Model Tests Research Articles

Managing deepsea oil spills through a systematic modeling approach

Offshore oil exploration and production in deepwater are associated with environmental risks to marine ecosystems. This research introduces DWOSM (Deep Water Oil Spill Model), a three-dimensional Lagrangian model, which is developed to simulate the transport and fate of oil spills resulting from subsea blowouts. DWOSM comprises three interconnected modules: DWOSM-DSD, which predicts the oil droplet size distribution from a blowout release; DWOSM-NearField, simulating plume dynamics and tracking oil droplets within the plume region; and DWOSM-FarField, modeling the evolution of dispersed oil beyond the near-field. Compared to other oil spill models, this integrated approach improves the transition between near and far fields using a near-field particle tracking algorithm. It also employs the thermodynamic models to enable the prediction of oil properties under varying deep water pressure and temperature. To gauge the reliability and efficacy of DWOSM, a hypothetical case situated within a North American context is employed for model testing. The DWOSM and its each module are juxtaposed with other established oil spill models. The outcomes indicate that DWOSM yields comparable results to these models by providing reasonable predictions of a deepwater blowout. The model's verification through case scenario testing and comparison underscores its potential as a decision tool for assessing and managing the potential environmental impacts of offshore petroleum activities.

Coupled surface-internal deformation monitoring in three-dimensional space for freezing-thawing soil

Soil frost deformation significantly influences engineering projects in cold regions. The anisotropic behavior of soil, involving surface and internal deformation in three dimensions (3D), introduces inaccuracies in evaluating freeze–thaw geological hazards. To explore the relationship between internal strain and surface displacement of soil in a 3D space during the freezing-thawing process, a platform for monitoring coupled surface-internal deformation in 3D were developed using binocular recognition technology and a novel 3D strain rosette. Subsequently, a freezing-thawing model test of soil in Dalian Offshore Airport filling is conducted using the platform. The results show that, the internal strain of soil is closely associated with the boundary conditions of the test unit. During freezing test, the vertical strain exhibits a more significant increase in comparison to the horizontal strain. Surface displacements in soil primarily occur during the initial freezing and thawing stages. The variation of surface horizontal displacement in each direction is minimal throughout the freezing-thawing process. A surface freezing boundary leads to an increment in internal strain, while the deep frozen stress relief causes the soil surface expand during thawing. This study provides a suggestion for the control of the cold source in cold region engineering.

Fortifying Network Security: Pioneering Hybrid Machine Learning for BotNet Attack Detection

Abstract: With the rising sophistication of cyber threats, the detection of BotNet attacks on networks has become a perilous contest for cybersecurity. This paper proposes an innovative approach leveraging a hybrid machine learning (ML) framework for the detection of BotNet attacks in network atmosphere conquers a notable accuracy of 98.63%. By amalgamation of different strengths of ML algorithms such as KNN and Decision Trees, our approach aims to enhance the accuracy and efficiency of BotNet detection. The methodology comprises feature extraction from network traffic data, followed by training and testing of the hybrid model on labelled datasets to identify patterns revealing of BotNet activity. Experimental outcomes reveal the effectiveness of the proposed approach in precisely detecting BotNet attacks while diminishing false positives. The hybrid ML approach offers a forthcoming avenue for fortifying network security and mitigating the risks associated with BotNet threats.

Global Weight Optimization on Artificial Neural Network for Optimizing Crop Yield Prediction Using Genetic Algorithm

Abstract: Accurate crop yield prediction is a complex and intricate task that encompasses a multitude of factors and variables, rendering it arduous to establish a dependable mathematical model. Conventional machine learning (ML) models for crop yield prediction have surpassed their efficacy. This research endeavour sought to enhance crop yield prediction accuracy by hybridizing a neuro-genetic model utilizing statistical data amassed over a 35-year period from various pertinent agricultural departments in Tamil Nadu, India, including the Statistical, Agricultural, and Meteorological Departments. This research delved into analyzing and identifying the optimal weight configuration for the artificial neural network (ANN) to bolster accuracy with the assistance of genetic algorithms (GA). Seventy-five percent of the data was employed to train the model, while the remaining 25% was utilized for model testing. To gauge the performance of this research work, 5-fold cross-validation was implemented. RMSE, MAE, and Adj R2 were employed to evaluate the performance and contrast the performance of the neuro-genetic model with the conventional ANN. The neuro-genetic model exhibited superior accuracy compared to the conventional ANN.

Study on the critical stable height of vertical excavation in rocky foundation pit within layered structural plane

The structural plane characteristic was the most critical factor for determining the self-stability ability of deep foundation pit vertical-rock-wall in layered rock stratum. Multiple methods such as model testing, numerical calculation, and theoretical calculation were utilized comprehensively in this paper. The self-stabilizing control effect on the deep foundation pits vertical-rock-wall that under the different structural plane inclination angle (α) and under the different structural plane strength was systematically studied. The results indicated that the overall variation trend of "Sharp decrease ~ Slow decrease ~ Slow increase ~ Sharp increase" in the symmetrical distribution for the self-stability critical height (Hcr) varied with the gradually increasing of α was presented. Meanwhile, the variation trend of "continuously decreasing and rapidly decreasing first, and then slowly decreasing and tending to stabilize" with the structural plane strength reduction coefficient (k). The key factor to control the self-stability of the deep foundation pit vertical-rock-walls lied in fully grasping and utilizing the basic characteristics of rock structural planes. The research results of this paper provided the theoretical basis for scientifically determining the safety level and designing reasonable support structures of the deep foundation pit vertical-rock-walls in layered rock stratum.

Practical Evaluation of Ionic Liquids for Application as Lubricants in Cleanrooms and under Vacuum Conditions

As part of a publicly funded cooperation project, novel high-performance lubricants (oils, greases, assembly pastes) based on ionic liquids and with the addition of specific micro- or nanoparticles are to be developed, which are adapted in their formulation for use in applications where their negligible vapor pressure plays an important role. These lubricants are urgently needed for applications in cleanrooms and high vacuum (e.g., pharmaceuticals, aerospace, chip manufacturing), especially when the frequently used perfluoropolyethers (PFPE) are no longer available due to a potential restriction of per- and polyfluoroalkyl substances (PFAS) due to European chemical legislation. Until now, there has been a lack of suitable laboratory testing technology to develop such innovative lubricants for extreme niche applications economically. There is a large gap in the tribological test chain between model testing, for example in the so-called spiral orbit tribometer (SOT) or ball-on-disk test in a high-frequency, linear-oscillation test machine (SRV-Tribometer from German “Schwing-Reib-Verschleiß-Tribometer”), and overall component testing at major space agencies (ESA—European Space Agency, NASA—National Aeronautics and Space Administration) or their service providers like the European Space Tribology Laboratory (ESTL) in Manchester. A further aim of the project was therefore to develop an application-orientated and economical testing methodology and testing technology for the scientifically precise evaluation and verifiability of the effect of ionic liquids on tribological systems in cleanrooms and under high vacuum conditions. The newly developed test rig is the focus of this publication. It forms the basis for all further investigations.

Design and simulation implementation of bismuth-doped fiber laser

Rare-earth doped fibers are an important means of expanding the wavelength band of optical fibers. Currently, researchers aim to broaden the working wavelength band of optical fibers by doping with different rare-earth elements, thereby increasing the amount of information that can be transmitted. In this paper, a bismuth-doped fiber laser operating around 1300nm was designed. A basic physical model for implementing a bismuth-doped fiber laser was proposed based on the energy levels and transition processes of bismuth, rate, and power propagation equations. It was possible to determine the link between pump power and laser power at a wavelength of 1300 nm by modeling tests using the physical model. Additionally, the relationship between pump light and laser power in bismuth-doped fiber at different positions and propagation directions was analyzed. Suggestions for the future large-scale application of bismuth-doped fiber lasers around the 1300nm wavelength band were provided.

Constitutive Characteristics of Rock Damage under Freeze–Thaw Cycles

Freeze–thaw effect is one of the most important environmental conditions that rocks may be subjected to. Through laboratory model tests, the damage characteristics of rocks under the FTC were studied. Based on assuming that the strength of rocks subject to the FTC follows the Weibull distribution, the cumulative damage variable of the number of FTCs was introduced. A cumulative damage constitutive model of shear strength attenuation of rock that meets the Mohr–Coulomb criterion is established. The rationality and applicability of the proposed damage constitutive model are verified by comparing the results of rock shear strength parameters under cyclic freeze–thaw loads.

Relationships Between Theme Park Ride Experience and Loyalty: The Moderating Role of Past Experience

ABSTRACT Understanding the relationship between theme park ride experiences and visitor loyalty is crucial yet still not fully elucidated, particularly regarding differences between first-time and repeat visitors. Drawing upon the experience economy framework and the theory of experienced utility, this study explores how various aspects of theme park ride experience (education, aesthetics, entertainment, and escapism) influence visitor loyalty (revisit and recommendation intentions), considering the moderating effect of past experience. Structural equation modeling and invariance tests were conducted on data collected from 412 theme park visitors in China. Results indicate that the four dimensions of theme park ride experience have varying impacts on patrons’ revisit and recommendation intentions. Additionally, first-time visitors’ intentions are more influenced by active participation experiences compared to repeat visitors. This study advances the theoretical knowledge of theme park ride experience and offers practical implications for park management.

Intelligent prediction of wave loads based on multi-source data-driven methods

ABSTRACT High-fidelity wave-load tests is pivotal in the design and development of modern ship structures. Nonetheless, the prohibitive cost of conducting such tests limits their applicability. A wave-load data fusion method was implemented using the model test data from a typical displacement-type ship to generalise the small sample test, and a multi-source data characterisation and model parameter optimisation method were established to achieve efficient wave-load (wave frequency and slamming superposition) prediction. Using multi-source data, a multi-fidelity wave-load prediction (MFWLP) model was constructed by combining numerical computation, regular wave tests (RWT), and irregular wave test (IWT) data based on transfer learning with a secondary correction wave load prediction under irregular wave conditions. The model was effectively employed in a ship wave-load engineering case. This study reveals that the adopted MFWLP model demonstrates adequate extrapolation and prediction capabilities, even with limited high-fidelity test samples. The discrepancy between the nonlinear wave load prediction and model test was found to be within 15%. Therefore, the proposed method can serve as a foundation for rapidly assessing ship wave loads across various sea conditions, especially under high sea states.

Experimental analysis of self-propelled characteristics with uncertainty analysis of ONR tumblehome hull

In this paper, the self-propelled characteristics of the benchmark ONRT hull were studied experimentally at both Froude numbers, Fr = 0.20 and Fr = 0.30. The assessments were conducted under free-running conditions using a fully appended Office of Naval Research Tumblehome (ONRT), model 5613, scaled at 48.9, a customary proportion in academic research. To demonstrate the reliability of self-propulsion experiments conducted at the Istanbul Technical University, Ata Nutku Ship Model Testing Laboratory (ITU-AN), an uncertainty analysis method was applied to the ONRT results. The self-propulsion points from the studies in literature at both Fr = 0.20 and Fr = 0.30, were compared with the present test results. Based on the analysis results at self-propulsion points, it was noted that there was a high level of both intra-laboratory repeatability and inter-laboratory reproducibility characteristics. Through repeated tests, it was discerned that the uncertainties impacting essential parameters were, in descending magnitude, thrust, torque, and rotational rate. Consequently, this investigation enhances the precision and reliability of results by presenting the thrust and torque characteristics of the ONRT hull form, along with associated uncertainties for these Fr numbers.

Efficacy Testing of the Comprehensive Institutional Model (CIM) using Design-based Research: Instrumental Case Study

COVID-19 was a “black swan” event that forever altered higher education’s adult teaching and learning landscape by requiring a pathway shift in institutional resources to meet student and faculty support needs for academic success and institutional sustainability. Over the last two years, thousands of scholarly articles have been published about the challenges that higher education institutions (HEIs) faced during COVID-19 and their lasting impact on student learning, faculty engagement, and institutional operations in the post-COVID environment. Many researchers offer strategies and guidance to help address the challenges; however, research is limited to testing these strategies and proposed models designed to mitigate the challenges and manage such a crisis in the future. The proposed study will help close this gap by assessing the efficacy of the Comprehensive Institutional Model (CIM), developed based on the findings of Perceptions of Online Strategies and Digital Readiness in the COVID-19 Environment: An Instrumental Case Study by McCray et al. [19]. The CIM aims to provide HEIs with a model to support Hy-flex learning environments to ensure readiness for new emergencies and the aftermath of a “new normal” in higher education. The model organizes how aligning administrators, faculty, and graduate students impacts effective Hy-flex teaching and learning environments. Design-Based Research (DBR) will be used to systematically collect and analyze evidence-based testing results of the CIM across three iterations.

Motion and mooring load responses of a novel 12 MW semi-submersible floating wind turbine: An experimental study

Abstract Due to the complexity of the integrated Floating Wind Turbine (FWT) system, obtaining reliable results necessitates extensive experiments. This paper conducts a comprehensive study on the motion performance and mooring load responses of a novel 12 MW semi-submersible FWT through model tests carried out in a wave basin. A multi-blade large-scale wind generation system, equipped with a rectifier network, was enhanced and constructed to provide a dependable wind field. And a flexible tower was designed and fabricated, achieving an accurate simulation of the tower's stiffness characteristic and its impact on the overall dynamic response. The marine environmental conditions encompass various combinations of wind, waves, and currents. Rigorous calibration and identification tests were undertaken to validate the environmental conditions and the model system. The findings reveal that, under mild wave parameters, the mooring load is primarily influenced by the resonance response with platform motions, particularly surge resonance. The load effect of wind and current induces mean surge and pitch motions, while their damping effect reduces the standard deviation of responses, notably suppressing the pitch response peak at its natural motion frequency. Wave loads predominantly dictate the vibration range of motion responses. When the current velocity reaches a sufficient magnitude, the coupling effect between current and wave in the wave-frequency region significantly amplifies the mooring response. Notably, motions and mooring loads in the 60° and 90° directions surpass those in the 0° direction, with the maximum responses occurring at 60°.

Waveform inversion with structural regularizing constraint based on gradient decomposition

Abstract Full waveform inversion (FWI) can simultaneously update low-to-medium wavenumber velocity components and high-wavenumber velocity components. However, if seismic data lack large-offset data and effective low-frequency components, FWI updates will be dominated by high-wavenumber velocity perturbation. Meanwhile, providing that the initial model is inaccurate, inversion will have the problem of local minima. In this study, FWI is developed with structural regularizing constraint based on gradient decomposition (RGDFWI). By correlating the separated forward wavefield and backward wavefield with specific propagating direction, FWI gradient is decomposed into tomography-mode gradient and migration-mode gradient. We propose an optimized strategy taking full advantage of the two modes of FWI gradient. On the one hand, we use tomography-mode gradient to enhance low-to-medium wavenumber updates. On the other hand, we use migration-mode gradient to apply structural regularizing constraint by estimating structure dip and adding sparsity constraint in Seislet domain. During the inversion process, high-wavenumber structural information constrains and guides low-wavenumber model updates. The results of two numerical tests, Marmousi model test and Overthrust model test, validate the optimized strategy, which can produce a better initial velocity model for FWI. The inversion finally generates a high-precision and high-resolution velocity model.

Mechanical Characteristics of Cracked Lining Reinforced with Steel Plate–UHPC Subjected to Vertical Load

The steel plate reinforcement method is widely used for strengthening damaged linings. Nevertheless, low durability is one of the disadvantages of the steel plate reinforcement method, which uses epoxy resin as the interface binder. To enhance the load-bearing performance and strengthening effect of steel-plate-reinforced structures, this study introduced ultra-high performance concrete (UHPC) as the reinforcing bonding layer and proposed a novel method for steel plate–UHPC reinforcement of cracked linings. A mechanical performance model test was conducted on a 1/5 scale lining model using a loading test device to evaluate the load-bearing performance and stress deformation of both conventional steel plate and steel plate–UHPC reinforced cracked linings. The characteristics, mechanisms of failure, and impacts of strengthening of the steel plate reinforcement method and steel plate–UHPC reinforcement method for cracked linings were compared. A numerical simulation model was developed to investigate the reinforcement effect of cracked linings using steel plate–UHPC reinforcement. The analysis included examining the influence of steel plate thickness, UHPC bonding layer thickness, and reinforcement timing. Model test results show that the overall damage mode of the steel plate–UHPC-reinforced structure had good elastic–plastic behaviour, and the deformation and damage process under the vertical concentrated load can be divided into four typical phases. Compared with the traditional steel plate reinforcement, the ultimate load-carrying capacity and ductility of the steel plate–UHPC-reinforced structure were increased by 53% and 366%, respectively, showing significantly better load-carrying capacity and deformation performance. Numerical simulation results show that the reinforced structure’s load-carrying capacity and stiffness enhancement rate increased non-linearly with the increase in UHPC layer thickness and steel plate thickness. However, reasonable reinforcement timing exists for steel plate-UHPC reinforcement, and too late reinforcement timing leads to a decrease in structural load-carrying capacity and stiffness enhancement rate.

Research on Road Pattern Recognition of a Vision-Guided Robot Based on Improved-YOLOv8

In order to promote the accurate recognition and application of visual navigation robots to the environment, this paper carried out research on the road pattern recognition of a vision-guided robot based on improved YOLOv8 on the basis of road pattern calibration and experimental sampling. First, an experimental system for road image shooting was built independently, and 21 different kinds of road pattern image data were obtained by sampling roads with different weather conditions, road materials, and degrees of damage. Second, the road pattern recognition model based on the classical neural network Resnet 18 was constructed for model training and testing, and the initial recognition of road pattern was realized. Third, the YOLOv8 target detection model was introduced to build the road pattern recognition model based on YOLOv8n, and the model was trained and tested, improving road pattern recognition accuracy and recognition response speed by 3.1% and 200%, respectively. Finally, to further improve the accuracy of road pattern recognition, improvement research was carried out on the YOLOv8n road pattern recognition model based on the C2f-ODConv module, the AWD adaptive weight downsampling module, the EMA attention mechanism, and the collaboration of the three modules. Three network architectures, classical CNN (Resnet 18), YOLOv8n, and improved YOLOv8n, were compared. The results show that four different optimization models can further improve the accuracy of road pattern recognition, among which the accuracy of the improved YOLO v8 road pattern recognition model based on multimodule cooperation is the highest, reaching more than 93%.

#2462 Impact of tacrolimus peak concentration on kidney graft outcomes

Abstract Background and Aims Low tacrolimus (Tac) trough concentration-to-dose ratio (C0/D ratio) identifies kidney transplant patients with high level of Tac metabolization and has been shown to be associated with lower graft function and survival. Why fast metabolizers experience poorer outcomes is however unclear. We hypothesized that fast metabolization is associated with higher maximal Tac blood concentration (Cmax) and that Tac Cmax has a detrimental effect by itself. Method We retrospectively selected consecutive kidney transplant patients who (I) were treated by Tac (irrespective of the pharmaceutical formulation), (ii) had systematic abbreviated pharmacokinetic tac evaluation at 3- and 12-months’ post-transplant, and (iii) had a minimal follow-up of 5 years. Fast metabolizers were defined by a C0/D ratio <1.05. Cmax was defined by the higher value of Tac concentration observed at 30, 90 or 180 minutes after Tac morning ingestion and was indexed to C0 in order to exclusively focus on patients with no obvious Tac overexposure. Association between Tac Cmax/C0 with traditional transplant outcomes was analysed by univariate and multivariate cox model and logrank test when appropriate. Results 436 patients transplanted from 2008 to 2016 (64% of male, mean age of 55 ± 13 y) with a median follow-up of 8 years (Q1: 6; Q3: 11) were analysed. Fast metabolizers had lower C0 while receiving higher dose of Tac and displayed significantly higher median Cmax (20 vs 17 μg/l, p < 0.001). Median Cmax/C0 was 3 and 2 in fast and non-fast metabolizers, respectively (p < 0.001). At 15 years’ post-transplant, death-censored graft survival was 13% lower for patients with the highest Cmax/C0 values (p = 0.04). In multivariate cox analysis, higher Cmax/C0 was independently associated with death-censored graft survival (HR = 1.30 (1.03;1.64), p = 0.026). Conclusion Our data support the hypotheses 1—that fast metabolizers exhibit higher Tac Cmax even in situations where Tac C0 are not elevated and 2—that exposure to high Cmax is a potential mechanism underlying their poorer outcome. Tac formulations prone to mitigate pharmacokinetic peak could thus be particularly beneficial to fast metabolizers and should be thoroughly evaluated in this indication.

OLE! Dairy model

The process of intensification of the dairy sector has been characterized in recent decades by the increase in milk production per hectare, the increase in livestock density, the inclusion of more concentrates in the diet, and the improvement of the genetic merit of dairy cows. The use of models has productive, environmental, and economic advantages. The objectives of the study were to describe a new model, “OLE! Dairy model”, to (a) simulate the biophysical performance of a pasture-based dairy production system; (b) evaluate the predictive capacity of the model with a set of statistical parameters, comparing its results with the biophysical performance of experimental studies of dairy farm systems, and (c) calibrate by adjusting the technical coefficient. The experimental design combines two feeding strategies with a different proportion of pasture in the diet and two animal genotypes. We make a description of the biophysical component and the calculations proposed in the “OLE! Dairy model”. Then a variety of parameters was calculated for model testing, including the Mean Squared Error, the Relative Prediction Error, the square root of the MSE, the Concordance Correlation Coefficient, and the Model Efficiency. The model presented a good predictive capacity for stocking rate and concentrate, pasture, and reserve intake. The predictive capacity of the model for individual production and area production improves after performing a rapid calibration, which allows for avoiding overestimations or underestimations that generate erroneous measurements in the planning and management of milk production systems, and can be adjusted to different conditions of production of the region.

The effect of bedding thickness on interlocking block pavement performance

ABSTRACT An interlocking block pavement (IBP) comprises discrete blocks, joints, bedding sand, and base and subbase layers. The thickness of the bedding sand layer gives significant impact on IBP performance. However, previous laboratory model tests have often overlooked the geotechnical properties of paving materials and the deformation characteristics of the sublayers, leading to conflicting recommendations regarding appropriate thickness. This study performed laboratory tests on IBP models with varying bedding thicknesses (30, 50, and 80 mm), considering the geotechnical properties (relative density, shear strength, and stress–strain behaviour) of the paving materials. In addition, a novel two-dimensional (2D) model chamber with a transparent wall was designed for particle image velocimetry (PIV) analysis to assess the overall deformation of the sublayers. The test results demonstrated that a bedding thickness of 50 mm exhibited higher load-dispersion ability, allowing the blocks to settle and rotate appropriately and achieving a full interlocking effect. Consequently, the deflection in the sublayer was distributed over a wide area at shallow depths. However, a bedding thickness of 30 mm provided a better performance in terms of resistance to deflection, imposing a higher stress on the base layer.

Active failure mechanisms and earth pressure of narrow backfill behind retaining structures

Through a series of model tests accomplished by particle image velocimetry analyses, this study presents the visualisation of the displacement field of narrow soil behind retaining structures under translational mode. The progressive development of failure mechanisms and active earth pressure are measured in the process of tests. Finite-element limit analyses are additionally carried out to investigate and verify the ultimate failure mechanism and active earth pressure acting on retaining structures. Furthermore, this study carried out analyses on the development of failure mechanisms and active earth pressure with different aspect ratios, inclinations of the existing structure and backfill surface surcharge. A reasonable agreement was observed between experimental and numerical results. With an increase in backfill spacing, the failure mechanism of backfill turns from reflective shear bands into a single shear band, and the earth pressure exerted on the retaining structure increases.