Geometric Design Features Research Articles

Closed Circuit of 3-Dimensional Polymer Powders

This article describes the most important stages of testing the levels of innovative readiness of a new machine and material construction solutions for closed loops of polymer powders in 3D additive manufacturing. The aim of this study was to indicate the state and directions of development of the technology of geometric recycling of polymer powders in 3D additive manufacturing, the need to control the geometric quality of the powders, and the quality of the design of machines for their processing in a closed circuit. The method was aimed at creating a strategy and verifying the stages of development of a new idea for stabilizing the geometric and dynamic design features of polymer powders for additive manufacturing (3D printing). Connections and relationships of the variable design features of powders, machines and devices with variable postulated states of products and processes allowed for the analysis, knowledge, description and development of variables for stabilizing geometric features of polymer powders in recycling. The results show the possibilities of supporting innovative creativity according to the adopted method, allow for determining the level of compliance of the quality of the products of the technical system, the effectiveness of preparatory processes for recycling and the non-toxicity of the products and processes of the new technology and their closed loop. The goal of developing useful design values, according to an integrated method of analysis, assessment and environmental development, was achieved, including the proposal of design features of razor blade shredders, supported by genetic algorithms, and devices for stabilizing polymer powders in additive manufacturing with recycling.

Use of Historical Road Incident Data for the Assessment of Road Redesign Potential

Drivers’ safety and overall road functionality are key triggers for deciding on road interventions. Because of the socioeconomical implications of traffic incidents, either fatal or no, continuous research has been dedicated over the previous decades on the assessment of factors contributing to crash potential. Apart from the behavioral aspects of driving, which are commonly studied through simulation and advanced modelling techniques, the road infrastructure status is of equal or even higher significance. In this study, an approach is presented to discuss the road redesign potentials based on the evaluation of network-level historical incident records from road crashes in Greece. Based on total and fatal crash records, the following infrastructure-related aspects were assessed as critical for the discussion of the road redesign potential needs: the status of road’s surface (i.e., dry, wet, etc.), the issue of improving driving conditions near at-grade intersections, the presence and suitability of signage and/or lighting, and the consideration of particular geometric design features. Overall, it is deemed that intervention actions for at least one of these pillars should aim at enhancing the safety and functionality of roadways.

Selective State DOT Lane Width Standards and Guidelines to Reduce Speeds and Improve Safety

This research investigates the lane width standards and guidelines implemented by various State Departments of Transportation (DOTs) to reduce vehicle speeds and enhance road safety. Lane width reduction is often perceived as a strategy to mitigate speed and improve safety. Still, its effectiveness and implications vary across different contexts, including regions, urban/rural settings, or other geometric design features. Drawing from interviews with five State DOTs and a review of their road design manuals, this study aims to identify suggested lane widths depending on the contexts, design exception process when narrowing or widening lane widths, and introduce representative before/after studies. The findings indicate that State DOTs tend to have lower recommended lane widths in urban areas than in rural areas. Moreover, lane width standards among these states vary due to several factors, including the geographical location of roadways (urban or rural areas), design or posted speeds, traffic volume, road classification, and geometric road design features. Design exceptions are required if the existing or proposed design element is incompatible with both AASHTO and department governing criteria. In conclusion, the findings will provide valuable insights and recommendations for policymakers, transportation planners, and road engineers to inform optimal lane width and decision-making processes.

Examining the Effect of Geometric Design Features on the Speed in Horizontal Curve on Mountain Road

Examining the Effect of Geometric Design Features on the Speed in Horizontal Curve on Mountain Road

‘안도다다오 건축에서 나타난 기하학적 공간 특성’에 관한 연구

This study is a research paper that derives the geometric design characteristics that appear in Tadao Ando's architecture. The purpose of this study is to theoretically analyze Tadao Ando's architecture and geometry and derive those characteristics through examples of recent domestic buildings since 2010 by Tadao Ando. . The method of this study is to study literature related to theory and analyze cases through architectural collections. Based on Tadao Ando's architectural concept and the meaning of geometry, the characteristics of combined geometry, disconnected geometry, and independent geometry were derived. In addition, a building case analysis was conducted based on geometric spatial characteristics. Tadao Ando's architecture is composed of six methods: juxtaposition, separation, expansion, overlap, transformation, and absorption, and the substantial form of space becomes existential meaning through spatial recognition and becomes essential architecture. Based on this study, we hope to develop research into the essential concepts of geometric space characteristics that appear in architectural space.

Comparative Evaluation of Crash Hotspot Identification Methods: Empirical Bayes vs. Potential for Safety Improvement Using Variants of Negative Binomial Models

The empirical Bayes (EB) method is widely acclaimed for crash hotspot identification (HSID), which integrates crash prediction model estimates and observed crash frequency to compute the expected crash frequency of a site. The traditional negative binomial (NB) models, often used to estimate crash predictive models, typically struggle with accounting for the unobserved heterogeneity in crash data. Complex extensions of the NB models are applied to overcome these shortcomings. These techniques also present new challenges, for instance, applying the EB procedures, especially for out-of-sample data. This study applies a random parameter negative binomial (RPNB) model within the EB framework for HSID using out-of-sample data, comparing its performance with a varying dispersion parameter NB model (VDPNB). The research also evaluates the potential for safety improvement (PSI) scores for both models and compares them with EB estimates using three generalised criteria: high crashes consistency test (HCCT), common sites consistency test (CSCT), and absolute rank differences test (ARDT). The results yield dual insights. Firstly, the study highlights associations between crash covariates and frequency, emphasising the significance of roadway geometric design characteristics (e.g., lane width, number of lanes, and parking type) and traffic volume. Some variables also influenced overdispersion parameters in the VDPNB model. In the RPNB model, annual average daily traffic (AADT) and lane width emerged as random parameters. Secondly, the HSID performance assessment revealed the superiority of the EB method over PSI. Notably, the RPNB model, compared to the VDPNB, demonstrates superior performance in EB estimates for HSID with out-of-sample data. This research recommends adopting the EB method with RPNB models for robust HSID.

Geometric parameter design and contact characteristics of beveloid gear and involute cylindrical gear transmission with crossed axes

Geometric parameter design and contact characteristics of beveloid gear and involute cylindrical gear transmission with crossed axes

Traffic Performance of Successive Freeway Merge Segments

At freeway interchanges with high entering flows, implementing two successive merges can improve traffic flow and capacity by distributing the merging maneuvers. The German Guidelines for the Design of Motorways define different types of successive (“double”) merges. According to the quality of service assessment procedure for freeway merge segments given in the German Highway Capacity Manual, successive merge segments can be evaluated separately. However, depending on the distance between the merges, the capacity of the second (downstream) merge might be affected by the entering traffic at the first (upstream) merge, which influences the lane-flow distribution. For a more precise evaluation of traffic flow performance and traffic safety depending on the geometric design characteristics, vehicle interactions, lane changes, the resulting capacity of successive merge segments, accident rates, and crash types were analyzed in the study. The research was based on loop detector data as well as trajectory data obtained from video measurements, which provide an insight into the interactions between mainline and entering vehicles. For the analysis of traffic safety, crash data were evaluated over a period of 3 years. Furthermore, successive merge segments with different geometric and traffic characteristics were modeled with the microscopic traffic simulation tool BABSIM to analyze the influence on traffic flow and capacity. As a result, capacity models and recommendations for the geometric design of successive freeway merge segments are provided.

Analyzing Freeway Safety Influencing Factors Using the CatBoost Model and Interpretable Machine-Learning Framework, SHAP

Exploring and analyzing safety influencing factors can guide targeted traffic safety management. Traditional traffic safety models are aimed at specific data problems and making adjustments to the model structure, which lack focus on predictive ability and have limited information on the analysis of influencing factors. In recent years, machine-learning methods have opened new avenues in modeling that have higher prediction accuracy, can identify complex nonlinear relationships, and can overcome over- and under-dispersion and correlation. Machine-learning methods, however, pose the problem of limited interpretability. The interpretable machine-learning framework SHAP can be an effective solution, which can not only reflect the influence of features in each sample but also generate global interpretation. This study established gradient boosting models including the CatBoost and XGBoost models as traffic safety models, which were compared with a traditional NB regression model and a zero-inflated negative binomial regression model. SHAP was used to analyze several safety influencing factors, including geometric design features, traffic operation characteristics, time of day, and land use. Results confirmed that the CatBoost model has better prediction ability and is a more suitable traffic safety model than the traditional negative binomial regression model. Among the key findings were that ramp type is the most important factor in freeway crash frequency; curve presence has a great positive impact, while truck proportion has a great negative impact; and traffic volume is highly correlated with truck proportion. These findings can provide theoretical support for safety operation management and targeted improvement measures for freeways.

Analysis of the Effects of Highway Geometric Design Features on the Frequency of Truck-Involved Rear-End Crashes Using the Random Effect Zero-Inflated Negative Binomial Regression Model

Statistical data indicate that trucks are more prone to rear-end crashes, making this an area of concern. The objective of this study is to create a model that analyzes the factors influencing the frequency of rear-end crashes involving trucks (TIRC). To achieve this, researchers identified the most appropriate model as Spatial Zero-Inflated Negative Binomial Regression (SZINB). This model takes into account spatial correlation, which plays a significant role in the occurrences of TIRC on different road segments supervised by each highway ward. The estimation of parameters in the SZINB model has led to key findings that shed light on the factors contributing to a higher likelihood of TIRC. These findings include the increased probability of TIRC on curved roads compared to straight ones, roads that feature open middle islands, six lanes per direction, a slope, right-of-way shoulder width, pavement type, lane width, and a post speed limit. Based on these key findings, this study developed policy recommendations and sample measures aimed at reducing the frequency of TIRC. Implementing measures such as improving the road design on curved sections, optimizing middle islands, and enhancing traffic management on wider roads can help mitigate the risk of crashes involving trucks.

Attenuation of Detrimental Hub Leakage Effects in an Axial Compressor Rotor by Customized Geometrical Design Features

Abstract The aerodynamic impact of hub gap leakage on the performance characteristics of an axial compressor rotor in conventional design (no blisk) with a high hub-to-tip ratio has been investigated using three-dimensional steady-state Reynolds-averaged Navier–Stokes simulations. The inclusion of circumferential hub gaps in front of the leading edge and after the trailing edge, as well as inter-platform leakage, reduced the total pressure ratio and the polytropic efficiency of the rotor by as much as 3.74% and 3.97%, respectively, compared to a design case with clean endwalls. Potential design recommendations in terms of improved aerodynamic robustness against leakage effects were derived from the separate sealing of each hub gap. Six geometry modifications were assessed, which based on these results. In a throttled operating condition, large edge radii in the front gap on the disk and platform partially recovered the initial losses of both the total pressure ratio (17.7%) and polytropic efficiency (19.6%). A circular lateral platform shape with the opening pointing toward the blade’s pressure side showed superior loss recovery capabilities at a dethrottled operating point. The combination of both features did not reduce the losses further. However, the circular lateral platform shape combined with smaller front gap chamfers proved more beneficial in a throttled state.

Lichens as bio-monitors of polycyclic aromatic hydrocarbons: Measuring the impact of features and traffic patterns

The role of road characteristics, including gradient and speed control devices, in influencing emission dynamics remains to be fully elucidated. Most studies have focused on fuel consumption as an indirect indicator of sector emissions instead of directly quantifying specific pollutants, like polycyclic aromatic hydrocarbons (PAHs). This research approach is often due to the complexities involved in capturing these pollutants and their subsequent analysis. Bio-monitors, such as lichens, offer an economically viable method. Their wide distribution across various habitats enables the comparison of PAH levels in diverse environments. Against this background, The present work analyses the ability of tropical lichens to indicate the effect that traffic patterns and geometric design features of roads (traffic activity, road gradient, traffic control devices, and vehicular speed) have on the emission of PAH concentration. Results showed that PAHs in lichens strongly correlated with the road gradient (Spearman correlation, p<0.005 with R=0.98). Each 1% increase in road gradient implies a rise of 24 ngPAH/gLichen in National Road. Additionally, a trend coherent of PAH concentration with the vehicle speed profile was observed on Panamericana Road. Speed control devices were associated with higher concentrations of PAHs due to acceleration and braking actions that increment fuel consumption. Finally, the results evidenced that lichens helped determine the source of aromatics and their carcinogenic potential using the diagnostic ratio of PAHs and the carcinogenic equivalence sum, respectively.

Effect of 3D blade design on the aerodynamic, aeroelastic and structural behavior of a scaled UHBR fan

In this paper, the effect of a 3D blade design on the aerodynamic, aeroelastic and structural behavior of a scaled UHBR fan is investigated numerically. First, an initial sensitivity analysis for the geometrical design features sweep and lean as well as an adaption of the thickness position in the fan hub region is conducted. Positive sweep is found to benefit the total pressure ratio, while positive lean improves the polytropic efficiency of the fan stage. Moving the maximum thickness position upwards leads to decreased flow turning and total pressure ratio.The mode shape and by that the twist-to-plunge ratio of the first mode is significantly influenced by the modifications. Thus, changing the aerodynamic damping of the blade and influencing the flutter behavior of the fan.Additionally, the fan displacements under aerodynamic and rotational loads are affected. For the fan presented a positive lean causes the blade to bend towards the pressure side when subjected to inertial forces, countering deformation from aerodynamic loads. Thickness adaption moves the shear center of the cross sections to the back. These results are used to optimize the fan blade behavior to achieve the project’s objectives. A final design, which satisfies the aerodynamic, aeroelastic and structrual needs of the CA3ViAR fan stage, is presented.

Geometric design and dynamic characteristics of a novel abnormal cycloidal gear reducer

A precision reducer with a high ratio and a small size is essential for precise control of the position of a robotic arm. The rotate vector (RV) is a reducer widely applied in robotic joints. However, its complex structure, over-positioning and difficult assembly restrict its application industrial robots. Herein, a novel abnormal cycloidal gear (ACG) reducer is proposed. In comparison to the RV reducer, the proposed reducer has the characteristics of compact structure, less over-positioning and high ratio. The compound tooth profile of “epicycloid-involute hypocycloid” is used as the driving teeth for improving the performance of the reducer. The operating principle, mechanism design and reduction ratio of the proposed reducer is investigated, and the design method of the ACG tooth profile is also introduced. A dynamic characteristic model is established to verify the correctness of the design method of the reducer. A prototype of the ACG reducer is fabricated by using the computer numerical control (CNC) machining technology. Results show that the ACG reducer is capable to cover a wide range of reduction ratios with a simple mechanism. The numerical and theoretical results are in agreement, which depict the structural feasibility and correctness of the design method of the reducer. The adaptation of the ACG tooth profile as the driving teeth helps in improving the performance of the reducer.

Evaluating Geometric Design Characteristics of Two-Lane Two-Way Rural Roads on Crash Frequencies Occurrences

Evaluating Geometric Design Characteristics of Two-Lane Two-Way Rural Roads on Crash Frequencies Occurrences

Sample Size Study of Driving Simulator Experiment for Freeway Design Safety Evaluations

Driving Simulator, a powerful simulation tool, has already been used in safety evaluation of roadway geometric design during the pre-construction design stage. Conventional ways of estimating proper sample size include the empirical method, the resource equation, power analysis, and the Bayesian method. However, significant boundaries and prior distributions of operational indices are hard to identify in simulator studies, which makes it difficult to use conventional ways in choosing the acceptable sample size. This study proposes an empirical method to infer proper sample size. The Tongji University eight-degree-of-freedom driving simulator was utilized to collect continuous driving behavior data from a simulated mountainous freeway. Vehicle speed and lane departure events were selected as the indices to measure the influence of geometric design features on operational efficiency and safety. A mixed linear model and a mixed logistic regression model were used to assess the relationships between geometric design features and vehicle speed and lane departure. Random sampling was used to choose 10 samples of 5 to 50 drivers from a total of 55 drivers. Acceptable sample size was determined based on the parameter coefficient convergence elbow points of the mean squared error (MSE) curves of significant variables. The clear elbow points of the MSE curves indicate that 30 is an acceptable sample size.

Magnetophoresis in Centrifugal Microfluidics at Continuous Rotation for Nucleic Acid Extraction.

Centrifugal microfluidics enables fully automated molecular diagnostics at the point-of-need. However, the integration of solid-phase nucleic acid extraction remains a challenge. Under this scope, we developed the magnetophoresis under continuous rotation for magnetic bead-based nucleic acid extraction. Four stationary permanent magnets are arranged above a cartridge, creating a magnetic field that enables the beads to be transported between the chambers of the extraction module under continuous rotation. The centrifugal force is maintained to avoid uncontrolled spreading of liquids. We concluded that below a frequency of 5 Hz, magnetic beads move radially inwards. In support of magnetophoresis, bead inertia and passive geometrical design features allow to control the azimuthal bead movement between chambers. We then demonstrated ferrimagnetic bead transfer in liquids with broad range of surface tension and density values. Furthermore, we extracted nucleic acids from lysed Anopheles gambiae mosquitoes reaching comparable results of eluate purity (LabDisk: A260/A280 = 1.6 ± 0.04; Reference: 1.8 ± 0.17), and RT-PCR of extracted RNA (LabDisk: Ct = 17.9 ± 1.6; Reference: Ct = 19.3 ± 1.7). Conclusively, magnetophoresis at continuous rotation enables easy cartridge integration and nucleic acid extraction at the point-of-need with high yield and purity.

Scaffold microarchitecture regulates angiogenesis and the regeneration of large bone defects

Emerging 3D printing technologies can provide exquisite control over the external shape and internal architecture of scaffolds and tissue engineering (TE) constructs, enabling systematic studies to explore how geometric design features influence the regenerative process. Here we used fused deposition modelling (FDM) and melt electrowriting (MEW) to investigate how scaffold microarchitecture influences the healing of large bone defects. FDM was used to fabricate scaffolds with relatively large fibre diameters and low porosities, while MEW was used to fabricate scaffolds with smaller fibre diameters and higher porosities, with both scaffolds being designed to have comparable surface areas. Scaffold microarchitecture significantly influenced the healing response following implantation into critically sized femoral defects in rats, with the FDM scaffolds supporting the formation of larger bone spicules through its pores, while the MEW scaffolds supported the formation of a more round bone front during healing. After 12 weeks in vivo, both MEW and FDM scaffolds supported significantly higher levels of defect vascularisation compared to empty controls, while the MEW scaffolds supported higher levels of new bone formation. Somewhat surprisingly, this superior healing in the MEW group did not correlate with higher levels of angiogenesis, with the FDM scaffold supporting greater total vessel formation and the formation of larger vessels, while the MEW scaffold promoted the formation of a dense microvasculature with minimal evidence of larger vessels infiltrating the defect region. To conclude, the small fibre diameter, high porosity and high specific surface area of the MEW scaffold proved beneficial for osteogenesis and bone regeneration, demonstrating that changes in scaffold architecture enabled by this additive manufacturing technique can dramatically modulate angiogenesis and tissue regeneration without the need for complex exogenous growth factors. These results provide a valuable insight into the importance of 3D printed scaffold architecture when developing new bone TE strategies.

Design Methodology and Application of Surface Texture: A Review

Surface texture is regarded as a promising solution for enhancing the tribological features of industrial materials due to its outstanding benefits, such as minimization of the contact area, enhancement of the load bearing capacity, storage of the lubricant, and management of the transition between lubrication regimes. Surface texture can be processed under either liquid or gas conditions. As compared to laser ablation in air, employing liquids or other gases as ablation media provides high accuracy and uniformity by limiting the heat-affected zone (HAZ) and other undesired defects to a large extent, as well as high crater structural features. In addition, the synergistic use of different liquid, solid, and additive lubricants with surface roughness recently demonstrated excellent performance. Therefore, surface texture helps to improve the tribological characteristics of a material. This paper reviews the design methodologies and applications of surface texture, emphasizing the proper selection of the appropriate laser parameters and ambient conditions for the best texture quality and functionality. Recent texture geometric design features to improve the film thickness and the self-lubricating system are presented. The ablation environment is explored using various media. The interaction between the lubricants’ types and surface textures is explored based on the operating conditions. Furthermore, surface texture applications using superhydrophobic surfaces, anti-drag, and vibration and noise friction are discussed. We hope that this review plays an enlightening role in follow-up research on laser surface texture.

Severity modeling of work zone crashes in New Jersey using machine learning models

In the United States, the probability of work zone crashes has increased due to an increase in renovation works by transportation infrastructures. The severity of work zone crashes is associated with multiple contributing factors such as the roadway’s geometric design features, temporal variables, environmental conditions, types of vehicles, and driver behaviors. For this study, we acquired and analyzed three years (2016–2018) of work zone crash data from the state of New Jersey. We investigated the performance of several machine learning methods, including Support Vector Machine, Random Forest, Catboost, Light GBM, and XGBoost to predict the type of injury severity resulting from work zone crashes. To evaluate models’ performances, some statistical evaluation parameters such as accuracy, precision, and recall scores were calculated. In addition, a sensitivity analysis was conducted to assess the impact of the most influential factors in work zone-related crashes. Random Forest and Catboost outperformed the other models in terms of predicting fatal, major, and minor injuries. According to the sensitivity analysis, crash type and speed limit were the most significantly associated variables with crash severity. The findings of this study are expected to facilitate the identification of appropriate countermeasures for reducing the severity of work zone crashes.