Geometry Factors Research Articles

Prediction of Jacking Force in Vertical Tunneling Projects Based on Neuro-Genetic Models

The vertical tunneling method is an emerging technique to build sewage inlets or outlets in constructed horizontal tunnels. The jacking force used to drive the standpipes upward is an essential factor during the construction process. This study aims to predict the jacking forces during the vertical tunneling construction process through two intelligence systems, namely, artificial neural networks (ANNs) and hybrid genetic algorithm optimized ANNs (GA-ANNs). In this paper, the Beihai hydraulic tunnel constructed by the vertical tunneling method in China is introduced, and the direct shear tests have been conducted. A database composed of 546 datasets with ten inputs and one output was prepared. The effective parameters are classified into three categories, including tunnel geometry factors, the geological factor, and jacking operation factors. These factors are considered as input parameters. The tunnel geometry factors include the jacking distance, the thickness of overlaying soil, and the height of overlaying water; the geological factor refers to the geological conditions; and the jacking operation factors consist of the dead weight of standpipes, effective overburden soil pressure, effective lateral soil pressure, average jacking speed, construction hours, and soil weakening measure. The output parameter, on the other hand, refers to the jacking force. Performance indices, including the coefficient of determination (R2), root mean square error (RMSE), and the absolute value of relative error (RE), are computed to compare the performance of the ANN models and the GA-ANN models. Comparison results show that the GA-ANN models perform better than the ANN model, especially on the RMSE values. Finally, parametric sensitivity analysis between the input parameters and output parameter is conducted, reaching the result that the height of overlaying water, the average jacking speed, and the geological condition are the most effective input parameters on the jacking force in this study.

Safety evaluation of multiple horizontal curves using statistical models

Road safety is an important aspect of road transportation. Safety evaluation of highways helps engineers in prioritising them for safety improvement and for evaluating the effectiveness of the improvement measures. Crash prediction models are very useful for evaluating the safety levels of highway elements. Many studies reported the effect of geometry and traffic factors on safety at simple (single) horizontal curves. But the situation becomes more complex when multiple horizontal curves occur. The Highway Safety Manual also does not provide a safety performance function on multiple horizontal curves. Hence, this study aims to quantify the influence of geometric characteristics of the preceding curve on crashes and develop models for evaluation of the safety performance of multiple horizontal curves on two-lane non-urban roads. The data required for this study include crash, geometric, and traffic data from 102 multiple horizontal curves.

Safety evaluation of multiple horizontal curves using statistical models

Road safety is an important aspect of road transportation. Safety evaluation of highways helps engineers in prioritising them for safety improvement and for evaluating the effectiveness of the improvement measures. Crash prediction models are very useful for evaluating the safety levels of highway elements. Many studies reported the effect of geometry and traffic factors on safety at simple (single) horizontal curves. But the situation becomes more complex when multiple horizontal curves occur. The Highway Safety Manual also does not provide a safety performance function on multiple horizontal curves. Hence, this study aims to quantify the influence of geometric characteristics of the preceding curve on crashes and develop models for evaluation of the safety performance of multiple horizontal curves on two-lane non-urban roads. The data required for this study include crash, geometric, and traffic data from 102 multiple horizontal curves.

Fracture resistance of railway ballast rock under tensile and tear loads

The influence of loading type on tensile and tearing fracture resistance of ballast rock was assessed using edge-notched diametrically compressed disc (ENDC) and edge-notched disc bend (ENDB) test geometries. The geometry of these two specimens was similar; however, their loading type (i.e., three-point bend and diametral compressive) was different affecting the geometry factors. The obtained pure tensile fracture toughness (KIc) using the ENDB test was higher than the ENDC test. In contrast to tensile fracture toughness, the pure tearing fracture toughness (KIIIc) in the ENDC test was higher than the ENDB fracture test. The obtained experimental data were explained in terms of crack propagation path, since two distinct trajectories were observed for both configurations under tearing deformation.

Monte Carlo simulation of a satellite-based detector of cosmic ray ions with elemental separation from hydrogen to nickel

Observing cosmic rays and solar energetic particles provides important information about the solar wind and solar storms. We are working toward building a Thai detector of energetic ions from space that is inspired by the Mass Spectrometer Telescope (MAST), a satellite-based detector installed on SAMPEX of cosmic ray ions with the energy range of 0.01 to 0.5 GeV/nucleon with the objective to determine the nuclear charge and kinetic energy for nuclei with atomic number of Z = 1 (hydrogen) to 28 (nickel). The energy range of the detector covers the energy range of anomalous cosmic rays, Galactic cosmic rays and solar energetic particles. Therefore, observations by such a detector can provide insight into the origin and transport of these ions in cosmic rays and solar energetic particles. During solar events, measurements of the elemental composition of solar energetic particles can be compared with the composition of the solar corona. We have created a computational model of the MAST detector to simulate ion detection using the FLUKA program to measure the energy deposition of heavy ions in multiple detector components to determine their initial kinetic energy in the simulation. From the simulation results, we can identify the ions’ energies and species using established methods and calculate the geometry factor of the detector, comparing the results with previous reports.

Design and Decomposition Analysis of Mixing Zone Structures on Flame Dynamics for a Swirl Burner

The recirculation zone and the swirl flame behavior can be influenced by the burner exit shape, and few studies have been made into this structure. Large eddy simulation was carried out on 16 cases to distinguish critical geometry factors. The time series of the heat release rate were decomposed using seasonal-trend decomposition procedure to exclude the effect of short physical time. Dynamic mode decomposition (DMD) was performed to separate flame structures. The frequency characteristics extracted from the DMD modes were compared with those from the flame transfer functions. Results show that the flame cases can be categorized into three types, all of which are controlled by a specific geometric parameter. Except one type of flame, they show nonstationary behavior by the Kwiatkowski–Phillips–Schmidt–Shin test. The frequency bands corresponding to the coherent structures are identified. The flame transfer function indicates that the flame can respond to external excitation in the frequency range 100–300 Hz. The DMD modes capture the detailed flame structures. The higher frequency bands can be interpolated as the streamwise vortices and shedding vortices. The DMD modes, which correspond to the bands of flame transfer functions, can be estimated as streamwise vortices at the edges.

Spatial analysis of the impact of urban geometry and socio-demographic characteristics on COVID-19, a study in Hong Kong

The World Health Organization considered the wide spread of COVID-19 over the world as a pandemic. There is still a lack of understanding of its origin, transmission, and treatment methods. Understanding the influencing factors of COVID-19 can help mitigate its spread, but little research on the spatial factors has been conducted. Therefore, this study explores the effects of urban geometry and socio-demographic factors on the COVID-19 cases in Hong Kong. For each patient, the places they visited during the incubation period before going to hospital were identified, and matched with corresponding attributes of urban geometry (i.e., building geometry, road network and greenspace) and socio-demographic factors (i.e., demographic, educational, economic, household and housing characteristics) based on the coordinates. The local cases were then compared with the imported cases using stepwise logistic regression, logistic regression with case-control of time, and least absolute shrinkage and selection operator regression to identify factors influencing local disease transmission. Results show that the building geometry, road network and certain socio-economic characteristics are significantly associated with COVID-19 cases. In addition, the results indicate that urban geometry is playing a more important role than socio-demographic characteristics in affecting COVID-19 incidence. These findings provide a useful reference to the government and the general public as to the spatial vulnerability of COVID-19 transmission and to take appropriate preventive measures in high-risk areas.

Driving simulators to evaluate road geometric design effects on driver behaviour: A systematic review

Several factors can influence driver behaviour, and road geometry is one of them. A better understanding of driver-roadway interaction can enhance road design to create a safer traffic system. In this context, driving simulators are powerful tools that combine convenience and effectiveness in identifying drivers' responses to different geometry factors. In this paper, a systematic review following a Prisma guideline was conducted on driving simulator studies that examined the effects of road geometry on driver behaviour to reveal the current procedures adopted in this field and their main findings. A systematic search of eleven databases was performed covering six years of research results. Inclusion of relevant studies focused on horizontal curves, a topic identified as the most cited, extended this period. The results revealed significant heterogeneity in relation to the measured variables and deficiencies when reporting the experiment, which prevented a meta-analysis of the studies' outcomes. Despite this, a discussion of the potential of driving simulators to contribute to several road safety research gaps is presented. In addition, problems of a lack of standardisation in the performance of the experiments were detected, potentially influencing the findings of the studies. However, the results also suggest that experiments that followed good experimental practices observed effects on driver performances not detected by other studies.

On the comparison of two mixed-mode I + III fracture test specimens

Towards measuring the mixed-mode I + III fracture toughness independent of geometry and loading type, two test specimens were numerically and experimentally compared. The capabilities of edge-notched disc bend (ENDB) and edge-notched diametrically compressed disc (ENDC) fracture test specimens were compared in producing the full range of mixed-mode I + III. Although the geometry of both specimens was similar, the difference of their loading type (i.e., bending and compression) noticeably affected the mixed-mode I + III fracture parameters. The existence of mixed-mode I + III fracture in the crack front of the ENDC specimen was more stable than the ENDB specimen. However, the variation of mode mixities ratio in the ENDC specimen was more sensitive to the rotation of the crack inclination angle than the ENDB specimen. The map of T-stress as the function of mixed-mode I + III geometry factors plotted for both specimens. There was an optimal crack length in the ENDB specimen by which the full range of mixed-mode I + III fracture toughness can be measured independent of geometry and loading type effects. While for the ENDC specimen, the optimum crack length only existed for pure mode III. The full range of mixed-mode I + III fracture toughness tests were performed using both test specimens. The corresponding fracture loads and fracture initiation angles were also obtained for both ENDB and ENDC specimens made of granite rock. The magnitude of pure mode I fracture toughness measured by the ENDB specimen was greater than the ENDC specimen. Conversely, the pure mode III fracture toughness measured by the ENDC specimen was greater than the ENDB specimen. These discrepancies were also predicted by the computed T-stress map. In addition to the T-stress, Tz, process zone size, and the stress triaxiality constraints, which governed the crack propagation path were other effective parameters on the difference between mixed-mode I + III fracture toughness values measured via both specimens.

Application of Adaptive Image Receive Coil Technology for Whole-Brain Imaging.

OBJECTIVE. The Adaptive Image Receive (AIR) radiofrequency coil is an emergent technology that is lightweight and flexible and exhibits electrical characteristics that overcome many of the limitations of traditional rigid coil designs. The purpose of this study was to apply the AIR coil for whole-brain imaging and compare the performance of a prototype AIR coil array with the performance of conventional head coils. SUBJECTS AND METHODS. A phantom and 15 healthy adult participants were imaged. A prototype 16-channel head AIR coil was compared with conventional 8-and 32-channel head coils using clinically available MRI sequences. During consensus review, two board-certified neuroradiologists graded the AIR coil compared with an 8-channel coil and a 32-channel coil on a 5-point ordinal scale in multiple categories. One- and two-sided Wilcoxon signed rank tests were performed. Noise covariance matrices and geometry factor (g-factor) maps were calculated. RESULTS. The signal-to-noise ratio, structural sharpness, and overall image quality scores of the prototype 16-channel AIR coil were better than those of the 8-channel coil but were not as good as those of the 32-channel coil. Noise covariance matrices showed stable performance of the AIR coil across participants. The median g-factors for the 16-channel AIR coil were, overall, less than those of the 8-channel coil but were greater than those of the 32-channel coil. CONCLUSION. On average, the prototype 16-channel head AIR coil outperformed a conventional 8-channel head coil but did not perform as well as a conventional 32-channel head coil. This study shows the feasibility of the novel AIR coil technology for imaging the brain and provides insight for future coil design improvements.

Homogenous asymptotic analysis on vibration energy dissipation characteristics of periodical honeycomb reinforced composite laminate filled with viscoelastic damping material

In this paper, free transverse vibration energy dissipation properties of honeycomb reinforced composite laminated structures are studied. By applying the homogenous asymptotic method (HAM) and representative unit cell (RUC) approach, considering the frequency- and temperature-dependent properties of the viscoelastic damping material (VDM), the constitutive equations of the laminated composite structure is obtained. Based on the transverse wave energy propagation and transmission theory in solid structures, the structural loss factor (SLF) of the composite structure can be ultimately determined, which is a frequency- and temperature-dependent variable according to the same properties of VDM’s physical parameters that were applied. Several geometry factors including the thickness of the VDM layer, the width and the inner angle of the honeycomb reinforcements, influence on the vibration energy dissipation characteristics of the composite structure are investigated qualitatively and quantitatively. The results are validated by the Galerkin method based asymptotic approach, which shows consistency with each other, especially when the external excitation frequency larger than 500 Hz in the considered frequency ranges.

The Effect of External Geometry Factors on the Characteristics of Flow Profiles and Segregation in a Vertical Sinter Cooling Bed

Good particle flow patterns and uniform particle velocity distributions enhance the performance of heat transfer and smooth flow processes in vertical sinter cooling beds (VSCBs). The effect of three typical geometries, conical, curved and rectangular, on the performance of flow profiles and segregation in a VSCB is investigated comparatively and quantitatively based on the discrete element method (DEM). The evolution of flow profiles and particle segregation directly influence the evenly distributed sinter layers and the efficiency of heat exchange in VSCBs. In this research, a 3D packed bed model is established for the three geometry types to quantitatively and qualitatively investigate the influence of structural parameters on the evolution of flow patterns and segregation. The comparison of the effect of the three geometry types on the particle flow process showed that the curved geometry types greatly improve the performance of the flow pattern and size segregation. The height of the mass flow pattern for the curved geometry varies with the structural parameters by 1.5-fold that of the flow pattern for the other two geometry types. The curved geometry dramatically reduces the magnitude of the segregation index (SI) near the sidewall, while this magnitude fluctuates near 1.0 in the central flow passage of the VSCB.

Parametric Study on the Flow Profiles of Vertical Sinter Cooling Bed Using the DEM and Taguchi Method for Waste Heat Recovery

To comprehensively understand the effectiveness of external factors on flow characteristics and realize particle flow distribution evenly in bulk layers is an essential prerequisite for improving the performance of heat transfer in vertical sinter cooling beds (VSCBs). The numerical discrete element method (DEM) was applied to investigate external geometric and operational factors, such as the aspect ratio, geometry factor, half hopper angle, normalized outlet scale, and discharge velocity. Using the Taguchi method, a statistical analysis of the effect of design factors on response was performed. In this study, we focused more on external factors than granular properties, be remodelling the external factors was more useful and reliable for actual production in industries. The results showed that the most important factor was the aspect ratio, followed by the geometry factor, normalized outlet scale, half hopper angle, and discharge velocity for the dimensionless height of mass flow. In terms of the Froude number, the most influential factor was the normalized outlet scale with a contribution ratio of 33.81%, followed by the aspect ratio (22.86%), geometry factor (17.73%), discharge velocity (17.73%), and half hopper angle (11.83%).

A finite element method based comparative fracture assessment of carbon black and silica filled elastomers: Reinforcing efficacy of carbonaceous fillers in flexible composites

This study is focused on numerical investigation on fracture behaviors of carbon black (CB) and silica filled elastomeric composites. Finite element analysis (FEA) in compliance with multi-specimen method is used to calculate J-integral and geometry factor of the rubber composites up to a displacement of 20 mm for single edge notch in tension (SENT) and double edge notch in tension (DENT) specimens. An empirical relationship between crack tip opening displacement (CTOD) and crack advancement is established depending on notch to width ratio (NWR). The stress contours across the notches for SENT and DENT specimens is discussed briefly. It is found that fracture propagation resistance of CB filled elastomer is 125% more than that of silica filled elastomer. Although, Silica filled elastomer have good tensile strength and crosslink density but it fails to replace carbon black in terms of fracture properties. The critical J-integral for CB filled elastomer is 18.7% and 32.2% more than silica filled elastomer for SENT and DENT specimens respectively. The effect of specimen type on various fracture properties is also explored. The factor of safety is found to be significantly more in case of CB filled elastomers making them less vulnerable to crack propagation and catastrophic failure.

The Stellar-INS Navigation Performance Influence Mechanism of Star Vector Orientation in the Field of View

The star sensor field of view varies from several arc-minutes to 20 degrees, which directly determines the star vector orientation in the field of view (FOV). Although the relationship between star vector orientation in the FOV and attitude accuracy has been revealed, the influence mechanism of star vector orientation on the integrated navigation performance of a stellar inertial navigation system has not been analysed. In order to improve the integrated accuracy, the main errors such as star sensor installation error, gyro error and initial platform angle error should be estimated online. It is significant to study the influence mechanism of star vector orientation on estimation of the above errors. In this paper, the star sensor sensitivity and the geometry factor are defined to feature the difference between the optical axis direction and the non-optical axis direction. The formulised mechanism and quantification results between star vector orientation and integration attitude and error estimation accuracy are clearly given. Simulation and ground testing were conducted and it was found that the larger the star vector orientation along the optical axis, the better the error estimation accuracy. In contrast, the attitude accuracy is weakly sensitive to the orientation of the star vector in conditions of appropriate posture adjustment and star observation scheme. This conclusion can offer universal guidance for the design and evaluation of stellar inertial navigation systems with narrow field of view or large field of view star sensors.

Urban traffic accident risk prediction for knowledge-based mobile multimedia service

Traditional accident prediction models have been mostly designed with statistical analysis that finds and analyzes the causal relationships between traffic accidents and a variety of human, road geometry, and environmental factors. However, these statistical methods have limitations in that they are based on assumptions about data distribution and function type. Therefore, this study suggests an accident prediction model using deep learning. This newly suggested risk prediction model is for predicting risk by reflecting static features of the road, such its length and the speed limit on it, and dynamic features of the road, such as traffic volume when driving on it, and the altitude and azimuth of the sun. For this purpose, 4470 accident cases, collected over 5 months from August to December 2018 in Seoul—the most complex, high-traffic, and accident-prone city in Korea—were analyzed. As a result of testing the model using such data, it was found to have an accuracy of 75% and recall of 81%. Based on testing results for the suggested risk prediction model, a system was developed to guide not only accident-prone regions predicted using statistical data but to also guide a risk level for the road. This level of risk is estimated based upon each given situation, so it can change even for the same road. This guide system can be used to provide a level of risk for each road segment and region but also to improve roads with recommendations, such as installation of safety features. In addition, it could support a mobile system that provides a driver with the optimized driving path for safety.

Theoretical Optimization of Trapped-Bubble-Based Acoustic Metamaterial Performance

Acoustic metamaterials have proven to be a versatile tool for the precise control and manipulation of sound waves. One of the promising designs of acoustic metamaterials employ the arrays of bubbles and find applications for soundproofing, blast mitigation, and many others. An obvious advantage of bubble-based metamaterials is their ability to be relatively thin while absorbing low-frequency sound waves. The vast majority of theories developed to predict resonant behavior of bubble-based metamaterials capitalize on Minnaert frequency. Here, we propose a novel theoretical approach to characterize bubble-based metamaterials that are based on our previous findings for a single bubble trapped in circular cavity modeled as a thin clamped plate. We obtain analytical expressions for resonant frequencies of bubble metascreens using self-consistent approximation. Two geometry factors, distance between bubble centers and distance between bubble center and interface of acoustic impedance change, are taken into account. We demonstrate the existence of multiple bandgaps and possibility of switching between them via adjustment of geometry parameters and reflector properties.

A 32-channel receive array coil for bilateral breast imaging and spectroscopy at 7T.

This work describes the construction and evaluation of a bilateral 32-channel receive array for breast imaging at 7T. The receive array consisted of 32 receive coils, placed on two 3D-printed hemispherical formers. Each side of the receive array consisted of 16 receive loops, each loop having a corresponding detachable board with match/tune capacitors, active detuning circuitry, and a balun. Coil performance was evaluated on homogeneous canola oil phantoms using a Philips Achieva 7T system. Array coil performance was compared with a bilateral forced current excitation volume coil in transmit/receive mode and with a previously reported 16-channel unilateral coil with a similar design. The 32-channel array had an increase in average SNR throughout both phantoms by a factor of five as compared with the volume coil, with SNR increases up to 10 times along the periphery and three times in the center. Noise measurements showed low interelement noise correlation (average: 5.4%; maximum: 16.8%). Geometry factor maps were acquired for various acceleration factors and showed mean geometry factors<1.2, for combined acceleration factors of up to six. The improvements achieved demonstrate the clear potential for use in dynamic contrast-enhanced or diffusion-weighted MR studies, while maintaining diagnostically relevant spatial and temporal resolutions.

Anisotropy in volume change behaviour of soils during shrinkage

It has been long recognised that some of the fundamental and engineering properties of soils exhibit a certain degree of anisotropy that eventually dictates their directional geoengineering behaviours. Consideration of the importance of the volume change behaviour of soils during shrinkage and a critical review of the literature suggests scopes for further research for the development of a better understanding of the anisotropy in volume change encountered during soil shrinkage. In this paper, anisotropy in volumetric shrinkage behaviour of soil is depicted with the theory of geometry factor and shrinkage strains. A systematic investigation and analysis on the evolution of geometry factors and shrinkage strains of several geomaterial samples during evaporative dewatering is reported herein. A theoretical framework for evaluating shrinkage geometry factors of a cylindrical soil specimen undergoing volume change during progressive moisture loss is described in this paper. Furthermore, based on experimental and literature data, shrinkage geometry factors of several specimens differing in terms of gradational properties, specimen size, evaporative boundary condition and pore fluid salinity are evaluated and discussed in detail in accordance with the theoretical framework. Linkages between shrinkage process, shrinkages strains and geometry factor are also analysed to underpin the usage of geometry factor and shrinkage strains to characterise anisotropy during soil shrinkage.

An improved method in petrophysical rock typing based on mercury-injection capillary pressure data

ABSTRACT Petrophysical rock typing plays a major role in carbonate reservoir characterization and geological modeling for reservoir simulation. In this study, based on 1120 samples of mercury-injection capillary pressure data, we have analyzed the contributions to rock permeability for the thick Cretaceous carbonate reservoir of Mishrif Formation in H Oilfield in Iraq. The analyses have been carried out for three types of pore-throat frequency distribution, i.e., monomodal, bimodal, and trimodal. The results show that for the bimodal and trimodal samples, the pore-throat frequency distribution of the first pore system contributes more than 95% of rock permeability. Further, the Thomeer function has been used to fit the mercury-injection capillary pressure curve, in which the displacement pressure, pore geometry factor, and bulk volume have been extracted. These three parameters have been utilized to characterize the pore structure and to fit with the rock permeability so as to obtain the reservoir classification parameter Mode. Then, we have established the relationship between permeability and mode, permeability and R35, and the correlation coefficients are 0.81 and 0.75, respectively. And permeability derived from Mode is more accurate than R35. The Modes of 1120 samples have been arranged in ascending order and plotted on the semi-logarithmic scales. After interpolation, derivation, and filtering, five rock types have been divided at the change in slope. The combination of Mode and this slope method is considered an improved method. The classification results of Mode, Winland R35, and Flow Zone Indicator have been compared with those of pore-throat distribution, T2 distribution of nuclear magnetic resonance, and conventional logging responses. The results demonstrate that the classification results of Mode are significantly better than those of Winland R35 and Flow Zone Indicator.