Small-scale Experiments Research Articles

Fast Hyperspectral Image Classification with Strong Noise Robustness Based on Minimum Noise Fraction

A fast hyperspectral image classification algorithm with strong noise robustness is proposed in this paper, aiming at the hyperspectral image classification problems under noise interference. Based on the Fast 3D Convolutional Neural Network (Fast-3DCNN), this algorithm enables the classification model to have good tolerance for various types of noise by using a Minimum Noise Fraction (MNF) as dimensionality reduction module for hyperspectral image input data. In addition, by introducing lightweight hybrid attention modules with the spatial and the channel information, the deep features extracted by the Convolutional Neural Network are further refined, ensuring that the model has high classification accuracy. Public dataset experiments have shown that compared to traditional methods, the MNF in this algorithm reduces the dimensionality of input spectral data, preserves information with higher signal-to-noise ratio(SNR) in the spectral bands, and aggregates spectral features into class feature vectors, greatly improving the noise robustness of the model. At the same time, based on a lightweight spectral–spatial hybrid attention mechanism, combined with fewer spectral dimensions, the model effectively avoids overfitting. With less loss in model training speed, it achieved better classification accuracy in small-scale training sample experiments, fully demonstrating the good generalization ability of this algorithm.

Numerical and experimental study on reinforced 3DCP walls filled with light-weight concrete

This paper explores the structural viability of 3DCP as a novel additive manufacturing method in the construction industry, focusing on its integration and standardization challenges due to its emerging nature. With the construction industry's increasing interest in innovative materials and robotic construction, 3DCP's unique characteristics necessitate thorough investigation to understand its potential fully. This study aimed to assess the structural capacity of 3DCP walls, employing flexural tests on samples filled with lightweight concrete containing EPS, and comparing the outcomes with those of traditionally cast concrete. Through a comprehensive approach that combines experimental work with numerical analysis, this study intended to calibrate the material's properties based on small-scale tests to inform the design of larger structures. Macro and micro-scale numerical modeling methods were investigated for the analysis of 3DCP. The findings revealed that the inherent strength of 3DCP significantly depends on the material's composition and quality. Moreover, it was observed that the structural integrity of 3DCP walls was somewhat inferior to that of fully cast counterparts. However, a strong correlation between the numerical simulations and experimental data underscores the value of this research. By calibrating 3DCP's properties from small-scale experiments, the study provides a foundational basis for designing larger structures with enhanced reliability. Both numerical methods demonstrate high accuracy for the analysis of 3DCP and can be adopted for the analysis of larger structures.

Damage mechanism of model arch dam subjected to far-field underwater explosion

The dynamic response and damage modes of arch dams subjected to explosions are key topics having been extensively researched in recent years. However, the majority of research employs numerical simulation, and there is a lack of experimental investigations to further support those numerical simulation results. Given this, small-scale model experiments were conducted on the arch dam to investigate its dynamic response to underwater explosions. The findings of these experiments indicated a potential overall damage mode along the crown cantilever profile. A numerical investigation of the experimental arch dam was executed employing the CEL method in combination with the Concrete Damage Plasticity model. The damage development process and cracking mechanism of the arch dam under a far-field underwater explosion were examined. According to the numerical findings, the damage process to the arch dam resulting from a far-field underwater explosion might be divided into two phases: the shock wave action phase and the overall response phase. During the shock wave action phase, slight damage first appeared on the downstream dam face. Later, during the overall response phase, a crack spread from the dam base to dam crest and from the downstream side to the upstream side, eventually penetrating through the crown cantilever profile. The damage mechanism in the shock wave action phase is the reflected rarefaction wave off the downstream dam face causing localized tensile damage to surrounding concrete. While the cracking mechanism in the overall response phase is structural bending-induced tensile damage driven by the overall response.

Decontamination of Bacterial Spores Using a Bio-reaction System

This report describes the test results of decontamination of Bacillus atrophaeus spores. The spore solution at 109 cfu/mL concentration was treated with chemical decontaminants, hydrogen peroxide, DF-200, sodium dichloroisocyanurate(NaDCC), and perasasfe. DF-200 was not suitable for decontamination of the spore solution. Among them, the optimal decontamination reaction conditions of perasafe and NaDCC were established from test tube experiments in a mL-scale, and they were validated in a bio-reaction system in a L-scale. The optimal conditions of perasafe and NaDCC were 1.0 % of concentration with 5 minutes of reaction time and 0.3 % of concentration with 10 minutes of reaction time, respectively. Also, both decontaminants required adequate agitation for decontamination. The results in the bio-reaction system were similar with the results from the smaller scale using test tubes, showing that the optimal conditions from the smaller scale experiments can be applied to the larger scale.

Experimental and numerical study on bubble pulsation characteristics of underwater explosions with multiple charges

This study examines the processes of expansion, merging, and collapse of multiple underwater explosion bubbles through experimental and numerical methods. A small-scale underwater explosion experiment was conducted in a water tank. The behaviors of three and four bubbles during expansion, merging, and collapse were captured using high-speed photography, and the effects of the quantity and spacing of the explosive charge on the bubble dynamics were analyzed. The results indicate that the evolution of bubble behavior in multiple charge underwater explosions, including the bubble period and radius, is significantly influenced by the spacing between charges. With a decrease in the ratio of the charge spacing to the bubble radius, the period of the merged bubble increases progressively. Independent small bubbles do not interact when the distance between charges exceeds 1.3 times the bubble radius. Furthermore, when the ratio of the spacing to the initial bubble radius (L/rb) is between 1.0 and 1.3, multiple bubbles merge during the contraction phase. When the spacing is less than the maximum radius of the bubbles, multiple bubbles inevitably merge, with fusion occurring during the expansion phase.

Multiscale modeling of cavitation around high-speed object based on Euler-Lagrange model and overset mesh

Abstract Cavitation is a common phenomenon, which usually occurs inside the high-speed liquid or at the liquid-solid interface. The unsteady behaviors of cavitating flow, such as shedding and collapse, can cause intense pressure fluctuations and reduce the stability of devices such as under-water high-speed vehicles. In addition, cavitating flow changes the dynamic characteristics of the liquid and causes vibration of the structure as well, making it extremely difficult in achieving precise control. Using OpenFOAM, the present work employs the large eddy simulation (LES) approach to investigate the characteristics of the unsteady cavitating flow around a high-speed under-water object with using the overset mesh technology. The volume of fluid (VOF) approach jointed with the Lagrangian discreate bubble model (DBM) is used for capturing the multiscale cavitation features. The Schnerr & Sauer model is applied for the mass transfer between water and vapor in macroscale, while the Reynolds-Pel equation is incorporated for the growing and collapsing of microscale bubbles. Due to the difficulty in incorporating the multi-scale method into the problems with mesh motion, the present work employs the overset mesh method. Compared with the published small-scale water tank experiment, the LES simulation results fit well with the experimental phenomena, and the DBM can capture the small bubbles accurately. On the basis of model verification, the mechanisms of cavitation forming and collapsing is investigated and the effect of cavitation shedding on the motion of the object is also studied. Moreover, the nucleation, growth, collapse of bubbles, and the interaction between discrete bubbles and large cavities can be well revealed. Further, the multi-scale Euler-Lagrange model is also applied in the rotating propeller, the generation of tip vortex cavitation which is hard to be captured by traditional models is well presented.

BOS and Hot-Film Analysis of a CH-53G Helicopter Wake in Ground Effect

Constant temperature anemometry and background-oriented schlieren (BOS) measurements on a CH-53G helicopter (takeoff mass ≈14t) are used to investigate the rotor wake including the vortex breakdown to statistical turbulence. Hovering flights at a range of hub heights 0.50 < h < 0.83 were investigated. The position of the rotorcraft was optically tracked using markers affixed to the fuselage. A complete breakdown of the tip vortices was noted within 0.3R of the rotor plane, in stark qualitative contrast to small-scale experiments which show the tip vortices persisting to the ground plane. The large (37 m2) BOS field of view showed a small effect of vortex pairing and blade vortex interaction, which was overshadowed by the rapid wake breakdown. Vortex pairing was found to result from varying vortex convection velocities rather than from initial differences in the vortex spacing due to the blade track.

Compact Solar Generator with Increased Efficiency

Today the world is moving towards renewable energy. Most important and common form of renewable energy is solar energy. But solar panels have less efficiency and covers more space. This paper discusses about new way of generating electricity with the help of solar panel. A small scale experiment was conducted results have proven good performance. In future this concept will prove a golden change in the life of people.

Study on the thermal radiation characteristics caused by two fires in a tunnel based on multi-layer zone model

The radiation of fire source and hot flue gas plays a very important role in the process of smoke movement. The radiation effect, which was little included in the earlier studies, was included in the present work. So the thermal radiation characteristics caused by two fires will be studied in a tunnel combined with multi-layer zone (MLZ) model, small-scale experiments and numerical simulations. Based on the data obtained by the aforementioned methods, research on the thermal radiation model is carried and a piecewise fire source model is proposed. Subsequently, the longitudinal thermal radiation model caused by two fires in a tunnel is investigated and then modified and verified. The results showed that the thermal radiation model caused by two fires for MLZ model in a tunnel is reliable, which can make a general and reliable judgment on the immediate fire disaster situation, and can also provide reference for the follow-up work.

Successful reintroduction of the European pond turtle Emys orbicularis with a small number of founders: results from a 20-years small-scale experiment

Successful reintroduction of the European pond turtle Emys orbicularis with a small number of founders: results from a 20-years small-scale experiment

Contribution of Unsteadiness to Solid Fuel Burning Characteristics in a Scramjet Combustor

The contributions of unsteadiness to solid fuel combustion are investigated numerically and validated against new experiments in a deep cavity scramjet. Large-eddy simulations discretized with discontinuous Galerkin (DG) elements are solved with a flamelet manifold approach in three dimensions. A multiphase model that incorporated thermal decomposition inside the foam layer is coupled with stagnation flow flames to determine the combustion manifold and regression rate. The approach accurately models small-scale experiments of convective burning over solid fuel. The inclusion of the manifold into the DG code features two innovations: a polynomial fitting of the pressure to reduce the interpolation dimensions and the coefficient of determination to include non-monotonic manifolds in DG schemes. Model validation was performed using pressure and averaged regression rate data, both of which showed strong agreement with experiments. Three-dimensional pressure modes in the cavity support a substantial increase in regression rates and a broadening of the peak due to oscillations of the impingement point. The majority of fuel is pyrolyzed at the shear-layer reattachment point in a stagnation flow boundary layer. The fuel in the cavity is pyrolyzed by conductive heat transfer from the main shear layer. Poor combustion is observed in the expanding fuel section.

A data-driven underground gas storage production system string failure prediction model for time-varying reliability analysis

In underground gas storage (UGS) systems, the production tubing string system undergoes complex thermo-mechanical loading conditions, leading to fatigue damage accumulation and potential failure risks. To accurately assess the fatigue reliability and mitigate risks, it is crucial to develop a data-driven physics-informed uncertainty modeling approach that captures the coupled thermo-mechanical effects and accounts for various uncertainties. This study proposes a data-driven physics-informed modeling method based on thermo-mechanical coupling for fatigue reliability assessment and risk mitigation in critical UGS systems. A quantitative analysis method is introduced, which relies on small-scale multi-stage loading experiments and combines the stochastic degradation process with time-series reliability theory. To analyze the fatigue life of joints under complex loading conditions, a modified S-N curve model is developed. This model takes into account the influences of the dimension coefficient, stress concentration factors, surface finish coefficients, and thermal load. It considers the uncertainties associated with different temperature loads and surface finish on fatigue life. By integrating physics-informed modeling, uncertainty quantification, and fatigue damage accumulation analysis, this approach provides a comprehensive framework for fatigue reliability assessment and risk mitigation in critical UGS systems. It enables informed decision-making for safe and reliable operations, as well as optimized maintenance strategies, ultimately enhancing the overall system performance and mitigating potential failures.

A Mixed Convection Model for Estimating the Critical Velocity to Prevent Smoke Backlayering in Tunnels

AbstractA novel mathematical model for the critical ventilation velocity to prevent smoke backlayering in tunnels is presented, addressing limitations of prior approaches. The basis of the model is a rigorous characterisation of the physical processes by the characteristic quantities. Empirical parameters within the new model are determined, to align with results from both full-size and small-scale tunnel experiments. Data from numerical simulations (CFD, Computational Fluid Dynamics), validated by known test data, are then used to estimate the effects of tunnel slope and other parameters on the critical velocity. The model is seen to approximate the critical velocity well, following all trends identified by test data and CFD parameter studies. The empirically calibrated equation permits prediction of the critical velocity beyond the narrow range of tunnel geometries where known results already give an answer. The resulting equation has practical application for tunnel design.

Topology-Driven Discovery of Transmembrane Protein S-Palmitoylation.

Protein S-palmitoylation is a reversible lipophilic posttranslational modification regulating a diverse number of signaling pathways. Within transmembrane proteins (TMPs), S-palmitoylation is implicated in conditions from inflammatory disorders to respiratory viral infections. Many small-scale experiments have observed S-palmitoylation at juxtamembrane Cys residues. However, most large-scale S-palmitoyl discovery efforts rely on trypsin-based proteomics within which hydrophobic juxtamembrane regions are likely underrepresented. Machine learning- by virtue of its freedom from experimental constraints - is particularly well suited to address this discovery gap surrounding TMP S-palmitoylation. Utilizing a UniProt-derived feature set, a gradient boosted machine learning tool (TopoPalmTree) was constructed and applied to a holdout dataset of viral S-palmitoylated proteins. Upon application to the mouse TMP proteome, 1591 putative S-palmitoyl sites (i.e. not listed in SwissPalm or UniProt) were identified. Two lung-expressed S-palmitoyl candidates (synaptobrevin Vamp5 and water channel Aquaporin-5) were experimentally assessed. Finally, TopoPalmTree was used for rational design of an S-palmitoyl site on KDEL-Receptor 2. This readily interpretable model aligns the innumerable small-scale experiments observing juxtamembrane S-palmitoylation into a proteomic tool for TMP S-palmitoyl discovery and design, thus facilitating future investigations of this important modification.

Addressing small-scale temperature swing adsorption challenges using intensified fluidised bed technology for carbon capture process development

Polyethylenimine (PEI)-based adsorbents exhibit high CO2 capacities, making them potential candidates for mitigating unavoidable industrial CO2 emissions. However, desorption of CO2 from PEI, and from adsorbents in general, has received far less attention in the literature than adsorption. Whilst Temperature Swing Adsorption (TSA) is simple to conceptualise, it is difficult to implement in small-scale experiments in practice. Here we study the desorption characteristics of a commercial branched PEI adsorbent in a small-scale swirling fluidised bed reactor (TORBED) to improve the small-scale heat transfer rates. Our experimental results show that higher desorption temperatures, higher gas flow rates, and higher CO2 concentrations during adsorption can improve the desorption efficiency (defined as the amount of CO2 removed as a fraction of the initial amount adsorbed). In terms of kinetics, we found that the fractional order kinetic model provided the best fit to the PEI adsorbent, implying that this adsorbent involves multiple simultaneous molecular interactions, physisorption processes, and chemisorption processes, that cannot be described by simpler pseudo 1st or 2nd order models. Desorption rates in the TORBED in this study were 1 order of magnitude faster than fluidised beds, and 2–3 orders of magnitude faster than packed beds.

Non-uniform dune development in the presence of standalone beach buildings

Shoreward sand transport and dune development are increasingly influenced by the urbanization of beach-dune systems in the Netherlands. Three topographic datasets, on various spatio-temporal scales, are used to study the effect of standalone buildings on long term local dune development. On the smallest scale, terrestrial laser scans are used to study the geomorphological effects of two sea containers on the beach. On the intermediate scale, the geomorphological effects of a beach pavilion on the local dune development are studied with a 2-year topographic dataset of (bi) monthly permanent laser scans. Finally, 15 yearly airborne lidar scans of the beach-dune system in Noordwijk are used to evaluate the effect of multiple beach pavilions on dune growth variations. The small-scale experiment shows that horseshoe-shaped deposition patterns developed on the leeside of the containers. These depositions follow daily wind changes and leave deposits corresponding to the residual wind direction over the whole measuring period. Similar patterns are found around the larger beach pavilion, but anthropogenic activities like bulldozing and beach shaping make the determination of the effect on dune development harder to discern. Evaluation of the longer-term dataset reveals large variations in dune height and volume around beach pavilions. Dune height/volume increases vary between 1 and 8 m in height and 0–200 m3 in volume. A variability analysis shows that the length scale of alongshore variability in dune height/volume of urbanized dunes can be 10 times smaller than for natural dunes. For about half the beach pavilions, variations in dune height and volume are significantly correlated to the location of beach pavilions but correlation to particular beach pavilion properties is yet inconclusive.

Small data methods in omics: the power of one.

Over the last decade, biology has begun utilizing 'big data' approaches, resulting in large, comprehensive atlases in modalities ranging from transcriptomics to neural connectomics. However, these approaches must be complemented and integrated with 'small data' approaches to efficiently utilize data from individual labs. Integration of smaller datasets with major reference atlases is critical to provide context to individual experiments, and approaches toward integration of large and small data have been a major focus in many fields in recent years. Here we discuss progress in integration of small data with consortium-sized atlases across multiple modalities, and its potential applications. We then examine promising future directions for utilizing the power of small data to maximize the information garnered from small-scale experiments. We envision that, in the near future, international consortia comprising many laboratories will work together to collaboratively build reference atlases and foundation models using small data methods.

Transcriptomic analysis of the response mechanisms of black rockfish (Sebastes schlegelii) under noise stress from offshore wind farms

During the operational phase of offshore wind farms, the generation of low-frequency underwater noise has received widespread attention due to its potential adverse impact on fish health. This study conducted a field survey of underwater noise at offshore wind farms located in Shandong province, China. Subsequently, a small-scale experiment was conducted to study the stress on black rockfish (Sebastes schlegelii). The fish were exposed to noise with dominant frequency of 80 Hz, 125 Hz and 250 Hz. These frequencies are same with the frequencies from wind power noise (wpn) at the actual site. After a 40-day experimental period, transcriptome sequencing was conducted on brain, liver, and kidney tissues of black rockfish to elucidate the underlying molecular mechanisms involved in the response to noise stress originating from offshore wind farms. The results revealed that the 125 Hz group exhibited the highest number of differentially expressed genes (DEGs) between the noise-exposed and control check group (CK group), with a total of 797 in the brain, 1076 in the liver, and 2468 in the kidney. Gene Ontology (GO) analysis showed that DEGs were significantly enriched in entries related to cellular processes, membrane components, binding, and metabolism. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that DEGs were enriched mainly in metabolism, immunity, apoptosis, signal transduction, and diseases. The findings indicate that prolonged exposure to underwater noise from offshore wind farms may induce metabolic imbalance, immune dysfunction, and an increased risk of myocardial diseases in black rockfish.

Strong electron coupling effect of non-precious metal Schottky junctions enhanced square meter level photocatalytic hydrogen evolution

Photocatalytic hydrogen production technology utilizes solar energy to decompose water into hydrogen, helping to alleviate the pressure of energy depletion. Engineering of non-precious metal nanomaterials as cocatalysts can play a significant role in low-cost, sustainable, and large-scale photocatalytic hydrogen production. Herein, MnCdS-Vs/NiCo2S4 (MCSN) Schottky junction nanomaterials with strong electron coupling effect were prepared by a two-step hydrothermal method and successfully applied to a square meter hydrogen evolution device. The optimized MCSN material demonstrated high hydrogen evolution activity of 34.28 mmol g−1 h−1, which is 9.34 and 685.60 times higher than that of pure MnCdS-Vs and NiCo2S4, respectively. More importantly, in a square meter (1 m2) flat-plate reactor, MCSN produced H2 evolution approximately 201 mmol in 5 h, showcasing its potential for large-scale applications. In-situ XPS and DFT calculations demonstrated that MnCdS-Vs interacts with NiCo2S4 to produce a strong electron coupling effect and form a Schottky junction. It promotes the facilitated the directional migration of photogenerated electrons from MnCdS-Vs to NiCo2S4, but also effectively suppressed electron backflow through the Schottky barrier. Furthermore, the abundance of sulfur vacancies enhanced visible light absorption capability, further improving photocatalytic hydrogen evolution performance. This work delves into the role of defect engineering and Schottky junction design in enhancing photocatalytic performance, providing new insights into transitioning photocatalytic hydrogen production technologies from small-scale laboratory experiments to large-scale practical applications.

Assessing the Limit of CO2 Storage in Seawater as Bicarbonate-Enriched Solutions.

The dissolution of CO2 in seawater in the form of bicarbonate ions is an attractive alternative to storage in geological formations, on the condition that the storage is stable over long periods and does not harm the marine environment. In this work, we focus on the long-term chemical stability of CO2 absorbed in seawater as bicarbonate by monitoring the physico-chemical properties of the solutions (pH, dissolved inorganic carbon and alkalinity) in six different sets of experiments on both natural and artificial seawater lasting up to three months. The bicarbonate treatment of natural seawater consists of mixing it with pre-equilibrated solutions obtained from the reaction of CO2 and Ca(OH)2, with the same pH as natural seawater. This was achieved with a pilot plant working with tons of seawater, while small-scale laboratory experiments were carried out by adding sodium bicarbonate to artificial seawater solutions. If the increase in the overall carbon concentration in the final mixture does not exceed a critical threshold (about 1000-1500 μmol/L), the resulting bicarbonate-rich solutions are found to be stable for over three months.