Layout Density Research Articles

Valorization of wheat straw through enhancement of cellulose accessibility, xylan elimination and lignin removal by choline chloride:p-toluenesulfonic acid pretreatment.

Different molar ratio of choline chloride (ChCl) and p-toluenesulfonic acid (p-TsOH) (2: 1, 1: 1 and 1: 2, mol: mol) were used to prepare deep eutectic solvents (ChCl: p-TsOH) for pretreating cellulose fibers to elevate cellulose accessibility, enhance xylan elimination, increase lignin removal and promote enzymatic digestion. ChCl: p-TsOH (1: 1, mol: mol) could effectually destroy the dense layout of wheat straw (WS) at 80 °C for 60 min. Cellulose crystallinity declined from 43.4 % to 25.5 %, and the lignin surface area and hydrophobicity were reduced to 182.6 m2/g and 3.2 L/g, respectively. While cellulose accessibility in WS was significantly improved to 523.9 mg/g. The delignification and xylan removal reached 72.4 % and 90.5 %, respectively. The enzymatic digestibility reached 89.3 %. Furthermore, molecular dynamics simulation and quantum chemistry calculation were conducted on the lignocellulose model. The van der Waals interaction between ChCl:p-TsOH and lignin and the dispersion interaction between ChCl and lignin were identified. Accordingly, the interaction between biomass and ChCl:p-TsOH was elucidated at the molecular level. It provides a comprehensive understanding of lignocellulosic biomass valorization through the highly efficient pretreatment by ChCl:p-TsOH.

Volumetric drag coefficients for generic urban configurations: Insights from canopy flow analysis

Alternative drag approaches for representing unresolved buildings were proposed in literature for computational fluid dynamics (CFD) simulation of macroscopic urban airflow. As a contribution, the present work derives the volumetric drag coefficient (Cd*) through canopy drag and velocity analysis and provides appropriate correlations for Cd*against urban morphological parameters. A total of 72 cases across various urban configurations are investigated, categorized by building typology, horizontal layout, height variability, and plan area density (λp, from 0.0625 to 0.57). Reynolds-Averaged Navier-Stokes (RANS) simulations with periodic boundary conditions are performed to model fully developed flows. Results for the normalized drag force and superficial velocity and their relations with λp are evaluated. Subsequent evaluation of the profiles for the sectional coefficients (Cd*(Z)) reveals four distinct types with variations in uniform-height cases and combinations in varying-height cases. A throughout correlations analysis, facilitated by data transformation, identifies the straightforward relations between Cd* and frontal area density (λf) and tortuosity (τ). The followed stepwise regression provides a recommended formula for Cd*, demonstrating a proper fit with the simulated values. These findings facilitate the understanding and appropriate estimation of Cd* and Cd*(Z), promoting the application of macroscopic turbulence models, for neighborhood-scale wind and air quality studies.

A multi-sectional analysis of building height, layout, and urban density on seasonal energy consumption: A case study

This study aims to investigate the influence of building height and layout on energy consumption. It also analyzes methods for reducing energy consumption in these buildings. The EnergyPlus software performs simulations under local climatic conditions for all seasons. The city is divided into several sections based on cardinal directions, and energy consumption is calculated for each section, considering the city's distinct seasonal variations. Buildings in suburban areas with more sunlight exhibited higher overall energy consumption due to the reliance on heating and cooling systems, compared to the city center where denser urban areas moderated temperature extremes. Additionally, building design and insulation played significant roles. The analysis also revealed a west-to-east trend; higher consumption at the edges compared to the center. This is attributed to factors such as building density and shade from taller structures. The study further examined the impact of varying building heights. While most buildings were 20 meters tall, specific rows ranged from 21 to 25 meters. Changing these heights resulted in decreased cooling and increased heating demands in the north-south analysis, and reduced demands for both heating and cooling in the west-east analysis. This highlights the complex interplay between building layout, height, and energy consumption.

Influence of the contraction section configuration and deflector layout density on the wind-snow flow characteristics inside the ice snow wind tunnel for railway vehicles

The significant accumulation of snow and ice in the bogie region severely compromises operational quality and poses a safety hazard to high-speed trains. To enhance testing capabilities for assessing ice and snow accumulation within bogie regions, this study conducts numerical investigations into the influence of contraction section configuration and deflector layout density on wind-snow flow quality within an ice and snow wind tunnel. The predictive accuracy of the numerical method is comprehensively validated against wind-snow wind tunnel tests, involving a comparison of airflow velocity in the test section and snow accumulation thickness on the channel's floor. The results demonstrate that the coupled numerical method of Improved Delayed Detached Eddy Simulation (IDDES) and Discrete Phase Model (DPM) is a reliable tool for analyzing wind-snow flow characteristics within an ice and snow wind tunnel. Furthermore, compared to the vickers curve and bicubic curve, quintic curves applied to the contraction section consistently compress and accelerate airflow. This contributes to a more uniform flow characterized by lower stream-wise fluctuation levels, pitch angles, and yaw angles in the test section, thereby significantly enhancing the overall flow quality of wind and snow. Thus, the quintic curves or smoother curves are recommended for the design of the contraction section in ice and snow wind tunnels. Moreover, increasing the deflector number leads to a noticeable improvement in flow quality inside the test section, while resulting in increased snow accretion on the windward surfaces of deflectors. Hence, a medium-level deflector density is suggested for designing ice and snow wind tunnels to achieve a better balance between flow quality and the additional snow accretion inside the channel.

Temperature field reconstruction based on femtosecond laser prepared of multiwavelength fibre bragg grating array

Temperature field measurements are of great significance in industrial production, scientific research, and other fields. Contact temperature measurements usually achieve high spatial resolution by increasing the layout density of the sensors. However, in practical applications, achieving high-density sensor placement is often difficult. Therefore, when the number of sensors is limited, it is necessary to perform function fitting or interpolation of the temperature of the sampling points to reconstruct the temperature field distribution. This study proposed a temperature field reconstruction method based on femtosecond laser prepared multiwavelength fibre Bragg grating (FBG) array. A multiwavelength FBG array was prepared using the femtosecond laser phase mask method combined with stress stretching, and applied for measuring the temperature field distribution in a tubular high-temperature furnace. Cubic spline interpolation and backpropagation (BP) neural networks were used to construct two-dimensional temperature field models for the temperature field distribution data measured by the FBGs, and the prediction accuracies of the two models were compared. The test results show that the root mean square error of the temperature field distribution constructed using the BP neural network is 0.7333 °C, which is approximately 23.18% of the predicted results of the cubic spline interpolation model, indicating that it is a high-precision temperature field reconstruction method.

T‐Skeleton: Accurate scene text detection via instance‐aware skeleton embedding

AbstractExisting segmentation‐based methods have made considerable progress in arbitrarily shaped text detection due to the advantage of dealing with shape variation. However, there still exist challenges to detecting accurate text instances with dense layouts, inaccurate annotations, and complex backgrounds. Many recent works have focused on improving arbitrary boundary prediction, but it may be difficult to accurately distinguish each instance of dense layouts because their boundary pixels may be mistakenly classified to produce inaccurate results (i.e., adhesive texts) with inaccurate annotation and complex backgrounds. Considering the local and long‐range dependencies, this paper proposes an efficient text detector, namely T‐Skeleton, to obtain more reliable segmentation detections. In the spirit of object skeletonization, we introduce the text instance skeleton highlighting the semantically significant structure (similar to the skeleton of a fish) to explicitly capture the long‐range dependencies of text instances. The key idea of T‐Skeleton is to calibrate the coarse text proposals by embedding text instance skeletons to separate crowd texts accurately and robustly. We further design a channel attention module to enlarge the performance margin between T‐Skeleton and the segmentation baseline. Experimental results on four publicly available datasets show the superiority of T‐Skeleton in handling long and curved texts.

Representing the effects of building height variability on urban canopy flow

AbstractWe conducted large‐eddy simulations over 98 urban arrays with varying building densities and height distributions. Compared with uniform‐height urban arrays, the influence of height variability on urban flow is pronounced and acts differently in two idealized urban configurations: the low buildings induce higher wind speed and stronger turbulence over staggered arrays but act inversely over aligned building configurations. The flow motions around tall buildings generate strong dispersive fluxes, which are sometimes of similar magnitude to the turbulent momentum flux and responsible for a persistent isolated roughness flow pattern in the upper canopy regardless of the urban density. Tall buildings further contribute disproportionately to the form drag of the urban surface, reaching up to 3.9 times the form drag induced by buildings of height equal to the average building height, in dense layouts. The flow inflection points—that is, the largest wind‐speed gradient that defines the aerodynamic interface between the urban canopy flow and the surface layer flow above—are found to be displaced to the maximum building height if less than 25% of buildings are below the mean building height. These findings provide critical insight for the development of urban canopy models, where the impacts of height variability on flow are often linked to the vertical variation in urban density alone. To address this deficiency, we provide a case study that considers the drag amplification due to the impact of vertical urban structures in the urban canopy model, enabling high‐resolution regional climate models to reproduce urban air flows better.

Occurrence City, Bangladesh of Street Crimes in Dhaka

This research looks on the complex relationship between spatial planning aspects and the prevalence of street-level criminal activity in Dhaka. The study investigates the relationship between the built environment and street crime by conducting a thorough examination of elements such as street layout, illumination, land use, and population density. This study gives a nuanced viewpoint by employing a mixed-methods approach that includes a survey of 400 inhabitants and a series of in-depth interviews with urban planners, architects, and law enforcement officials. The data show a strong link between spatial planning components and the occurrence of street crime in Dhaka. Poorly planned thoroughfares and inadequate illumination, in particular, emerge as key causes to these incidents. This study proposes a proactive agenda for urban designers and policymakers as a key takeaway: the importance of properly built urban places with appropriate illumination. The report believes that by doing so, Dhaka City may make considerable advances in reducing street-level criminal activity.

Shell Deformation During the Construction of Record Span Soil-steel Buried Structure in Ras-Al-Khaimah (UAE)

Abstract The algorithm presented in this paper concerns the processing of data in the form of coordinates of measurement points located around the structure periphery, obtained from the geodetic measurements. The geometric parameter used here to study the deformation of the steel shell is the change of curvature. It is used to estimate the bending moment and hence the normal stress in the corrugated steel shell. The results given in the examples of calculations of the analyzed structure show the possibility of determining places with extreme values. For this purpose, a dense layout of measuring points and use the precision geodesy technique is necessary. Of significant importance in stress estimation is the correction of the geodetic measurement base. This is due to the fact that the points in the initial measurement do not lie on a section of the circle as a reference curve, used to determine the deformation of the shell.

The Effect of Product Quality and Store Atmosphere on Purchase Decisions at Otsky Bandar Lampung Distro

Today's society realizes that clothing is more than just clothing needs, but also fashion needs. The shift in clothing style to being a medium to show one's existence in the community has made the clothing business grow rapidly today. Distro is one of the many apparel businesses that have sprung up in Indonesia today, especially in the city of Bandar Lampung. Otsky is a local clothing distribution that is popular with the people of Lampung. Otsky's shop has good product quality and a good store atmosphere. On the other hand, the researchers conducted a survey and found several complaints from consumers about unsatisfactory product quality in terms of materials and product form. Apart from that, there are complaints about the shop atmosphere at Otsky, which has a reasonably dense layout so that it fills the room which affects convenience when shopping. This study aims to determine whether product quality and store atmosphere can influence purchasing decisions at Otsky Stores. The research method used is quantitative, namely a process of finding knowledge that uses data in the form of numbers as a tool to analyze information about what you want to know. This study using a survey method by distributing questionnaires to Otsky Shop buyers. The population of this study were buyers of Otsky Stores in Bandar Lampung and 100 respondents were taken. The results of this study indicate that product quality (X1) and store atmosphere (X2) influence purchasing decisions (Y). The store atmosphere variable shows a result of 0.490, which is higher than the product quality variable, which has an impact of 0.447 on purchasing decisions.

Layout Optimization Algorithms for the Offshore Wind Farm with Different Densities Using a Full-Field Wake Model

To decrease the power deficit of a wind farm caused by wake effects, the layout optimization is a feasible way for the wind farm design stage. A suitable optimization algorithm can significantly improve the quality and efficiency of the optimization process. For exploring the high-performance algorithms under different layout densities, a comparison is conducted by optimizing the layout of a real offshore wind farm with five algorithms, namely two population-based algorithms and three single-point algorithms. Wake effects are considered by a full-field wake model. A penalty function is proposed for the population-based algorithms to handle the constraint violations. Different iterations and constraints of the layout density are applied in the optimization. The random search has the best optimization results in all the cases and the control of the feasibility check is necessary for this algorithm. More iterations can advance the optimization results. The density constraint greatly affects the computational cost of the random search, which is significantly increased under the strict constraint. Except under the strict constraint, the random search has the best performance of optimization efficiency. A combination of the pattern search and random search is recommended when the strict constraint is applied in the layout optimization.

Design of a microfluidic device for immunoaffinity-based isolation of circulating tumor cells with minimal clogging

Combining bioaffinity-based techniques with microfluidics is an effective strategy for the selective isolation of rare circulating tumor cells (CTCs) among peripheral blood cells. In this scope, designing a microfluidic channel with high cell-surface interaction is crucial, which can be realized by increasing surface area via micropillars. In such microfluidic channels, the interpillar distance represents a critical design parameter, and the value is decided considering the trade-off between the possibility of clogging and CTC capture efficiency. In this study, a curvilinear microfluidic channel with a wide (150 µm) interpillar distance was developed to prevent clogging while maintaining high CTC capture efficiency. Computational fluid dynamics was used to compare the residence time of particles in the designed channels. For the proof-of-concept study, microfabricated channels were biofunctionalized for immunoaffinity-based isolation of CTCs, using anti-EpCAM antibodies. Enhanced CTC capture was enabled through the micropillars inside the channels helping the increased encounters between the cells and the antibody-functionalized surface. The curvilinear channel effectively isolated cells from MCF-7 breast cancer cell line among white blood cells, with more than 85% capture efficiency. The rate of non-specific binding of white blood cells remained below 20%. This study demonstrated the ability to increase the interactions between particles and surfaces without requiring a dense layout of the micropillars inside the microchannel, therefore minimizing the clogging possibility of the channel without sacrificing performance.

Spatiotemporal path tracking via deep reinforcement learning of robot for manufacturing internal logistics

The development of engineering technology, the logistics system composed of wheeled mobile robots (WMR) and automated guided vehicles (AGV) have been widely used in industrial scenes. However, traditional manufacturing scenes with dense layout, such as weaving workshops, have higher requirements for automatic transportation of materials. How to realize the intelligent transportation and management of materials in the manufacturing workshop and balance the efficiency and safety of material processing and transportation is still a great challenge. To address this problem, we designed a logistics system based on cloth-roll handling robot (CHR) and its path tracking hybrid deep reinforcement learning (DRL) considering spatiotemporal efficiency and safety in weaving workshop. This research first focuses on the design of a dynamic observation Markov decision-making process that integrates scene features. Further, a deep reinforcement learning considering the heterogeneity of observation data is proposed to obtain the optimal action solution. Then, a distributed scenarios training is implemented to improve the interaction ability between agents and the environment in complex scenes. In addition, the balance between dynamic observation and on-site calculation is considered in the path tracking for actual weaving workshop.

Dynamic mode structure analysis of the near-wake region of a Savonius-type hydrokinetic turbine

Hydrokinetic turbine is a clean technology that can effectively use tidal energy, the Savonius-type runner is very suitable for natural flows, and has been widely used in tidal energy power stations. The dynamic structure of the flow field in the near-wake region downstream has strong impact on the dense layout of the turbine, but there has been no in-depth exploration till now. To explore the potential for beneficial interactions between turbines, this study conducted numerical simulations of Savonius-type turbine, combining fast Fourier transformation and Dynamic mode decomposition to conduct in-depth analysis of the velocity fluctuation frequency distribution and dynamic mode in near-wake region, and compared the advantages and disadvantages of the two methods. This research obtained the distribution of two main frequencies in the near-wake region and clarified their excitation sources. The frequencies of turbines are mixed in the far field, greatly affects the far-field flow state in the near-wake region. The DMD method has great advantages in flow field analysis, as it does not require prior knowledge of flow field compared to FFT method. The conclusions of this study provide new considerations for large-scale arrangement of turbine units, and provide a new method for the flow state analysis.

Large-scale agricultural greenhouse extraction for remote sensing imagery based on layout attention network: A case study of China

Rapid and accurate agricultural greenhouse extraction with remote sensing imagery is essential for providing spatial information for precision agriculture. Benefiting from local spatial perception, deep learning based object extraction methods have achieved satisfactory performances in extracting geo-objects. However, they fail to work for large-scale greenhouse extraction since the objects are sparsely distributed in the background and densely distributed in the foreground, where the local spatial perception causes redundant computation and false detection problems. In this paper, we propose a layout attention network (LANet) framework for large-scale greenhouse extraction using remote sensing imagery, which replaces the local spatial perception with spatial layout perception, i.e., a sparse global layout to identify the sparse background and a dense local layout to identify the dense foreground. To address the shortcoming of the sparse background, which leads to redundant computation, a sparse global layout awareness module is formulated as a scene classifier. This accommodates the global layout attention map of the global scene features by adopting a layout-shared convolutional neural network (CNN) backbone for generating class-agnostic layout priors and global channel attention for aggregating discriminative global layout features, ensuring robust sparse background identification. Then, to alleviate the problem of the dense foreground, which causes false detection, a dense local layout awareness module is proposed to incorporate the local layout attention map and rotated region of interest (RRoI) features. The RRoI features are then further embedded to guide the initial RRoIs for object location refinement by aligning the initial RRoI locations in a layout-sensitive attention mechanism and achieving semantic enhancement by taking the local layout density as a semantic prior to assign a reliable class score map. The experimental results obtained on an agricultural greenhouse benchmark dataset and a large-scale agricultural greenhouse extraction dataset illustrate that the proposed framework can outperform the state-of-the-art object extraction methods in both speed and accuracy, and has a high generalization ability for large-scale dense object extraction.

Analysis of Influence of Boundary Points Density on Precision of Sea Plot Area

In order to improve the area accuracy of the sea plot, the formula of the influence of the density of the graphic boundary points on the area accuracy is deduced and stripped. The conditions of the different values of the vertex angle of the boundary points to improve the area accuracy are analyzed separately. The values of the area accuracy of different sea plot under different distribution densities are deduced and simulated. The results show that the more insertion points on the Sea plot line boundary line, the higher the area accuracy. Under the condition that the boundary point accuracy is 0.1m and the error limit of the sea plot area is 100m2, when the area of the Sea plot with a width : length of 1:4 is greater than 9 hm2 and the area of the Sea plot with a width : length of 1:1 is greater than 25 hm2, it is necessary to consider the insertion point to improve the area accuracy. The maximum relative area error of the oil and cable pipeline sea plot is 3.5‰, taking into account the area accuracy of the cable pipeline sea plot and the actual workload, the insertion point interval of 100 ~ 200 m is selected. The formula and quantitative results derived in this paper can be used as a reference for the layout density of sea plot boundary sites.

Thrust characteristics of nano-carbon/Al/oxygenated salt nanothermites for micro-energetic applications

Combustion within small motors is key in the application-specific development of nanothermite-based micro-energetic systems. This study evaluates the performance of nanothermite mixtures in a converging-diverging nozzle and an open tube. Mixtures were prepared using nano-aluminum (n-Al), potassium perchlorate (KClO4), and different carbon nanomaterials (CNMs) including graphene-oxide (GO), reduced GO, carbon nanotubes (CNTs) and nanofibers (CNFs). The mixtures were packed at different densities and ignited by laser beam. Performance was measured using thrust measurement, high-speed imaging, and computational fluid dynamics modeling, respectively. Thrust, specific impulse (ISP), volumetric impulse (ISV), as well as normalized energy were found to increase notably with CNM content. Two distinctive reaction regimes (fast and slow) were observed in combustion of low and high packing densities (20% and 55%TMD), respectively. Total impulse (IFT) and ISP were maximized in the 5% GO/Al/KClO4 mixture, producing 7.95 mN·s and 135.20 s respectively at 20%TMD, an improvement of 57% compared to a GO-free sample (5.05 mN·s and 85.88 s). CFD analysis of the motors over predicts the thrust generated but trends in nozzle layout and packing density agree with those observed experimentally; peak force was maximized by reducing packing density and using an open tube. The numerical force profiles fit better for the nozzle cases than the open tube scenarios due to the rapid nature of combustion. This study reveals the potential of GO in improving oxygenated salt-based nanothermites, and further demonstrates their applicability for micro-propulsion and micro-energetic applications.

Quasi-static test study of tunnel with resistance-limiting shock absorption layer in high-intensity seismic

The Sichuan-Tibet Railway is faced with risks of active faults, unfavorable geological conditions, high in-situ stress levels, and a high potential for Traditional tunnel seismic measures that can no longer guarantee the safety of tunnel structures in high-intensity earthquake areas. The new shock absorption capacity layer with resistance-limiting is proposed in this paper and the resistance-limiting shock absorption principle. To study the safety of the new anti-shock lining structure, a large-scale quasi-static model test was carried out based on the improved static-dynamic coupling shear force. The test analyzes the response rules of strain, structural internal force, and lining failure form of tunnel lining, taking into consideration three influencing factors including layer layout position, layout density, and tunnel buried depth. The results showed that: 1) Under the action of low-cycle reciprocating shear strain, the failure mode of the shallow buried tunnel is mainly the tensile failure of the arch waist and the failure of the arch waist and the side wall, and the failure mode of the deeply buried tunnel is mainly the compression failure of the arch waist; 2) Compared with the case of no shock absorption layer, the lining tensile stress on the inner side of the arch waist position is significantly reduced. Under the high shear strain (0.20%), the increased tensile stress trend was slowed down on the inner side walls; 3) The main working area of the resistance-limiting layer can effectively improve the lining stress distribution underground vibration and protects the tensile damage on the arch waist to the side wall. The width and depth of the crack are weakened and the seismic bearing capacity of the width and depth of the crack is weakened and the seismic bearing capacity of the lining structure is greatly strengthened; 4) The lining cracks without the resistance limiting layer develop violently, and the crack at the arch waist runs The lining structure failure mode of the resistance limiting layer arranged at the arch waist is similar to The lining structure failure mode of the resistance limiting layer.

Research on the Application of Fracture Water to Mitigate the Thermal Imbalance of a Rock Mass Associated with the Operation of Ground-Coupled Heat Pumps

Shallow geothermal energy is a clean and effective form of energy that can overcome the problems associated with the depletion of carbon-based energy carbon emissions. Due to the special hydrogeological conditions in karst regions, the heat transfer between heat exchange boreholes and the ground formation is a complicated, multi-physical process. The abundant groundwater flow plays an important role in the heat transfer process, and even presents an opportunity to mitigate the heat imbalance during the long term operation of ground-coupled heat pumps (GCHP). In this study, both laboratorial experiments and numerical simulations were performed to analyze the mechanism that shows how fracture water impacts on heat capacity and the thermal imbalance of the energy storage rock mass. The results showed that the overall temperature fluctuation of the rock mass was reduced by the fracture water, and the temperature curve with time became gentler, which means in practice that the heat imbalance in the rock mass could be delayed. However, the temperature contour map showed that the impact of the fracture water flow was constrained in the nearby areas and decreased obviously with distance. The temperature field was also dragged along the direction of the fracture water flow. During the shutdown period, the fracture water significantly enhanced the thermal recovery ability of the rock mass. The results will assist in further understanding the mechanism of heat transfer and energy balance in a rock mass with fracture water flow. It is proposed that the U pipes should be located at zones with abundant fracture water if the construction condition permits. U pipes that are near the fractures should share more of the load or a denser layout could be possible as their heat transfer capacity is improved by the water flow.

Remote Sensing Image Segmentation of Mariculture Cage Using Ensemble Learning Strategy

In harbour areas, the irrational layout and high density of mariculture cages can lead to a dramatic deterioration of the culture’s ecology. Therefore, it is important to analyze and regulate the distribution of cages using intelligent analysis based on deep learning. We propose a remote sensing image segmentation method based on the Swin Transformer and ensemble learning strategy. Firstly, we collect multiple remote sensing images of cages and annotate them, while using data expansion techniques to construct a remote sensing image dataset of mariculture cages. Secondly, the Swin Transformer is used as the backbone network to extract the remote sensing image features of cages. A strategy of alternating the local attention module and the global attention module is used for model training, which has the benefit of reducing the attention computation while exchanging global information. Then, the ensemble learning strategy is used to improve the accuracy of remote sensing cage segmentation. We carry out quantitative and qualitative analyses of remote sensing image segmentation of cages at the ports of Li’an, Xincun and Potou in Hainan Province, China. The results show that our proposed segmentation scheme has significant performance improvement compared to other models. In particular, the mIoU reaches 82.34% and pixel accuracy reaches 99.71%.