Collision Probability Research Articles

A spatial analysis of risk factors associated with road collisions in Ciudad Juarez, Mexico and using a geographically weighted regression approach

This study examined changes in the spatial patterns and determinants of road collisions in Ciudad Juarez, Mexico in 2019 and 2020, encompassing the initial period of COVID-19 mobility restrictions. Kernel density estimation and local indicators of spatial association were used to compare collision distributions and identify significant clusters between years. A geographically weighted negative binomial regression model then generated local coefficients to analyze how demographic, socioeconomic, land use, and road network factors influenced collision probability spatially. Results show collisions decreased 13.18% in 2020 but clustered differently, validating restrictions' impact. Population aged 15–64 and industrial land uses significantly increased risk spatially, whereas commercial uses decreased. Lower socioeconomic conditions also correlated with higher risk. Younger populations presented varying collision likelihoods intra-urbanly. This research thus emphasizes how local contexts shape risk factors’ effects and informs data-driven safety policies accounting for place-specific issues. By adopting an explicitly spatial modeling approach, localized risk patterns were uncovered not detectable through traditional methods.

ACTOR: Adaptive Control of Transmission Power in RPL.

RPL-Routing Protocol for Low-Power and Lossy Networks (usually pronounced "ripple")-is the de facto standard for IoT networks. However, it neglects to exploit IoT devices' full capacity to optimize their transmission power, mainly because it is quite challenging to do so in parallel with the routing strategy, given the dynamic nature of wireless links and the typically constrained resources of IoT devices. Adapting the transmission power requires dynamically assessing many parameters, such as the probability of packet collisions, energy consumption, the number of hops, and interference. This paper introduces Adaptive Control of Transmission Power for RPL (ACTOR) for the dynamic optimization of transmission power. ACTOR aims to improve throughput in dense networks by passively exploring different transmission power levels. The classic solutions of bandit theory, including the Upper Confidence Bound (UCB) and Discounted UCB, accelerate the convergence of the exploration and guarantee its optimality. ACTOR is also enhanced via mechanisms to blacklist undesirable transmission power levels and stabilize the topology of parent-child negotiations. The results of the experiments conducted on our 40-node, 12-node testbed demonstrate that ACTOR achieves a higher packet delivery ratio by almost 20%, reduces the transmission power of nodes by up to 10 dBm, and maintains a stable topology with significantly fewer parent switches compared to the standard RPL and the selected benchmarks. These findings are consistent with simulations conducted across 7 different scenarios, where improvements in end-to-end delay, packet delivery, and energy consumption were observed by up to 50%.

Cooperative Distributed Uplink Cache over B5G small cell networks.

The emergence of content-centric network has resulted in a substantial increase in data transmission in both uplink and downlink directions. To tackle the ensuing challenges of network congestion and bottlenecks in backhaul links within Beyond Fifth Generation (B5G) networks, data caching has emerged as a popular solution. However, caching for uplink transmission in a distributed B5G scenario poses several challenges, including duplicate content matching and users' obliviousness about cached contents. Furthermore, it is important to maximize available space by caching the most popular contents in a distributed manner. In this paper, we propose two schemes for uplink transmission in distributed B5G SCNs. The first scheme focuses on content matching to eliminate duplicate contents among distributed caches, while the second scheme redistributes un-duplicated cached contents among distributed caches based on their available space and content's size. These approaches aim to enhance energy and spectral efficiency by reducing unnecessary uploads and optimizing distributed content caching, in addition to improve the content delivery. The analysis shows that the proposed schemes outperform the existing schemes by improving the cache hit ratio, cache hit probability, overall distributed cache efficiency, and diversity by 29.17%, 74.89%, 24.17%, and, 80%, respectively. Furthermore, the average throughput, Spectrum Efficiency (SE), and Energy Efficiency (EE) of the access network is improved by 17.78%, 18%, and 78%, respectively. Besides that, the EE and SE of both the sidehaul and backhaul links of the SBSs are also improved.

Numerical simulation of non-spherical microparticles' deposition on single fiber

As a classical gas-solid two-phase flow system, the processes of fiber filtering microparticles are prevalent in nature and engineering. However, the impact of microparticle shape on fiber filtration processes is still largely unexplored. Herein, using the self-developed spheropolyhedral-based discrete element lattice Boltzmann method, the filtration process of non-spherical microparticles through a single fiber is investigated. Results show that the single fiber efficiency (SFE) for non-spherical particles exhibits a trend of initially increasing and subsequently decreasing trend with the increase in Stokes number (St), which is similar to the case of spherical particles. However, it is interesting to note that the peak values of SFE increase significantly with decreasing particle sphericity (ψ) and the corresponding St values become larger. As ψ decreases from 1.0 (sphere) to 0.671 (tetrahedron), the SFE increase from 0.205 to 0.49 and the corresponding St rises from 1.0 to 1.75. The enhanced SFE can be explained by elevated collision probability and adhesion probability, based on detailed particle kinematics and dynamics behavior analysis as well as microscopic depositional structure evaluation. The depositional structures of the non-spherical particles have larger capture areas, leading to higher initial collision probabilities. Meanwhile, the anisotropic collisions between non-spherical particles and fibers greatly contribute to higher secondary collision probabilities. In addition, compared to spherical particles of the same volume, the non-spherical particles experience greater fluid resistance, resulting in lower initial collision velocities and larger initial adhesion probabilities. The face-to-face contacts between non-spherical particles also lead to stronger interparticle adhesion and enhanced adhesion probabilities.

Preliminary Safety Analysis of Megaconstellations in Low Earth Orbit: Assessing Short-Term and Long-Term Collision Risks

The deployment of megaconstellations in low Earth orbit (LEO) poses significant collision risks with space debris. This paper focuses on analyzing the short-term and long-term collision probabilities of megaconstellations to assess their collision risk. Firstly, a short-term collision risk evolution model is developed to accurately address rendezvous collisions. Secondly, a long-term collision risk evolution model is established by considering space object density, space debris attenuation, space target disintegration, and the distribution of disintegration targets. Through simulations conducted on the Starlink Phase I constellation, the results demonstrate a 30–40% increase in short-term collision probability within the constellation shell, a 70.2% probability of at least one collision during the constellation’s lifetime, and a 25.3% increase in secondary collisions following a collision event. This study provides a reference and application for analyzing the orbital safety of LEO megaconstellations and for promoting the sustainable development and utilization of space resources.

Charge Density-Regulated Microchannel-Based Electrochemiluminescence Sensor for Hydrogen Sulfide Detection with a Highly Efficient Accumulation Strategy.

The electrochemiluminescence (ECL) intensity can be regulated by ionic current passing through the microchannel, which broadened the regulation of the ECL sensors. But in the early reported sensors, the electrostatic repulsion and steric hindrance caused few targets to approach the interface of the microchannel driven by concentration difference, which reduced the detection efficiency and prolonged the detection period. In this study, different accumulation strategies, such as a positive electric field and different polarity electric fields, were designed to accumulate targets in the microchannel. The interaction of azide groups and hydrogen sulfide served as a research model. Hydrogen sulfide can react with the negatively charged azide groups in the microchannel surface to produce positively charged amino groups, decreasing the negative charge density of the microchannel and thus altering the ionic current and ECL intensity. The accumulation of hydrogen sulfide at the microchannel tip can increase the collision probability with azide groups to improve the detection efficiency, and the integration of accumulation and reaction can shorten the detection period to 28 min. The hydrogen sulfide concentration on the microchannel tip accumulated by applying different polarity electric fields was 22.3-fold higher than that accumulated by applying a positive electric field. The selected research model broadened the application range of a microchannel-based ECL sensor and confirmed the universality of the microchannel-based ECL sensor.

Numerical simulation and experimental study of hole cleaning

Insufficient hole cleaning causes tool wear and reduces drilling efficiency. Existing evaluation methods and models are limited. In this study, a universal method is proposed to assess hole cleaning efficiency (HCE). A coupled computational fluid dynamics and discrete element method (CFD-DEM) numerical model for non-Newtonian fluid simulation of cuttings transport is developed. The influence of various factors on HCE was analyzed from an energy and particle collision perspective, with a particular focus on the mechanisms of fluid viscosity and rate of penetration (ROP) on cuttings settling. Results show that increased fluid viscosity improves HCE, while excessive viscosity negatively affects it. Higher ROP results in increased solid particle concentration and collision probability, leading to energy loss and reduced efficiency. Lower HCE was observed when the inclination deviated from the vertical. The HCE can be significantly improved by increasing the fluid velocity and reducing the eccentricity. A comprehensive prediction model for HCE is established using Design of Experiment (DOE), dimensional analysis, and nonlinear regression. This model incorporates a generalized fluid apparent viscosity, taking into account the impact of each rheological parameter. Additionally, it can be applied to predict hole cleanliness in both Newtonian and non-Newtonian fluids. By comparing the experimental results of hole cleanliness in three distinct fluids, the regression model yielded reliable predictive results. The findings enhance understanding regarding how fluid properties and the ROP affect cuttings transport and enable precise and convenient prediction and optimization of hole cleaning efficiency.

Removal efficiency and mechanism of geosmin by modified micro-nano bubbles in drinking water treatment process

The problem of odor and taste caused by geosmin had been widely discussed globally. While existing water treatment processes were difficult to remove geosmin cleanly and efficiently, and the traditional aeration method of micro-nano bubbles (MNBs) led to low removal efficiency due to the low probability of collision between the bubbles and the contaminants. In this study, micro-nano bubble modification technique was used to improve the removal efficiency. Three surface modifiers, hexadecyl trimethyl ammonium bromide (CTAB), chitosan (CTS), and poly dimethyl diallyl ammonium chloride (PDADMAC), were selected for this study. The effects of the surface modifiers on the properties of MNBs and the effects of these changes on the removal efficiency of GSM were explored. The experimental results showed that when all three modifiers were dosed at 5 mg/L, the PDADMAC-modified MNBs had the best GSM removal effect of 70.9 %, while the Zeta potential of the effluent was lower at 4.17 mV, which had less influence on the downstream process, and was an ideal modifier. The contribution of various removal pathways to GSM removal was also explored through intermediate product analysis combined with variable control experiments. The experimental results showed that the enhanced removal of GSM was attributed to the enhanced capture of GSM by PDADMAC-modified MNBs and the enhanced oxidation of GSM by PDADMAC-modified MNBs. At the same time, the removal efficiency of this process in natural waters decreased by <5 % only. This study could provide data and theoretical support for the enhanced removal of olfactory compounds by modified MNBs for application in practical engineering.

Improved Collision Probability Analysis of the Double-Heterogeneity Problem Based on Matrix Chord Length Correction

Dispersion fuel exhibits excellent safety performance and effectively reduces the risk of radioactive leakage, making it widely applied in high-temperature gas-cooled reactors (HTGRs) and other advanced nuclear reactors. The presence of stochastic media in dispersion fuel leads to the challenging double-heterogeneity problem in neutron transport calculations. Hébert proposed a collision probability analysis model for treating stochastic media, which has been implemented in the DRAGON5 code. As one important basis of derivation, it is assumed in the Hébert model that the neutron transmission probability is identical to the neutron escaping probability in matrix material. In this paper, it is figured out that the assumption is not rigorous for realistic stochastic media. Then, an improved approach based on the Hébert model is proposed to take into account the realistic chord length distribution as well as to ensure the conservation and reciprocity of collision probabilities. The proposed methodology has been implemented in the HTGR lattice physics code XPZ. By numerical analysis against Monte Carlo reference solutions, it is demonstrated that the improved Hébert model with chord length correction gives good accuracy for addressing realistic double-heterogeneity problems.

Modelling yielding dilemma zone for drivers at non-signalised crosswalks

In developing countries like China, non-signalised crosswalks represent a considerable risk to pedestrian safety. This study introduces a “yielding dilemma zone” model to tackle the decision-making challenges encountered by drivers at these crosswalks. Field data collected via drones at three non-signalised crosswalks in Xi'an (China) facilitated the analysis of 1687 instances of driver yielding behaviour. The study employed Support Vector Machine (SVM), Artificial Neural Network (ANN), and Binary Logistic Regression (BLR) models to establish the boundaries of the dilemma zone. Additionally, it utilized surrogate safety metrics, such as the deceleration rate required to stop (DRS) and time to crossing (TC), to compare risks between dilemma and non-dilemma zones. Each modelling approach provided insightful findings. The SVM and ANN models identified the speed-distance dilemma zones, while the BLR model determined the multifactorial dilemma zones by considering characteristics such as pedestrian, vehicle, and traffic condition. The findings underscore the significance of the “yielding dilemma zone” for understanding driver-pedestrian interactions at non-signalised crosswalks. The innovative multi-model approach uncovered that pedestrian speed, vehicle type, vehicle approach speed, adjacent vehicle number, driving directions, and pedestrian crossing stage significantly influence this interaction. indicated a higher probability of collisions within dilemma zones compared to non-dilemma zones across all models. The study suggests that the SVM model could be instrumental in creating passive physical warning signs, while the ANN and BLR models could significantly contribute to real-time pedestrian and driver assistance systems. The “yielding dilemma zone” model, with its comprehensive approach, presents a promising avenue for enhancing pedestrian safety, intelligent transportation systems, and traffic management at non-signalised crosswalks.

Study on Assessment of Collision Probability between Ship and Bridge Based on Automatic Identify System Data

With the development of bridge crossings over rivers, the accident of the vessel–bridge collision is increasing as well. It is important to assess probability of bridges colliding with passing ships. Firstly, the AIS (Automatic identify system) data was collected and decoded to obtain the dynamic information of the ships passing the bridge including the distributions of ships position, speed, and yaw angle, which are then compared with the value recommended by the AASHTO (American Association of State Highway and Transportation Officials) specification. The mainly influential parameters of ship–bridge collision obtained from AIS data are used to correct the variables in the risk assessment of AASHTO specification, which intends to improve the assessment accuracy by considering the actual information of passing vessels. The collision probability with and without considering the actual situations of passing ships are compared. It is found that the distribution and transit path of passing ships significantly influence the collision probability. To improve the risk assessment accuracy, it is suggested to use the actual distributions of passing ships from AIS data.

Finite element model for partial differential equations in optimization of vehicle safety collision problem

Vehicle safety on roadsides is vital for preventing collisions, controlling failures and accidents, and ensuring driver and passenger wellness. Finite Element Analysis (FEA) in vehicle safety relies on the vehicle’s physical attributes for predicting and preventing collisions. This article introduces a Differential FEA (DFEA) model for predicting vehicle collisions regardless of the speed and direction for driver/ passenger safety. The proposed model induces a vehicle’s speed, direction, and displacement from two perspectives: self and approaching vehicle. The collision probability with the trailing or persuading vehicle is calculated by distinguishing the forward and rear features. The differential calculus for the point of deviation and distance metrics are significantly estimated for a vehicle’s front and rear ends. Such calculus generates a maximum and minimum possibility for self and approaching vehicle contact. This contact is further split based on the collision threshold; the threshold is determined using the safe distance between two vehicles for collision-less driving. The threshold exceeding vehicles are alerted for their change in direction/ speed through contact point (rear/front) differential derivatives. This ensures collision detection under fewer contact errors, leveraging the safety of the duo vehicles.

Design study of a 450MW thermal Modified CANDLE fast reactor using helium gas as a coolant

The Modified CANDLE (MCANDLE) burnup scheme divides the reactor core into several regions in an axial or radial direction with equal volume. It works like the CANDLE burnup scheme except that, in the CANDLE burnup scheme, the reactor core is divided into three main regions in the axial direction. Namely, spent fuel, burning region and fresh fuel region. In this study, the design of a modular modified CANDLE fast reactor using helium gas as a coolant has been performed. One of the important roles of a modified CANDLE fast reactor is that it can utilize natural uranium as fuel without the need for enrichment or reprocessing. This type of reactor can be used, including in developing countries, without the nuclear proliferation problem. Using helium gas as a coolant gives hope for a fast reactor due to its properties, such as its less neutron absorption, less radioactive, and as helium is an inert gas, prevents chemical reactions with other materials. The study was performed on a rector with a thermal power of 450MWth. The active core was divided into ten regions with equal volume in radial directions. The refueling scheme has been optimized every ten years of burnup to obtain a good reactor design. In the beginning, the fuel was put in the first region after ten years of burnup was moved to the second region, after another ten years of burnup was moved to the third region and so on until the tenth region where the fuel gets out. The neutronic calculation has been performed using the SRAC (Standard Reactor Analysis Code system). The collision probability method (PIJ) was employed for cell burnup calculation, and CITATION was used for the reactor core design with JENDL 4.0 as the nuclear data library.

CFD investigation of chalcopyrite flotation prediction coupled with flotation kinetic model

CFD (computational fluid dynamics) simulation plays an important role in flotation prediction research and application. The flotation process of chalcopyrite in a three-dimensional mineralized tube was simulated coupled with flotation kinetic model. Regarding of kinetic prediction model in the flotation process is explored at gas volume flow rate of 1 L/min, slurry volume flow rate of 0.4 and 0.5 m3/h, including collision probability model, attachment probability model, detachment probability model and bubble slip velocity model. Flotation experiments of chalcopyrite is performed, and the simulation of flotation process is realized by adding UDF (user-defined function). Furthermore, the flotation rate constant is taken to verify the validity of the model. The prediction error of flotation rate constant is 19 % and 17 % between flotation experiments and simulations at slurry volume flow rate of 0.4 and 0.5 m3/h, respectively. According to the combinations of flotation kinetic model, it’s found that the prediction results of Yoon-Luttrell collision probability model, Yoon-Luttrell attachment probability model, Schulze detachment probability model and Kostoglou bubble slip velocity model are superior to other combinations. the prediction error of flotation rate constant is 8 % at the slurry flow rate of 0.4 m3/h.

Advanced collision risk estimation in terminal manoeuvring areas using a disentangled variational autoencoder for uncertainty quantification

Air Traffic Management aims at ensuring safety during aircraft operations, particularly within Terminal Manoeuvring Areas where traffic density is high. The challenge lies in balancing safety and efficiency by closely managing the likelihood of mid-air collisions regarding the airport movements. Traditional models like the Reich and Anderson-Hsu models have been influential, but they fall short in representing the complex reality of Terminal Manoeuvring Areas. Data-driven approaches are emerging, with Monte Carlo simulations offering a more flexible methodology for collision risk estimation. This paper introduces a framework for assessing Mid-Air Collision likelihood resulting from Terminal Manoeuvring Area procedures by combining the field of Deep Generative Modelling using a Variational Autoencoder with the domain of rare event statistics through Subset Simulation. By incorporating disentanglement into the Variational Autoencoders model, we create a latent space that aligns dimensions with distinctive trajectory traits. Then, Subset Simulation is employed to gauge Mid-Air Collision probability, utilizing latent representations as input. Finally, sensitivity analysis reveals pivotal factors influencing collision risk, correlated with trajectory attributes via disentanglement. The methodology is applied to traffic around Zurich Airport: it evaluates the risk arising from go-around and take-off procedures using Automatic Dependent Surveillance-Broadcast data.

A Novel Molten Salt Mediated Synthesis of Mesoporous Metal Oxides with High Crystallization.

The controlled synthesis of mesoporous metal oxides remains a great challenge because the uncontrolled assembly process and high-temperature crystallization can easily destroy the mesostructure. Herein, we develop a facile, versatile, low-cost, and controllable molten salt assisted assembly strategy to synthesize mesoporous metal oxides (e.g., CeO2, ZrO2, SnO2, Li2TiO3) with high surface area (115-155 m2/g) and uniform mesopore size (3.0 nm). We find this molten salt mediated assembly enables the desolvation of the precursors and forms bare metal ions, enhances their coordination interaction with the surfactant, and promotes their assembly into a mesostructure. Furthermore, the molten salt assisted crystallization process can lower the collision probability of the target metal atom, inhibit its further growth into large crystals, and achieve a well-maintained mesostructure with high crystallization. Furthermore, this method can be expanded to synthesize various structured mesoporous metal oxides, including hollow spheres, nanotubes, and nanosheets by introducing the carbon template. The obtained mesoporous CeO2 microspheres loaded with Cu species exhibit excellent antibacterial performance and superior catalytic activity for the hydrogenation of nitrophenol with high conversion and cycling stability.

Output feedback containment fuzzy control for multi-agent systems with quantitative input and tunable reference signals

For multi-agent systems with quantitative input, we propose a novel containment control scheme to guarantee that the agents can enter a convex hull generated by the leader's signals after starting from any initial position. The problem with existing schemes is that the reference signals of the agents are affected by the communication topology such that the position of the reference signal cannot be changed when this communication topology is determined. To solve this problem, the proposed scheme can generate a flexible and adjustable reference signal for each agent. This has the advantage of reducing the probability of collisions among agents. Meanwhile, to address the situation where some agents cannot receive reference signals, we design an estimator to generate an adjustable estimation signal for each specific agent to ensure that all agents continue moving within the convex hull. In addition, by combining the fuzzy observer with the command filter design method, we devise a novel controller design scheme for quantitative input, which ensures that all signals in closed-loop multi-agent systems are uniformly and ultimately bounded. Finally, the simulation results demonstrate the feasibility and superiority of the proposed scheme for controlling multi-agent systems.

The Probability of Ship Collision during the Fully Submerged Towing Process of Floating Offshore Wind Turbines

As global warming intensifies, the development of offshore wind farms is swiftly progressing, especially deep-water Floating Offshore Wind Turbines (FOWTs) capable of energy capture in deep-sea regions, which have emerged as a focal point of both academic and industrial interest. Although numerous researchers have conducted comprehensive and multifaceted studies on various components of wind turbines, less attention has been paid to the operational stage responses of FOWTs to wind, waves, and currents and the reliability of their structural components. This study primarily employs a theoretical analysis to establish mathematical models under a series of reasonable assumptions, examining the possibility of collisions between FOWT transport fleets and other vessels in the passage area during the towing process. Using the model, this paper takes the Wanning Floating Offshore Wind Farm (FOWF) project, which is scheduled to be deployed in the South China Sea, as its research object and calculates the probability of collisions between FOWTs and other vessels in three months from the pier near Wanning, Hainan, to a predetermined position 22 km away. The findings of the analysis indicate that the mathematical model developed in this study integrates the quantities and velocities of navigational vessels within the target maritime area as well as the speeds, routes, and schedules of the FOWT transport fleet. By employing statistical techniques and geometric calculations, the model can determine the frequency of collisions between various types of vessels and the FOWT transport fleet during the transportation period. This has substantial relevance for future risk assessments and disaster prevention and mitigation measures in the context of FOWT transportation.

Small ship collisions in coastal areas during tsunamis: Impact on seawalls behind sand dunes

Coastal regions often feature seawalls situated behind sand dunes, introducing unique topographical factors that significantly influence ship drift and collision behavior. This study investigates the collision dynamics of a small ship, particularly fishing boats, in coastal areas during tsunamis and the subsequent impact forces on a seawall behind dunes. Through hydraulic model experiments, the characteristics of tsunami-driven drift, collision probabilities, and instantaneous impact forces were examined. The likelihood of ship collisions with seawalls increased when the dimensionless initial position of a ship (the ratio of its distance from the shore to the tsunami breaking point) was less than 0.6. The impact force experienced by a ship was influenced by the behavior of the water mass rising in front of the seawall post-tsunami. Collisions before the descending water mass resulted in increased impact forces, while collisions post-descent showed forces decreased owing to reduced drift velocity. In cases where ships encountered falling water masses before a collision, impact forces decreased significantly compared to other scenarios. An equation to estimate ship impact velocity, accounting for dune effects, based on the dimensionless time difference between the tsunami and ship collision and the tsunami propagation velocity calculated from near-shore tsunami height was introduced. This equation considers the damping effect of impact velocity, improving accuracy within the experimental range of small impact forces.

Operando Mobile Catalysis for Reverse Water Gas Shift Reaction

AbstractMetal atoms on the support serve as active sites for many heterogeneous catalysts. However, the active metal sites on the support are conventionally described as static, and the intermediates adsorbed on the support far away from the active metal sites cannot be transformed. Herein, we report the first example of operando mobile catalysis to promote catalytic efficiency by enhancing the collision probability between active sites and reactants or reaction intermediates. Specifically, ligand‐coordinated Pt single atoms (isolated MeCpPt‐ species) are bonded on CeO2 and transformed into mobile MeCpPt(H)CO complexes during the reverse water gas shift reaction for operando mobile catalysis. This strategy enables the conversion of inert carbonate intermediates on the CeO2 support. A turnover frequency (TOF) of 6358 mol CO2 molPt−1 ⋅ h−1 and 99 % CO selectivity at 300 °C is obtained for reverse water gas shift reaction, dramatically higher than those of Pt catalysts reported in the literature. Operando mobile catalysis presents a promising strategy for designing high‐efficiency heterogeneous catalysts for various chemical reactions and applications.