Experiment Data Research Articles

Fluid-to-fluid similarity and CFD predictions of surrogate fluid as a replacement for R11 refrigerant used in a subcooled flow boiling analysis: Validation against reference experimental data

In this study, we present the possibility of substituting the primary fluid Freon 11 (CCl3F, R11) used in the experimental thermohydraulic test facility which offers the advantage to obtain phase change at relatively low heat fluxes and pressure if compared to water working fluid. Nevertheless, R11 is a CFC (Chlorofluorocarbures) part of the gases that contribute to the degradation of the ozone layer.For this purpose, four working fluids (non-CFC) are judiciously selected to replace the R11, namely the R123, R134a, R143a and CO2, and this through multidimensional Computational Fluid Dynamics (CFD) modeling of steady state flow boiling phenomenon. The calculation model covers a wide range of mass fluxes (435 – 1443 kg/m2s) and heat fluxes (1.2– 36 W/cm2); it predicts the heat transfer rates and transitions points for each flow regime. In this research, the experiment's data were compared to the outcomes of Ansys-CFX computations, using a steady Reynolds-Averaged Navier-Stokes (Steady-RANS) model, to investigate the best replacement refrigerant for R11. The turbulence effects on the mean flow and near wall are taken into consideration using the Shear Stress Transport (SST k-ω) turbulence model. The results from the four fluids were transposed to their water equivalent and compared to those deduced from the experimentation and correlations available in the literature to select the appropriate substitution fluid. The results qualitative and quantitative for vertical and horizontal subcooled boiling flow at the CHF location show that, the most effective surrogate fluid is R123 (HCFC), is still widely used in the refrigeration and air-conditioning industry, then R134a (HFC), then R143a (HFC).

Lightweight AC Arc Fault Detection Method by Integration of Event-Based Load Classification

As the main cause of electrical fires, arc fault detection attracts lots of attention in recent years. However, with the growing complexity of electric loads, arc fault detection becomes more difficult. This paper proposes a lightweight arc fault detection method that integrates load classification into fault detection. Firstly, according to the turn-on patterns, we divide loads into resistive, inductive and switchable loads. Load classification is developed using an event-based method. Then, arc detection method is developed for each load category, which is achieved through sequential forward floating selection. Its performance is validated by the experiment data and comparison with other reported methods. Meanwhile, the selection of classifiers, sampling rate, and sampling periods for arc fault detection are also discussed in detail. The results show that the proposed method not only achieves a high fault detection performance but also keeps a relatively low sampling rate and short sampling period. Thus, it is beneficial for practical arc fault interrupter development.

Physiological arousal underlies preferential access to visual awareness of fear-conditioned (and possibly disgust-conditioned) stimuli.

Fear and disgust have been associated with opposite influences on visual processing, even though both constitute negative emotions that motivate avoidance behavior and entail increased arousal. In the current study, we hypothesized that (a) homeostatic relevance modulates early stages of visual processing, (b) through widespread physiological responses, and that (c) the direction of these modulations depends on whether an emotion calls for immediate regulatory behavior or not. Specifically, we expected that increased arousal should facilitate the detection of fear-related stimuli, and inhibit the detection of disgust-related stimuli. These hypotheses were tested in two preregistered experiments (data collected in 2022, total N = 120, ethnically homogeneous Polish sample). Using a novel, response bias-free version of the breaking continuous flash suppression paradigm, we examined localization and discrimination of fear- and disgust-conditioned stimuli at individually determined perceptual thresholds. Our first hypothesis was confirmed: fear-conditioned stimuli were detected and discriminated better than neutral stimuli, and the magnitude of conditioning-related perceptual preference was related to arousal during conditioning acquisition. In contrast with our second hypothesis, perceptual access to disgust-conditioned stimuli was not diminished. Exploratory analyses suggest that discrimination of disgust-conditioned stimuli was also enhanced, although these effects appeared weaker than those evoked by fear conditioning. The current study strengthens previous evidence for facilitated perception of threatening objects and shows for the first time that stimuli evoking disgust might also gain preferential access to awareness. The results imply that homeostatically relevant stimuli are prioritized by the visual system and that this preference is grounded in the underlying arousal levels. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Pyrolysis process control: temperature control design and application for optimum process operation

Fast pyrolysis in auger reactor gains attention for efficient bio-oil production. Due to the quick nature of the process, precise temperature control using the proportional-integral-derivative (PID) algorithm is paramount. This study harnesses various PID tuning approaches through modelling and experimental validation to optimize continuous and precise pyrolysis temperature. System identification was done to investigate the process dynamic with fit accuracy above 93% and design a suitable PID control. Comparison with the experiment data shows a favorable result with rise time and settling time match above 75%. Ziegler-Nichols (ZN) and Cohen-Coon (CC) tuning methods were implemented in the system with undistinguished results, yielding steady-state error (SSE) below 1% and settling time around 4,300 to 4,800 seconds. The heuristic fine-tuning method improved the rise time and settling time by stabilizing before 3,600 seconds. Furthermore, the robustness of PID controllers was verified with a disturbance rejection test, keeping the SSE deviation inside the boundary of 2%. Finally, the setup could support maximum pyrolytic oil production by 69.6% at 500 °C. The result implies that the PID controller could provide a stable and rugged response to support a productive and sustainable pyrolysis plant operation.

The research on the effect of temperature of electro-surgical unit to surgical smoke distribution in theatre-in vitro and simulation study.

In electro-surgery, surgical smoke was hazard to surgeons and patient in theatre. In order to institute effective countermeasures, quantifying of the effect of tip temperature of electro-surgical unit to surgical smoke distribution in theatre was studied. The relation of tip temperature to power of electro-surgical unit through in vitro cutting experiment. Based on experiment data, the mathematical model was established to simulate the electro-surgery in laminar operation room. As the power of electro-surgical knife increased, the knife tip temperature increased. Total content of (CO, CO2, CH4, NH3) in waste gas and net flow rate of waste gas at outlet increased with the rising temperature of knife tip and formation rate of condensed tar droplets and non-viable particles also increased. Based on simulation, it was found that The maximum height of surgical smoke rising right above the incision of electro-surgical unit was increased with rising temperature of electro-surgical knife tip. There was a spread route of dispersed surgical smoke near the walls of theatre through natural convection. The polynomial fitting relationship was derived. As the tip temperature of knife increased from 200 to 500°C, maximum ascending height of surgical smoke right above the incision position of electro-surgical unit increased from 1.1 m to 1.45 m. When the tip temperature of electro-knife was more 400°C, the CO content in the surgeon's operating zone was more than 200 ppm, which would cause the surgeon's HbCO level increased. As the patient's tissue in the wound during operation was open, when the electro-knife of more than 400°C, the content of condensed tar droplets and in-viable particle was higher than 20 g/m3 and 12 g/m3 in the zone around patient's wound of open tissue, which should be hazard to health of patient.

Life tables in entomology: A discussion on tables' parameters and the importance of raw data.

Life tables are one of the most common tools to describe the biology of insect species and their response to environmental conditions. Although the benefits of life tables are beyond question, we raise some doubts about the completeness of the information reported in life tables. To substantiate these doubts, we consider a case study (Corcyra cephalonica) for which the raw dataset is available. The data suggest that the Gaussian approximation of the development times which is implied by the average and standard error usually reported in life tables does not describe reliably the actual distribution of the data which can be misleading and hide interesting biological aspects. Furthermore, it can be risky when life table data are used to build models to predict the demographic changes of the population. The present study highlights this aspect by comparing the impulse response generated by the raw data and by its Gaussian approximation based on the mean and the standard error. The conclusions of this paper highlight: i) the importance of adding more information to life tables and, ii) the role of raw data to ensure the completeness of this kind of studies. Given the importance of raw data, we also point out the need for further developments of a standard in the community for sharing and analysing data of life tables experiments.

Check dam impact on sediment loads: example of the Guerbe River in the Swiss Alps – a catchment scale experiment

Abstract. The construction of check dams is a common practice around the world where the aim is to reduce the damage by flooding events through mountain streams. However, quantifying the effectiveness of such engineering structures has remained very challenging and requires well-selected case studies, since the outcome of such an evaluation depends on site-specific geometric, geologic and climatic conditions. Conventionally, the check dams' effectiveness has been estimated using information about how the bedload sediment flux in the stream changes after the check dams are constructed. A permanent lowering of the bedload flux not only points to a success in reducing the probability of sediment transport occurrence but also implies that the sediment input through the system is likely to decrease. Here, we applied a method for data acquisition and two different equations (Meyer-Peter–Müller and Recking approach) to estimate and compare the sediment transport in a mountain stream in Switzerland under engineered and non-engineered conditions. Whereas the first equation is derived from a classical approach that is based on flume experiment data with a slope of less than 0.02 m m−1, the second equation (Recking) has been derived based on a bedload field dataset comprising active mountain streams under steeper conditions. We selected the Guerbe (Gürbe) River situated in the Swiss Alps as a case study, which has been engineered since the end of the 19th century. This has resulted in more than 110 check dams along a ca. 5 km reach where sediment has continuously been supplied from adjacent hillslopes, primarily by landsliding. We measured the riverbed grain size, topographic gradients and river widths within selected segments along this reach. Additionally, a gauging station downstream of the reach engineered with check dams yielded information to calibrate the hydroclimatic situation for the study reach, thus offering ideal conditions for our catchment-scale experiment. Using the acquired data and the dataset about historical runoff covering the time interval between 2009 and 2021 and considering the current engineered conditions, we estimated a mean annual volume of transported bedload which ranges from 900 to 6000 m3 yr−1. We then envisaged possible channel geometries before the check dams were constructed. We inferred (1) higher energy gradients which we averaged over the length of several check dams and which we considered a proxy for the steeper river slope under natural conditions; (2) channel widths that are smaller than those measured today, thereby anticipating that the channel was more confined in the past; and (3) larger grain size percentiles, which we consider to be similar to the values measured from preserved landslides in the region. Using such potential non-engineered scenarios as constraints, the two equations both point towards a larger sediment flux compared to the engineered state, although the results of these equations differed significantly in magnitude. Whereas the Recking approach returned estimates where the bedload sediment flux is ca. 10 times larger in comparison with the current situation, the use of the Meyer-Peter–Müller equation predicts an increase of ca. 100 times in bedload fluxes for a state without check dams. These results suggest that the check dams in the Guerbe River are highly efficient not only in regulating sediment transport by decreasing the probability of high sediment flux occurrence during torrential conditions but also in stabilizing the channel bed by avoiding incision. The most likely consequence is a stabilization of the terrain around such structures by reducing the activation of landslides.

Sociolinguistic Insights from Free Associative Experiment Data

This study delves into the intricate relationship between language, cognition, and society by employing a multidimensional approach. It combines free associative experiments and sociolinguistic analysis to offer a nuanced perspective on concept configuration. By focusing on the intersection of sociolinguistics and psycholinguistics, the research explores how sociocultural factors influence the way individuals associate concepts, exemplified through the study of “Altruism” in English native speakers. The findings underscore the significant impact of variables like age and gender on the concept configuration, revealing the fact that social variables shape linguistic consciousness. This integration of methodologies provides a comprehensive understanding of the concept configuration, emphasizing the need for a multidimensional approach in the study of language intricacies. In summary, this article highlights the importance of merging free associative experiments and sociolinguistic analysis to unravel the influence of social factors on concept associations. It contributes valuable insights into the dynamic nature of language, cognition, and society while emphasizing the relevance of age and gender variables in such investigations. This research lays a foundation for further exploration in the fields of sociolinguistics and psycholinguistics.

Data Acquiring System for Gas Turbine Engine’s Dynamic Performance; Build and Validate

ABSTRACT Gas Turbine Engines (GTE) have the highest power-to-weight ratio among Internal Combustion Engines (ICE). Its modularity and ability to utilize various types of fuel make it highly recommended in power plants, naval transportation, and, of course, the most equipped in aviation. The lack of GTEs’ real data is increasing a recognized need for collecting informative real data sets from GTEs for modeling, monitoring, and fault diagnosis and isolation (FDI). In the present article, a robust versatile data acquisition measuring system has been built to collect real-time data from an axial turboshaft GTE. The system facilitates connectivity and integrity by means of two wiring harnesses connecting the data acquisition card (DAQ), the engine’s control unit, and the operator’s control console. Mobility is guaranteed using a wireless connection between DAQ and a customized programmable LabVIEW interface application. Many experiments have been conducted in different operating conditions to collect the engine and controller’s data in different regimes. The measured signals have been filtered using software-implemented filters and transformed into the right measurement quantities. The experiment data have been analyzed for different regimes, and the milestone documented readings were compared with the measured ones to validate the accuracy and precision of the measuring system. The system is valid for collecting informative data sets that are usable for modeling the engine’s dynamic performance and fault detection.

SpatialView: an interactive web application for visualization of multiple samples in spatial transcriptomics experiments.

Spatial transcriptomics (ST) experiments provide spatially localized measurements of genome-wide gene expression allowing for an unprecedented opportunity to investigate cellular heterogeneity and organization within a tissue. Statistical and computational frameworks exist that implement robust methods for pre-processing and analyzing data in ST experiments. However, the lack of an interactive suite of tools for visualizing ST data and results currently limits the full potential of ST experiments. To fill the gap, we developed SpatialView, an open-source web browser-based interactive application for visualizing data and results from multiple 10× Genomics Visium ST experiments. We anticipate SpatialView will be useful to a broad array of clinical and basic science investigators utilizing ST to study disease. SpatialView is available at https://github.com/kendziorski-lab/SpatialView (and https://doi.org/10.5281/zenodo.10223907); a demo application is available at https://www.biostat.wisc.edu/˜kendzior/spatialviewdemo/.

An uncertainty quantification framework for agent-based modeling and simulation in networked anagram games

ABSTRACT In a networked anagram game, players are provided letters with possible actions of requesting letters from their neighbours, replying to letter requests, or forming words. The objective is to form as many words as possible as a team. The experimental data show that behaviours among players can vary significantly. However, simulations using agent-based models (ABM) in the literature often have not incorporated proper uncertainty quantification methods to characterise diverse behaviours of players. In this work, we propose an uncertainty quantification framework to build, exercise, and evaluate agent behaviour models and simulations for networked group anagram games. Specifically, using the data of game experiments, the proposed framework considers the clustering of game players based on their performance to reflect players’ heterogeneity. Moreover, we also quantify uncertainty within each cluster through statistical modelling and inference. Numerical studies of networked game configurations are conducted to demonstrate the merits of the proposed framework.

The Risks of Ranking: Revisiting Graphical Perception to Model Individual Differences in Visualization Performance.

Graphical perception studies typically measure visualization encoding effectiveness using the error of an "average observer", leading to canonical rankings of encodings for numerical attributes: e.g., position area angle volume. Yet different people may vary in their ability to read different visualization types, leading to variance in this ranking across individuals not captured by population-level metrics using "average observer" models. One way we can bridge this gap is by recasting classic visual perception tasks as tools for assessing individual performance, in addition to overall visualization performance. In this article we replicate and extend Cleveland and McGill's graphical comparison experiment using Bayesian multilevel regression, using these models to explore individual differences in visualization skill from multiple perspectives. The results from experiments and modeling indicate that some people show patterns of accuracy that credibly deviate from the canonical rankings of visualization effectiveness. We discuss implications of these findings, such as a need for new ways to communicate visualization effectiveness to designers, how patterns in individuals' responses may show systematic biases and strategies in visualization judgment, and how recasting classic visual perception tasks as tools for assessing individual performance may offer new ways to quantify aspects of visualization literacy. Experiment data, source code, and analysis scripts are available at the following repository: https://osf.io/8ub7t/?view_only=9be4798797404a4397be3c6fc2a68cc0.

A Novel Iterative Positioning Method Based on Difference RSS Model With 5G Field Experiments

In the 5th Generation (5G) positioning, the accurate values of environmental parameters such as Pathloss exponent (PLE) and transmit power are difficult to obtain accurately. Methods based on the difference of received signal strength (DRSS) can be utilized to solve the problems. An estimation method to obtain the distance ratio is given, and a distance ratio positioning model is proposed. The initial positioning results are calculated with linear least squares (LLS) algorithm. A Levenberg-Marquardt (LM) based maximum a posteriori (MAP) algorithm is proposed to obtain the final result by performing a series of iterations. We have completed the 5G field data collection in urban environments and preprocessed the raw data in 5G field experiments. We also propose a judgment method for 5G positioning based on horizontal dilution of precision (HDOP). Compared to the state-of-art DRSS-based algorithms, the proposed method has the best positioning accuracy and achieves a positioning error of 43.8 meters for 80% of samples with six base stations.

TRNAGlu-derived fragments from embryonic extracellular vesicles modulate bovine embryo hatching

Transfer RNA-derived small RNAs (tsRNAs) have been shown to be involved in early embryo development and repression of endogenous retroelements in embryos and stem cells. However, it is unknown whether tsRNAs also regulate embryo hatching. In this study, we mined the sequencing data of a previous experiment in which we demonstrated that the microRNA (miRNA) cargo of preimplantation embryonic extracellular vesicles (EVs) influences embryo development. We thus profiled the tsRNA cargo of EVs secreted by blastocysts and non-blastocysts. The majority of tsRNAs was identified as tRNA halves originating from the 5´ ends of tRNAs. Among the 148 differentially expressed tsRNAs, the 19 nt tRNA fragment (tRF) tDR-14:32-Glu-CTC-1 was found to be significantly up-regulated in EVs derived from non-blastocysts. RT-qPCR assays confirmed its significant up-regulation in non-blastocyst embryos and their conditioned medium compared to the blastocyst group (P < 0.05). Inhibition of tDR-14:32-Glu-CTC-1 by supplementing antagomirs to the conditioned medium improved embryo hatching (P < 0.05). Transcriptomic analysis of embryos treated with tDR-14:32-Glu-CTC-1 antagomirs further showed differential expression of genes that are associated with embryo hatching and implantation. In summary, tDR-14:32-Glu-CTC-1 is up-regulated in non-blastocyst embryos and their secretions, and inhibition of tDR-14:32-Glu-CTC-1 promotes embryo hatching, while influencing embryo implantation-related genes and pathways. These results indicate that embryonic EVs containing specific tRFs may regulate preimplantation embryo development.

Distributed MPC for Multi-Vehicle Cooperative Control Considering the Surrounding Vehicle Personality

In real traffic environment, a single control mode of traditional autonomous vehicles cannot meet various driving requirements for different drivers, which will decrease the acceptance of autonomous vehicles, and even may further cause traffic risks. This paper studies the cooperative strategies between ego vehicle and surrounding vehicles with the naturalistic experiment data, and then designs an autonomous vehicle control method based on the distributed Model Predictive Control (MPC) in order to consider the interaction relationship of ego vehicles and surrounding vehicles. Finally, the proposed method is verified by software simulation and Hardware in the Loop (HIL) simulation experiments, and the experiment results demonstrate that the control method proposed in this paper not only can control the vehicle to complete the typical driving tasks smoothly, in terms of car-following and lane-changing, but also can reflect the different cooperative strategies among different driving behavior characteristics, which can improve safety and acceptance of autonomous vehicles to promote the practical application of autonomous vehicle technology.

Theoretical modeling of predicting elastic modulus of polyurethane copolymer/organic-montmorillonite nanocomposite

A structure of theoretical models set was suggested to predict the elastic moduli of polyurethane copolymer (PUC)/organic modified montmorillonite (OMMT) nanocomposites (NCs) in terms of length (L) to thickness (t) ratio and volume fraction ([Formula: see text]) of OMMT nanoparticles. The predicted elastic modulus outcomes of PUC/OMMT NCs were compared with experiment data. The outcome demonstrated that the suggested aspect ratio of predicted elastic modulus decreased with increased [Formula: see text] of OMMT compared to experimental data. The largest value of effective aspect ratio belonged to the Hui–Shia model over all OMMT [Formula: see text]. The modified Halpin–Tsai model incorporated with the factor for decreasing modulus (FFDM) recorded the lowest range of percentage error between theoretical and experimental data around 0.385–0.816% at [Formula: see text] (4[Formula: see text]wt.%) OMMT.

Assessing Sensor Integrity for Nuclear Waste Monitoring Using Graph Neural Networks.

A deep geological repository for radioactive waste, such as Andra's Cigéo project, requires long-term (persistent) monitoring. To achieve this goal, data from a network of sensors are acquired. This network is subject to deterioration over time due to environmental effects (radioactivity, mechanical deterioration of the cell, etc.), and it is paramount to assess each sensor's integrity and ensure data consistency to enable the precise monitoring of the facilities. Graph neural networks (GNNs) are suitable for detecting faulty sensors in complex networks because they accurately depict physical phenomena that occur in a system and take the sensor network's local structure into consideration in the predictions. In this work, we leveraged the availability of the experimental data acquired in Andra's Underground Research Laboratory (URL) to train a graph neural network for the assessment of data integrity. The experiment considered in this work emulated the thermal loading of a high-level waste (HLW) demonstrator cell (i.e., the heating of the containment cell by nuclear waste). Using real experiment data acquired in Andra's URL in a deep geological layer was one of the novelties of this work. The used model was a GNN that inputted the temperature field from the sensors (at the current and past steps) and returned the state of each individual sensor, i.e., faulty or not. The other novelty of this work lay in the application of the GraphSAGE model which was modified with elements of the Graph Net framework to detect faulty sensors, with up to half of the sensors in the network being faulty at once. This proportion of faulty sensors was explained by the use of distributed sensors (optic fiber) and the environmental effects on the cell. The GNNs trained on the experimental data were ultimately compared against other standard classification methods (thresholding, artificial neural networks, etc.), which demonstrated their effectiveness in the assessment of data integrity.

Improvement of the method of time rationing for assembling car groups on one track

Purpose. To improve the method for standardizing the duration of the shunting operation of assembling cars on one track. This can be achieved as a result of solving the following research problems: development of a method for searching the optimal order of assembling cars on one track; distribution parameters estimation of the random value of the duration of shunting operation of assembling cars on one track based on calculation experiments. Methodology. During the research, the methods of theory of railway operation, dynamic programming and mathematical statistics were used. Findings. Research on the assembling process of car group to one track established the distribution parameters of the random variable of time spent for shunting. In the course of the research, the problem of choosing the optimal order of shunting operations during car assembling was formalized and solved as a problem of dynamic programming. The time spent for shunting work was chosen as the optimality criterion. The paper considers the possibility of approximating the data of calculation experiments by analytical dependencies. It was found out that the use of linear polynomials with interaction allows obtaining dependencies describing time standards with a relative accuracy of ±5 %. Originality. The method is improved for developing the time standards for shunting work, which, unlike the existing one, is based on the performance of a series of calculation experiments, each of which solves the optimization problem of finding such an order of assembling cars that ensures minimum time consumption for shunting. Practical value. The methods developed in the work and the dependencies obtained allow improving the quality of decisions made when developing technology and designing railway stations and sidings of industrial enterprises.

Using Patient Preferences in Health Technology Assessment: Evaluating Quality-Adjusted Survival Equivalents (QASE) for the Quantification of Non-health Benefits.

Interest in using patient preference (PP) data alongside traditional economic models in health technology assessment (HTA) is growing, including using PP data to quantify non-health benefits. However, this is limited by a lack of standardised methods. In this article, we describe a method for using discrete choice experiment (DCE) data to estimate the value of non-health benefits in terms of quality-adjusted survival equivalence (QASE), which is consistent with the concept of value prevalent among HTA agencies. We describe how PP data can be used to estimate QASE, assess the ability to test the face-validity of QASE estimates of changes in mode of administration calculated from five published DCE oncology studies and review the methodological and normative considerations associated with using QASE to support HTA. We conclude that QASE may have some methodological advantages over alternative methods, but this requires DCEs to estimate second-order effects between length and quality of life. In addition, empirical work has yet to be undertaken to substantiate this advantage and demonstrate the validity of QASE. Further work is also required to align QASE with normative objectives of HTA agencies. Estimating QASE would also have implications for the conduct of DCEs, including standardising and defining more clear attribute definitions.

Estimate of Wave Overtopping Rate on Armoured Slope Structures Using FUNWAVE-TVD Model

In this study, the program was modified by adding the empirical formula of EurOtop (2018) to enable calculation of wave overtopping on armoured slope structures in the FUNWAVE-TVD model using the fully nonlinear Boussinesq equation. The validity of the modified numerical model was verified by comparing it with CLASH data and experiment data for the rubble mound structure. This model accurately reproduced the change in wave overtopping rate according to the difference in the roughness factor of the armoured block, and well reproduced the rate of decrease in wave overtopping rate due to the increase in relative freeboard. The overtopping rate of the armoured slope structures showed significant differences depending on the positioning condition of the armoured blocks. When Tetrapods were placed with regular positioning, the overtopping rate increased significantly compared to when they were placed with random positioning, and it was consistent with when they were placed with Rocks. Meanwhile, when rocks were placed in one row, the wave overtopping rate was greater than when rocks were placed in two rows, which is believed to be due to the influence of the roughness and permeability of the structure’s surface.