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Understanding the strengths and limitations of the modeling capacity of surface flooding in urbanized floodplains is of utmost importance as such events are becoming increasingly frequent and extreme. In this study, we assess two computational models against laboratory observations of surface urban flooding in a reduced‐scale physical model of idealized urban districts. Four urban layouts were considered, involving each three inlets and three outlets as well as a combination of three‐ and four‐branch crossroads together with open spaces. The first model (2D) solves the shallow‐water equations while the second one (3D) solves the Reynolds‐averaged Navier‐Stokes equations. Both models accurately predict the flow depths in the inlet branches. For the discharge partition between the outlets, deviations between the computations and laboratory observations remain close to the experimental uncertainties (maximum 2.5 percent‐points). The velocity fields computed in 3D generally match the measured surface velocity fields. In urban layouts involving mostly a network of streets, the depth‐averaged velocity fields computed by the 2D model agree remarkably well with those of the 3D model, with differences not exceeding 10%, despite the presence of helicoidal flow (revealed by the 3D computations). In configurations with large open areas, the 3D model captures generally well the trajectory and velocity distribution of main surface flow jet and recirculations; but the 2D model does not perform as well as it does in relatively channelized flow regions. Visual inspection of the jet trajectories computed by the 2D model in large open areas reveals that they substantially deviate from the observations. Plain Language Summary Advancing our modeling capacity of urban flooding is of utmost importance for improving the design of risk reduction measures. During extreme urban flooding, complex flow patterns develop in urban environments, involving three‐dimensional flow structures. Though, urban floods are commonly simulated with two‐dimensional computational models. So far, no detailed comparison between flow fields predicted by two‐ and three‐dimensional computational models were conducted and assessed against reference data such as experimental observations for representative configurations of urban flooding. In this study, we assess two computational models against laboratory observations of urban flooding in a reduced‐scale physical model of an idealized district. Key Points Predictions of 2D and 3D computational models were compared against laboratory experiments representing urban flooding in a steady‐state Both models perform equally well to predict upstream flow depth, outlet discharge partition, and velocity field in street networks In urban layouts with large open spaces, only the 3D model accurately predicts the velocity field

Identifying characteristic structural conformations of enzymes and proteins, especially key titratable amino acids, could become a mandatory stage of further research in performing natural and computational experiments by varying the pH values, charges, and concentrations of water–salt environments. The authors of this work perform computer molecular dynamics (MD) and experimental studies of the enzyme alcohol dehydrogenase and its cofactor (ADH + NAD) solvated with water on a graphite carbon surface. Images are obtained of the adsorption of ADH + NAD on the surface of a graphitic carbon surface during long-term 100 ns dynamic conformational and rotational changes. MD analysis allows the orientation of ADH + NAD enzyme adsorption to be mapped, thereby providing detailed observations of changes in the conformation of proteins in the region of titratable amino acid residues of ADH. An extension of MD modeling is used to consider the mechanism of conformational changes in the ADH + NAD + water/graphitic carbon surface system, along with the orientation adsorption of the protein system and the key titratable amino acids. Finally, data from MD modeling are compared to experimental observations.

Rehman, K.; Park, K.-Y., and Cho, Y.-S., 2018. Experimental and Numerical Investigation of Solitary Wave Run-up Reduction. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1111–1115. Coconut Creek (Florida), ISSN 0749-0208. Rising sea-levels and extreme wave events threaten coastal communities and stability of coastal regions. Accurate prediction of wave over-topping over coastal protection structures is challenging, but vital for effective hazard mitigation. Non-hydrostatic numerical modelling and laboratory experiments are used to assess magnitude of run-up over coastal protection structures under varying relative wave heights and structural features. The primary focus is the investigation of solitary wave impact with breakwaters, the consequent run-up and measures for its reduction. The experiments consisted of generating solitary waves in a 1.1 m high and 32.5 m long flume and observing its run-up for different heights of incident waves. A slope adjuster was used to vary the slope of a plywood plank for reproducing coastal features. Experimental observations were verified by proposing a numerical model based on non-linear shallow water equations (NLSWE) and solution is obtained by Godunov-type finite volume method. The NLSWE provide good approximation of shoaling, wave breaking, and wave reflection which arise due to wave overtopping in the swash and surf zones. The novel feature of the numerical model is the introduction of bed slope discretization technique – applicable on both structure and unstructured meshes- which offers well-balanced solution even for steep slopes encountered in case of breakwaters. Shock-capturing capabilities of Harten, Lax, and van Leer with contact wave restoration (HLLC) solver are utilized for accurate estimation of shocks and bore waves features during flow transitions. The proposed model gives excellentn agreement with experimental observations. The findings will further enhance the understanding of extreme wave propagation events over submerged coastal structures and related mitigation techniques.

Source term estimation (STE) is crucial for understanding and addressing hazardous gas leakages in the chemical industry. Most existing methods basically use an atmospheric transport and dispersion (ATD) model to predict the concentrations of hazardous gas leakages from different possible sources, compare the predicted results with multi-sensor data, and use the deviations to search and derive information on the real sources of leakages. Although performing well in principle, complicated computations and the associated computer time often make these methods difficult to apply in real time. Recently, many machine learning methods have also been proposed for the purpose of STE. The idea is to build offline a machine-learning-based STE model using data generated with a high-fidelity ATD model and then apply the machine learning model to multi-sensor data to perform STE in real time. The key to the success of a machine-learning-based STE is that the machine-learning-based STE model has to cover all possible scenarios of concern, which is often difficult in practice because of unpredictable environmental conditions and the inherent robust problems with many supervised machine learning methods. In order to address challenges with the existing STE methods, in the present study, a novel multi-sensor data-driven approach to STE of hazardous gas leakages is proposed. The basic idea is to establish a multi-sensor data-driven STE model from historical multi-sensor observations that cover the situations known as the independent hazardous-gas-leakage scenarios (IHGLSs) in a chemical industry park of concern. Then the established STE model is applied to online process multi-sensor data and perform STE for the chemical industry park in real time. The new approach is based on a rigorous analysis of the relationship between multi-sensor data and sources of hazardous gas leakages and derived using advanced data science, including unsupervised multi-sensor data clustering and analysis. As an example of demonstration, the proposed approach is applied to perform STE for hazardous gas-leakage scenarios wherein a Gaussian plume model can be used to describe the atmospheric transport and dispersion. Because of no need of ATD-model-based online optimization and supervised machine learning, the new approach can potentially overcome many problems with existing methods and enable STE to be literally applied in engineering practice.

Our planet is changing, and one of the most pressing challenges facing the scientific community revolves around understanding how ecological communities respond to global changes. From coastal to deep-sea ecosystems, ecologists are exploring new areas of research to find model organisms that help predict the future of life on our planet. Among the different categories of organisms, meiofauna offer several advantages for the study of marine benthic ecosystems. This paper reviews the advances in the study of meiofauna with regard to climate change and anthropogenic impacts. Four taxonomic groups are valuable for predicting global changes: foraminifers (especially calcareous forms), nematodes, copepods and ostracods. Environmental variables are fundamental in the interpretation of meiofaunal patterns and multistressor experiments are more informative than single stressor ones, revealing complex ecological and biological interactions. Global change has a general negative effect on meiofauna, with important consequences on benthic food webs. However, some meiofaunal species can be favoured by the extreme conditions induced by global change, as they can exhibit remarkable physiological adaptations. This review highlights the need to incorporate studies on taxonomy, genetics and function of meiofaunal taxa into global change impact research.

The highly dynamic and unsteady characteristics of the cavitating flow cause many negative effects such as erosion, noise and vibration. Also, in the real application, it is inevitable to neglect the dissolved air in the water, although it is usually neglected in the previous works to reduce the complexity. The novelty of the present work is analysing the impact of dissolved air on the average/unsteady characteristics of Venturi flow by conducting sets of experimental tests. For this purpose, two different amounts of dissolved air at five pressure levels (i.e. five different sets of cavitation numbers) were considered in the study of cavitating flow inside a Venturi nozzle. The fast Fourier transform analysis of pressure fluctuations proved that the shedding frequency reduces almost by 50% to 66%, depending on the case, with adding the amount of dissolved air. However, the reduction of 14% to 25% is achieved by the vibration transducers. On the other hand, the cavity enlarges as well as bubbly flow is observed in the test chamber at a higher level of dissolved air. Furthermore, it is observed that the re-entrant jet, as the main reason for the cavity detachment, is more effective for the detachment process in cases with a lower level of dissolved air, where the re-entrant jet front penetrates more toward the leading edge.

Buoyant unstable behavior in initially spherical lean hydrogen-air premixed flames within a center-ignited combustion vessel have been studied experimentally under a wide range of pressures (including reduced, normal, and elevated pressures). The experimental observations show that the flame front of lean hydrogen-air premixed flames will not give rise to the phenomenon of cellular instability when the equivalence ratio has been reduced to a certain value, which is totally different from the traditional understanding of the instability characteristics of lean hydrogen premixed flames. Accompanied by the smoothened flame front, the propagation mode of lean hydrogen premixed flames transitions from initially spherical outwardly towards upwardly when the flames expand to certain sizes. To quantitatively investigate such buoyant instability behaviors, two parameters, “float rate (ψ)” and “critical flame radius (Rcr)”, have been proposed in the present article. The quantitative results demonstrate that the influences of initial pressure (Pint) on buoyant unstable behaviors are different. Based on the effects of variation of density difference and stretch rate on the flame front, the mechanism of such buoyant unstable behaviors has been explained by the competition between the stretch force and the results of gravity and buoyancy, and lean hydrogen premixed flames will display buoyant unstable behavior when the stretch effects on the flame front are weaker than the effects of gravity and buoyancy.

In this paper, we experimentally investigate the pattern transition of two-dimensional Faraday waves at an extremely shallow depth in a Hele-Shaw cell. Several patterns of Faraday waves are observed, which have some significant differences in wave profile,wave height and wave length. It is found that, in a wide range of the forcing frequency f, there always exists a region of the acceleration amplitude A, in which there exist the so-called hysteretic jumps between different patterns of Faraday waves. All of these experimental observations could enrich our knowledges about the Faraday waves and would be helpful to the further theoretical studies on the related topic in future.

The effect of stress depolarization will cause actuation function degradation of a piezoelectric actuator, which can eventually trigger function failure of the piezoelectric smart structure system. In the present study, we experimentally demonstrate the degradation process of the actuation function of the Macro Fiber Composite (MFC) piezoelectric actuator. Actuation function degradation data of MFC actuators undergoing cyclic loads with four different stress amplitudes have been measured. Based upon the experimental results, the radial basis function (RBF) neural network learning algorithm was adopted to establish a neural network model, in order to predict the actuation function degenerative degree of the MFC actuator, undergoing arbitrary cyclic load within the concerned stress amplitude range. The maximum relative error between the predicted result and our experimental result is 4%.

The Fellows of the Royal Society of London for the Improvement of Natural Knowledge bonded with one another in the 1660s, in response to external skepticism about their observation-based epistemology and practices, through an active book-gifting network that seeded their libraries with one another’s works. An examination of the way membership in the Royal Society was demarcated, negotiated, and cultivated vis-à-vis books and other archived properties serves to illuminate the contradictions inherent in the birthing of the hybrid identity of the gentleman-scholar as the ideal practitioner of the New Science in England during the Restoration period. The Fellows, in turn, rejected the upstart gentlewoman-scholar and poet, Margaret Cavendish, Duchess of Newcastle, and her efforts to participate in their book-gifting network, revealing the limitations on their ability to absorb challenges to the observation-based methodology of the New Science, and hence to truly embrace diversity of thought and identity at a time when the perimeters of scientific inquiry were being drawn.