim through a tank. Future work involves performing fluid visualization tests to validate a simple mathematical model of flow through the bell, as well as optimize the design, integrate onboard environment sensors and implement autonomy to allow operation in a larger swarm.

Visualization and quantitative evaluation of aerosol deposition using 3D-printed adult nose cavities

Local steroid medication is one of the most important treatment options for chronic rhinosinusitis. Regional deposition has a higher clinical value compared with total deposition in predicting treatment outcomes or evaluating adverse reactions. The goal of this project is to propose an effective technique for visualizing and quantifying aerosol deposition in a three-dimensional adult nasal cavity, and to verify the practicality of this method. Three-dimensional (3D) nasal cavity models were constructed from computed tomography (CT) scans of one post-operative rhinosinusitis subject using imaging software. The nasal cast was coated with a water-indicating paste and deposited with saline; a liquid dressing was added to visualize the progress. The quantity of liquid dressing was evaluated via HPLC and the liquid deposition was analyzed within the nasal cast cavity. Herein, 98.77% of the particles generated by the nebulizer were over 5 μm, suggesting that most of the aerosol could effectively enter the nasal cavity instead of the lower respiratory system. The liquid dressing was mainly deposited in the nasal cavity, ethmoid sinus, and frontal sinus according to the visualization tests. HPLC results suggested that the main deposits were the frontal sinus (up to 41.80%) as well as in the sphenoid sinus and ethmoid sinus (14.00%). The large particle nebulizer (BM-TCA) generally led to better deposition in sinus areas when compared to the smaller particle nebulizer (PARI). This technology allows for in vitro testing of various types of nasal preparations and equipment under various test methods.

Evaluating 3D Apparel Simulation Technology's Performance of Creative Pattern-Cutting Techniques with the Assist of ASVT

Three-dimensional (3D) simulation technologies have experienced a significant rise in popularity in the fashion industry. Analyzing the efficacy of such technologies aids in pinpointing areas that require enhancement. While previous studies mostly focused on evaluating the fit and appearance of 3D simulation technologies with simple clothing styles, this research aims to assess the effectiveness of 3D fashion simulation software in producing digital designs that include creative pattern-cutting techniques known for their intricate structures and design complexities. Four designs were chosen to exemplify different design characteristics, and 95 people were recruited to assess the effectiveness of two cuttingedge 3D fashion simulation programs. Furthermore, the researchers utilized the apparel spatial visualization tests (ASVT) to examine whether the participants’ spatial visualizing aptitude would impact their assessment outcomes. The findings offer suggestions for enhancing the existing 3D simulation technology and provide instructions for the assessment procedure.

Analysis of Bubble Flow in an Inclined Tube and Modeling of Flow Prediction

The lubricating oil system is a significant component of aviation engine lubrication and cooling, and the scavenge pipe is an essential component of the lubricating oil system. Accurately identifying and understanding the flow state of the scavenge pipe is very important. This article establishes a visualization test bench for a 45-degree inclined scavenge pipe, with upward and downward flow directions, respectively. The test temperature is 370 K, and a high-speed camera captures the changes in the two-phase flow inside the pipeline. Based on high-speed photography photos, we develop software for analyzing the flow characteristics of bubbles inside the tube and explore the influence of gas phase conversion velocity and liquid phase conversion velocity on the apparent velocity of bubbles inside the tube. Multiple algorithms were used to develop the model by combining machine learning with speed and accuracy to establish a data regression prediction model for the apparent velocity of bubbles inside the tube. Through calculation and analysis, it was found that the root mean square error of the prediction model using the BP neural network algorithm was the lowest, and the decision coefficient of the prediction model using the support vector machine algorithm was the highest.

Forensic identification of fingerprints on various substrates based on fluorescent carbon nanodots from date seeds assisted by Tracker software

Fingerprint identification is done by observing fingerprint patterns usually found on various surfaces at crime scenes. However, fingerprints are easily damaged, erased, and/or lost. Therefore, alternative materials are needed that can preserve fingerprint patterns. In this study, we use carbon nanodots (C-dots). This research aims to prepare and characterize C-dots made from date seeds, and then determine the robustness of the latent fingerprints using C-dots on various printed substrates assisted by Tracker software. This is experimental research of preparing and characterizing fluorescent C-dots from date seeds and printing fingerprints on various substrates. The C-dots were prepared using oven and microwave heating methods and characterized using an ultraviolet-visible (UV-Vis) spectrophotometer, photoluminescence (PL), X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and particle size analyzer (PSA). The substrates used for printing the fingerprints were plastic, ceramic, paint, and glass. Based on the characterization results, the C-dots have i) an absorption peak at wavelength of 252.2 nm (core) and band gap energy of 3.27 eV, ii) an emission wavelength of 495 nm emitting cyan color, iii) an amorphous structure based on the diffraction pattern, iv) functional groups of C-H, CC, CC, and O-H, and v) particle sizes of 1.3 nm (< 10 nm). Moreover, the results of the fingerprint identification based on the visualization test were successful because a subject’s fingerprint pattern was formed and various patterns were identified. In the robustness test, the latent fingerprints lasted 30 days and then slightly faded in the whorls pattern.

Visual Loop-Mediated Isothermal Amplification (LAMP) Assay for Rapid On-Site Detection of Escherichia coli O157: H7 in Milk Products.

(1) Background: Rapid on-site testing is an effective method for the detection of Escherichia coli O157: H7(E. coli O157: H7) in food ingredients and the environment. (2) Methods: In this study, we developed colorimetric loop-mediated isothermal amplification (LAMP) and immunochromatographic test strips (ICTs) for the rapid and visual detection of E. coli O157: H7. This study designed new specific LAMP primers for E. coli O157: H7 virulence island genes. After the LAMP amplification, the double-stranded DNA target sequence labeled with digoxin and fluorescein isothiocyanate (FITC) at both ends was bound to the anti-digoxin antibody on the gold nanoparticles. Subsequently, it was further bound to the anti-FITC antibody at the T line of the ICTs, forming a positive test result. Hydroxynaphthyl blue dye was directly added to the LAMP amplification product. A blue color indicated positive results, while a purple color indicated negative results. (3) Results: Two visualization methods showed high specificity for the target strains. The visualization tests had sensitivities of 5.7 CFU mL-1, and the detection limit of the Escherichia coli O157: H7 in artificially contaminated milk samples was 5.7 × 102 CFU mL-1, which was consistent with the results of the standard method (LAMP-electrophoresis method) used in commercial inspection. (4) Conclusions: Both methods could be useful in remote and under-resourced areas.

Liquid level monitoring and quenching front tracking for SMR rod bundle CHF tests under low pressure, low flow, high quality conditions

In most Light Water Reactor (LWR) based Small Modular Reactors (SMRs), one of the critical factors that might affect Critical Heat Flux (CHF) and other thermal–hydraulic phenomena under low flow, low pressure, high-quality conditions is the existence of high water column over a relatively short fuel core in the majority of the integral design SMR reactor vessels. With the existence of this water column over the relatively short and high-power peaking fuel bundle, the potential of a reflood quenching effect is highly plausible under low pressure, low flow and high-quality conditions as the location of the CHF event will be much closer to the exit plenum, especially in the case of exit power peaking. The results from CFD modeling and flow visualization tests presented in this paper demonstrate the importance of liquid level as well as its impacts on rod bundle CHF. Such a critical factor has often been overlooked by the prevailing SMR designs as many of the rod bundle CHF tests performed for SMR, including those with the licensing data, have either neglected the effects of the exit quenching effect, or were performed with non- prototypical heater rod designs or surrogate fluid that may not include such exit quenching phenomena.In this paper, the phenomenon of exit quenching on SMR rod bundle CHF has been introduced with the development of the proprietary On-line, Real-time Liquid Level Monitoring System (OR_LLMS) and On-line, Real-time dynamic Quenching Front Tracking Systems (OR_QFTS), which allow accurate measurements of rod bundle CHF as a function of both liquid level and degree of downward quenching under various test conditions. The future application is also presented, which will aid in the development of rod bundle CHF correlations that account for and take advantage of different water levels over the reactor core.

Experimental and numerical investigations on the intermittent heat transfer performance of phase change material (PCM)-based heat sink with triply periodic minimal surfaces (TPMS)

The excessive heat generated during the operation of electronic components leads to significant temperature increases, posing a significant risk to their service life. For the problem of efficient thermal management of electronic devices in confined spaces experiencing high heat flow, a scheme using triply periodic minimal surfaces and a phase change material-based active–passive cooling heat sink is proposed to control the temperature of electronic equipment. The apparent heat capacity method is employed to simulate the intermittent process of the phase change material-based heat sink. The optimization based on Box-Behnken Design and Nondominated Sorting Genetic Algorithm II is analyzed to obtain an improved triply periodic minimal surface structure. The effect of thermal performance (including base temperature, liquid fraction, and Grashof number) of an intermittent heat sink based on an improved structure is discussed. Visualization and temperature testing platforms are established. Through visualization experiments, the internal temperature and liquid fraction distribution of the heat sink are obtained, and the simulation results are in good agreement with the test results. The results show that the base temperature, liquid fraction, and Grashof number achieve a steady periodic variation during the intermittent process. Specifically, the base temperature remains stable in the range of 314 K to 340 K, the liquid fraction stabilizes between 0.8 and 1.0, and the Grashof number stabilizes between 100 and 1000. At the heating power of 30 W or below, the base temperature of the heat sink exhibits a steady periodic variation. At the heating power of 40 W, the maximum base temperature of the heat sink exceeds 370 K.

Visualisation Testing of the Vertex Angle of the Spray Formed by Injected Diesel–Ethanol Fuel Blends

The internal combustion engine continues to be the main source of power in various modes of transport and industrial machines. This is due to its numerous advantages, such as easy adaptability, high efficiency, reliability and low fuel consumption. Despite these beneficial qualities of internal combustion engines, growing concerns are related to their negative environmental impacts. As a result, environmental protection has become a major factor determining advancements in the automotive industry in recent years, with the search for alternative fuels being one of the priorities in research and development activities. Among these, fuels of plant origin, mainly alcohols, are attracting a lot of attention due to their high oxygen content (around 35%). These fuels differ from diesel oil, for instance, in kinematic viscosity and density, which can affect the formation of the fuel spray and, consequently, the proper functioning of the compression–ignition engine, as well as the performance and purity of the exhaust gases emitted into the environment. The process of spray formation in direct injection compression–ignition engines is extremely complicated and requires detailed analysis of the fast-changing variables. This explains the need for using complicated research equipment enabling visualisation tests and making it possible to gain a more accurate understanding of the processes that take place. The present article aims to present the methodology for alternative fuel visualisation tests. To achieve this purpose, sprays formed by diesel–ethanol blends were recorded. A visualisation chamber and a high-speed camera were used for this purpose. The acquired video provided the material for the analysis of the changes in the vertex angle of the spray formed by the fuel blends. The test was carried out under reproducible conditions in line with the test methodology. The shape of the fuel spray is impacted by an increase in the proportional content of ethanol in the diesel and dodecanol blend. Based on the present findings, it is possible to note that the values of the vertex angle in the spray produced by the diesel–ethanol blend with the addition of dodecanol are most similar to those produced by diesel oil at an injection pressure of 100 MPa. The proposed methodology enables an analysis of the injection process based on the spray macrostructure parameters, and it can be applied in the testing of alternative fuels.

A hybrid deep learning model for fault diagnosis of rolling bearings using raw vibration signals

Abstract The fault symptoms of rolling bearings are subject to various interferences in complex industrial environments, so achieving accurate, robust, and generalized fault diagnosis has become a key research direction. This article proposes a rolling bearing fault diagnosis method based on 1D-Inception-SE, which combines the 1D-Inception network model with Squeeze and Excitation Attention and can directly use the original vibration signals for fault diagnosis. The method incorporates the Adaptive Batch Normalization algorithm to enhance the model’s generalization performance in the presence of noise interference and cross-load diagnostics. Performance tests on Paderborn University Bearing and Case Western Reserve University datasets show that our approach achieves superior recognition accuracy compared to other models under similar and varied loads, as well as different signal to noise ratio. Ablation and visualization tests confirm the rationality and effectiveness of the model structure.

The effect of cognitive flexibility on students’ spatial visualization abilities and computational thinking skills in a three-dimensional design and coding training

ABSTRACT Aim and background Today, students are encouraged to develop spatial visualization ability to meet the challenges of digital technologies impacting their daily life and education when exposed more time to a virtual 3D environment. This study investigated the effect of cognitive flexibility levels on students’ spatial visualization abilities and computational thinking skills in three-dimensional design and coding training. In addition, this study examined the effect of the training on the spatial visualization abilities and computational thinking skills of the students. Method The study employed a one-group pre-test/post-test quasi-experimental design. A total of 60 university students (51 female and 9 male) participated in this study. University students received three-dimensional design and coding training by using Tinkercad. The Spatial Visualization Test, the Cognitive Flexibility Scale, the Computational Thinking Scale and semi-structured interview form were used to collect data. Paired samples t-test and one-way ANCOVA were used for the data analysis. Results and discussion Results from the training indicated that the students’ spatial visualization abilities improved. Their spatial visualization abilities and computational thinking skills were related to their cognitive flexibility levels. The training also improved the spatial visualization abilities and computational thinking skills of students with high cognitive flexibility. 3D design and coding education could be more effective for students with high cognitive flexibility. The qualitative findings supported the results of the study.

Performance and techno-economic evaluation of a high-efficiency electrospray cyclone

"Nowadays, because of the global air pollution issue caused by fine dust, fine dust collection and removal technologies are crucial for enhancing living environments and human health. This research proposes a new pilot-scale electrospray cyclone (ESC) designed for the collection of submicron dust particles. The experimental apparatuses comprised a cyclone dust collector and an insulating tank. Initially, laboratory-scale single-nozzle visualization tests were conducted to investigate the droplets’ number and size under various operating conditions. Subsequently, based on the visualization research outcomes, electrospray module was inserted to the industrial cyclone, which was designated by ESC. Performance assessments of the pilot-scale ESC were conducted under diverse water flowrates, applied voltages and nozzle sizes. The capture efficiencies for PM10, PM2.5, and PM1.0 were measured up to 98.2%, 95.4%, and 90.3%, respectively. Both the environmental and economic viabilities of the newly-proposed ESC in this study were evaluated based on three aspects: 1) capacitive particle collection efficiency; 2) capacitive installation cost; and 3) rated power and operational cost. This evaluation method has been defined as the Levelized Cost of Precipitator (LCOP), and it is intended to assess the environmental and economic performance of 5-convenstional dust collectors. In these results, the ESC shows relatively high performance in terms of the environmental and economic aspects. Based on these indices, we assess that the ESC has one of the promising alternatives of commercial precipitators."

Modern imaging of acute pulmonary embolism

The first-choice imaging test for visualization of thromboemboli in the pulmonary vasculature in patients with suspected acute pulmonary embolism (PE) is multidetector computed tomography pulmonary angiography (CTPA) – a readily available and widely used imaging technique. Through technological advancements over the past years, alternative imaging techniques for the diagnosis of PE have become available, whilst others are still under investigation. In particular, the evolution of artificial intelligence (AI) is expected to enable further innovation in diagnostic management of PE. In this narrative review, current CTPA techniques and the emerging technology photon-counting CT (PCCT), as well as other modern imaging techniques of acute PE are discussed, including CTPA with iodine maps based on subtraction or dual-energy acquisition, single-photon emission CT (SPECT), magnetic resonance angiography (MRA), and magnetic resonance direct thrombus imaging (MRDTI). Furthermore, potential applications of AI are discussed.

Detection of Campylobacter jejuni based on CRISPR/Cas12a with novel target yclQ obtained by pan-genome analysis

Campylobacter jejuni (C. jejuni) is one of the most common causes of bacterial gastrointestinal foodborne infections worldwide. Conventional detection methods based on bacterial culture are time-consuming, therefore, rapid detection methods are urgently needed to be developed. The objective of this study was to screen a novel species-specific target and to develop a rapid and accurate method for the detection of C. jejuni in food. Through pan-genome analysis of 298 Campylobacter whole-genome sequence data, a new species-specific target yclQ was screened. The yclQ gene was verified through PCR to be unique to C. jejuni. Subsequently, based on the target yclQ, we developed of a CRISPR/Cas12a-based platform for fluorescence visualization and nucleic acid test strips. The RAA-CRISPR/Cas12a system demonstrates the ability to detect C. jejuni at 1.8 CFU/mL within 50 min. Compared to PCR (1.8 × 101 CFU/mL), the RAA and RAA-CRISPR/Cas12a assay showed higher sensitivity. The detection results of the actual samples were consistent with those of the isolation and culture procedures. In conclusion, the RAA-CRISPR/Cas12a system, based on the target yclQ, demonstrates significant potential for the rapid and accurate detection of C. jejuni in food.

Use Of Natural Dyes From Plants In Coloring Woven Yarns

The use of natural dyes as an environmentally friendly alternative to reduce the use of synthetic dyes which have a negative impact on the environment. Natural dyes can be obtained from various natural sources such as plants, animal waste, and minerals, with plants being the most common source. Plant pigments such as anthocyanins, tannins, flavonoids, and chlorophyll provide a variety of colors that can be used for coloring. The natural dyeing process involves four stages: making the dye solution, fabric preparation, dyeing, and fixation. Testing the quality of natural dyes includes color visualization tests, color aging, color differences and fastness to washing. The methodology for writing this article is a literature study, reviewing various related research from 2013 to 2023. The results show that several plants such as Tarum, Coconut, Secang, Noni, Turmeric, and Shallots can produce colors such as dark blue, brownish cream, red , yellow, and brownish orange on fabric. In conclusion, natural dyes not only support environmental sustainability but also offer a safe and low-cost coloring alternative, although there are challenges in the manufacturing and application process of these natural dyes.