Minimum Transit Time Research Articles

Influence from highways on regional economic growth – based on the trade potential in China

The question of whether the construction of the highway network is economical and can produce positive economic benefits has been a hot topic of discussion in recent years. Previous scholars have explored the impact from multiple perspectives. Our paper draws the “trade potential” model proposed by Armstrong, based on the universal gravity model and the principle of space interaction, which is different from the traffic accessibility, market potential, and market access used in most of the literature. We argue that it is more appropriate to consider both the size impact and the time distance or trade cost impact of the two cities. The paper constructs a conceptual framework and theoretical model for the impact of highways on regional economic growth, measures the “minimum transit time” of highways between prefecture-level cities in China, and calculates the trade potential of prefecture-level cities. Through corresponding empirical model testing, we have obtained some meaningful conclusions.

Foraging Attributes of Insect Pollinators on Tulsi (Ocimum basilicum)

Pollination is an intricate relationship between plants and pollinators; this interaction is the best example of mutualism where pollinators utilize floral rewards while pollination accomplished on plants. Pollination ecology of tulsi (Ocimum basilicum) is poorly understood. Foraging attributes: foraging rate, foraging speed and transit time of pollinators are key performance indicator to determine their pollination efficiency. Foraging speed and foraging rate were recorded during blooming period with the help of stopwatch and transit time was calculated from foraging rate and foraging speed. The performance of seven pollinators; Apis florea, Amegilla cingulata, Megachile femoratella, Megachile sp., Apis cerana, Apis dorsata and Apis mellifera were evaluated on the basis of foraging attributes. Foraging rate, foraging speed and transit time varied during the blooming period week to week and pollinator species to species. The maximum foraging rate was observed with A. mellifera, maximum foraging speed was observed with A. florea and minimum transit time as well as wasted minimum time was calculated with A. mellifera. The maximum foraging rate, foraging speed and minimum transit time were observed with all the pollinators at the peak of blooming period. Based on foraging attributes A. mellifera performance was better than other pollinators on Tulsi.

Modeling, Feedforward Control, and Constrained Trajectory Generation for a Concrete Conveyance System

Abstract Automated fabrication of concrete elements requires precise control of outgoing volume flow. Since measurements of the volume flow or the total extruded volume are challenging during production, a feedforward control is required, which in turn necessitates a model of the dynamics at hand. In this paper, a concrete conveyance system with two pumps is considered. These are mounted at the inlet and outlet of the hose, respectively. Based on previous work, a dynamical model with concentrated parameters is derived, which is motivated on the general distributed dynamics of two-phase flow. The model is validated by experiments, with parameters calculated by a tailored estimation approach. Based thereon, a feedforward control approach is presented and tested in simulation, exploiting the approximate flatness of the system. The flat parametrization is then used for constrained, smooth setpoint transition of the volume flow with minimal transition time.

Safe Reinforcement Learning for Transition Control of Ducted-Fan UAVs

Ducted-fan tail-sitter unmanned aerial vehicles (UAVs) provide versatility and unique benefits, attracting significant attention in various applications. This study focuses on developing a safe reinforcement learning method for back-transition control between level flight mode and hover mode for ducted-fan tail-sitter UAVs. Our method enables transition control with a minimal altitude change and transition time while adhering to the velocity constraint. We employ the Trust Region Policy Optimization, Proximal Policy Optimization with Lagrangian, and Constrained Policy Optimization (CPO) algorithms for controller training, showcasing the superiority of the CPO algorithm and the necessity of the velocity constraint. The transition trajectory achieved using the CPO algorithm closely resembles the optimal trajectory obtained via the well-known GPOPS-II software with the SNOPT solver. Meanwhile, the CPO algorithm also exhibits strong robustness under unknown perturbations of UAV model parameters and wind disturbance.

Correlation between RF signal first-arrival and minimum spectral transit time in cancellous bone

Measurement of the singular ultrasound velocity of a homogeneous sample may be calculated by division of its thickness and propagation transit time, generally utilizing a detection criterion of an RF signal’s first-arrival. A porous composite sample composed of two materials of differing ultrasound velocity will however exhibit a range of transit times. Ultrasound transit time spectroscopy (UTTS) considers propagation of an array of sonic-rays, with minima and maxima values ranging from entire higher and lower velocity materials, respectively. The aim of this Technical Note is to test the hypothesis that conventional RF signal transit time measurement correlates with the minimum spectral transit time, utilizing previously obtained experimental data from human cancellous bone samples. Linear regression yielded a coefficient of determination (R2) of 94%. The authors consider a practical consequence of the hypothesis is that information on the variability of transit time within a heterogeneous test sample may be better assessed by UTTS than conventional RF first-arrival transit time measurement. Noting the fundamental relationships between transit time, velocity, and elasticity of a test sample, there is further potential for UTTS to describe both velocity and elasticity spectroscopies within a wide range of structurally complex composites.

Evaluation of the deformation index of sea urchin Echinometra vanbrunti ovules by microfluidics

Microfluidics is a technique for controlling the flow of liquids in micrometric-scale channels, it is a powerful tool for performing analyzes with high throughput, high sensitivity, and speed, as well as low cost. In cells, the deformation index (DI) is one of the parameters that can be analyzed by this technique. Cell deformation is linked to the structure and mechanical properties of the biological constituents. By passing cells through a narrow channel, they are dynamically deformed, this can be done by a precise control of the pressure in the system. In this study, the ovule of the sea urchin Echinometra vanbrunti was used since it is a model cell due to its circularity very close to one. The average size of the cells (62.67 ± 2.91 μm) was analyzed to determine the appropriate size of the microchannels and to be able to manufacture a functional device to carry out the experiment. The device was manufactured based on polydimethylsiloexane (PDMS). Each experiment was digitally recorded to later be processed with Tracker modeling software and finally the data analysis was done with R program from which parameters such as DI, transit times in the channel and transit speed were obtained and searched for a relationship between the initial diameter of the cells and the transit time. We found a maximum DI of 0.698, a minimum transit time of 3.6 s and a maximum of 296.3 s, in addition, three different behaviors in the DI were found.

Optimal Transition Trajectory of a Quadrotor Biplane Tailsitter

This work focuses on transition trajectory generation for a special class of hybrid vertical takeoff and landing (VTOL) vehicles called quadrotor biplane tailsitter. The transition refers to the change of flight modes for a hybrid VTOL vehicle. A transition maneuver is challenging as the vehicle undergoes in low-speed high angle of attack condition which is highly unstable. This work proposes methods to generate an optimal trajectory for the forward transition of the vehicle. A simplified 3-degree-of-freedom (3-DOF) model of the vehicle is considered for generating the transition trajectory. The optimization problem is solved using nonlinear programming with appropriate dynamic and physical constraints. The work considers multiple optimality conditions that include minimal control effort, minimal transition time, and a combination of them. The results of different approaches are compared considering the feasibility of implementation on a physical vehicle.

Исследование динамики включения низковольтных InP-гомотиристоров

A series of heterostructure designs of low-voltage InP homothyristors have been investigated using numerical simulation methods. The design with a space charge layer formed in the p-base region of the n-p-n transistor part was considered as the base one. The dynamic characteristics and processes that determine the rate of transition to the on state are investigated. It is shown that as the p-base thickness increases from 1 to 2.6 μm, the maximum on-state currents increase from 70 to 90 A, while the minimum turn-on transition time is 11 ns at a maximum blocking voltage of 55 V. It is shown that the operation efficiency in the on state is determined by the residual voltage. Residual voltage decreases with a decrease in the thickness of the p-base.

Ice Transit and Performance Analysis for Cryorobotic Subglacial Access Missions on Earth and Europa.

Ice-covered ocean worlds, such as the Jovian moon Europa, are some of the prime targets for planetary exploration due to their high astrobiological potential. While upcoming space exploration missions, such as the Europa Clipper and JUICE missions, will give us further insight into the local cryoenvironment, any conclusive life detection investigation requires the capability to penetrate and transit the icy shell and access the subglacial ocean directly. Developing robust, autonomous cryorobotic technology for such a mission constitutes an extremely demanding multistakeholder challenge and requires a concentrated interdisciplinary effort between engineers, geoscientists, and astrobiologists. An important tool with which to foster cross-disciplinary work at an early stage of mission preparation is the virtual testbed. In this article, we report on recent progress in the development of an ice transit and performance model for later integration in such a virtual testbed. We introduce a trajectory model that, for the first time, allows for the evaluation of mission-critical parameters, such as transit time and average/overall power supply. Our workflow is applied to selected, existing cryobot designs while taking into consideration different terrestrial, as well as extraterrestrial, deployment scenarios. Specific analyses presented in this study show the tradeoff minimum transit time and maximum efficiency of a cryobot and allow for quantification of different sources of uncertainty to cryobot's trajectory models.

Leukocytapheresis variables and transit time for allogeneic cryopreserved hpc: better safe than sorry.

Cryopreservation was recommended to ensure continuity in allogeneic hematopoietic progenitor cells (HPC) transplantation during the COVID-19 pandemic. Several groups have shown no impact on clinical outcomes for patients who underwent HPC transplantation with cryopreserved products during the first months of this pandemic. However, concerns about quality control attributes after cryopreservation have been raised. We investigated, in 155 allogeneic peripheral blood cryopreserved HPC, leukocytapheresis characteristics influencing viable CD34+ and CD3+ cells, and CFU-GM recoveries after thawing. Collection characteristics such as volume, nucleated cells (NC)/mL and hematocrit correlated with viable CD34+ and CD3+ cells recoveries after thawing in univariate analysis but only CD3+ cells remained statistically significant in multivariate analysis (r2 = 0.376; P = < 0.001). Additionally, transit time also showed correlation with viable CD34+ (r2 = 0.186), CD3+ (r2 = 0.376) and CFU-GM recoveries (r2 = 0.212) in multivariate analysis. Thus, diluting leukocytapheresis below 200 × 106 NC/mL, avoiding red cells contamination above 2%, cryopreserving below 250 × 106 NC/mL and minimizing transit time below 36 h, prevented poor viable CD34+ and CD3+ cells, and CFU-GM recoveries. In summary, optimizing leukocytapheresis practices and minimizing transportation time may better preserve the quality attributes of HPC when cryopreservation is indicated.

Multi-objective closed-loop supply chain network design: A novel robust stochastic, possibilistic, and flexible approach

Nowadays, the production of stone paper, in addition to its widespread utilization in various fields, does not require water consumption, cutting down trees, and stone paper products are easily recyclable and recoverable. Due to the importance of developing and using stone paper and paying attention to environmental matters, Closed-Loop Supply Chain Network Design (CLSCND) is very important for stone paper products. Moreover, due to epistemic, randomness uncertainties, the uncertainties in Objective Function (OF), and the flexible constraints for CLSCND in the real world, this paper introduces a novel Mixed Robust Stochastic, Possibilistic, and Flexible Programming (MRSPFP) approach based on credibility theory. The different attitudes of the Decision-Makers (DMs) are addressed by a more flexible measurement of the optimistic and pessimistic parameters using the criterion of credibility. In the study, a comprehensive procedure is proposed for stone paper CLSCND, to minimize costs, increase responsiveness by minimizing transit time between different facilities, and regarding environmental concerns into account through minimizing carbon emissions. The model is solved utilizing an interactive fuzzy programming solution procedure and the Best-Worst Method (BWM). The results of sensitivity analysis, the effect of changing the problem parameters, and the performance of the proposed model are investigated and compared. The results show that the MRSPFP model has a better performance compared to other previous models. The MRSPFP model performs better in strategic decisions that require high investment costs due to the minimization of the absolute deviation of OF from its mean. Also, the applied results of the study show that CLSCND has a good capability and potential for sustainable development in the field of stone paper.

Data-Driven Decomposition Control to Output Tracking With Nonperiodic Tracking–Transition Switching Under Input Constraint

AbstractThis paper is concerned with solving, from the learning-based decomposition control viewpoint, the problem of output tracking with nonperiodic tracking–transition switching. Such a nontraditional tracking problem occurs in applications where sessions for tracking a given desired trajectory are alternated with those for transiting the output with given boundary conditions. It is challenging to achieve precision tracking while maintaining smooth tracking–transition switching, as postswitching oscillations can be induced due to the mismatch of the boundary states at the switching instants, and the tracking performance can be limited by the nonminimum-phase (NMP) zeros of the system and effected by factors such as input constraints and external disturbances. Although recently an approach by combining the system-inversion with optimization techniques has been proposed to tackle these challenges, modeling of the system dynamics and complicated online computation are needed, and the controller obtained can be sensitive to model uncertainties. In this work, a learning-based decomposition control technique is developed to overcome these limitations. A dictionary of input–output bases is constructed offline a priori via data-driven iterative learning first. The input–output bases are used online to decompose the desired output in the tracking sessions and design an optimal desired transition trajectory with minimal transition time under input-amplitude constraint. Finally, the control input is synthesized based on the superpositioning principle and further optimized online to account for system variations and external disturbance. The proposed approach is illustrated through a nanopositioning control experiment on a piezoelectric actuator.

Risso's dolphins perform spin dives to target deep-dwelling prey.

Foraging decisions of deep-diving cetaceans can provide fundamental insight into food web dynamics of the deep pelagic ocean. Cetacean optimal foraging entails a tight balance between oxygen-conserving dive strategies and access to deep-dwelling prey of sufficient energetic reward. Risso's dolphins (Grampus griseus) displayed a thus far unknown dive strategy, which we termed the spin dive. Dives started with intense stroking and right-sided lateral rotation. This remarkable behaviour resulted in a rapid descent. By tracking the fine-scale foraging behaviour of seven tagged individuals, matched with prey layer recordings, we tested the hypothesis that spin dives are foraging dives targeting deep-dwelling prey. Hunting depth traced the diel movement of the deep scattering layer, a dense aggregation of prey, that resides deep during the day and near-surface at night. Individuals shifted their foraging strategy from deep spin dives to shallow non-spin dives around dusk. Spin dives were significantly faster, steeper and deeper than non-spin dives, effectively minimizing transit time to bountiful mesopelagic prey, and were focused on periods when the migratory prey might be easier to catch. Hence, whereas Risso's dolphins were mostly shallow, nocturnal foragers, their spin dives enabled extended and rewarding diurnal foraging on deep-dwelling prey.

Effects of magnetic field, binary particle loading and rotational conic surface on phase change process in a PCM filled cylinder

In the present work, coupled effects of forced convection, rotational conic surface and magnetic field on the phase change dynamics are numerically explored by using finite element method for a phase change material (PCM) filled 3D cylindrical reactor. The PCM filled region has a conic shape and it is rotating. The study is conducted for various values of rotational Re number (between 0 and 2500), magnetic field strength (Hartmann number between 0 and 30) and conic surface aspect ratio (between 1 and 2). It is observed that the coupled interactions between the rotational surface and magnetic field significantly affect the phase change process dynamics and convective heat transfer between different phases. Optimum value of rotational Reynolds number for minimum complete phase transition time is achieved at Rew = 1000. The magnetic field has a positive impact on the phase change process while it is impact is profound without surface rotation. There are 98% and 65% reductions in the complete phase transition times when configurations at Rew = 1000 are compared with motionless conic surface case in the absence and presence of magnetic field. The effects of rotation are profound when different aspect ratios of the PCM filled region is considered. The transition time is increased up to 553% without rotation while this value is only 86% when cases with lowest and highest aspect ratio are compared. A modal analysis with 30 mode is used to capture the phase change dynamics and coupled interactions between the rotational surface and magnetic field on the variation of liquid fraction.

Revisiting Trans-Arctic Maritime Navigability in 2011–2016 from the Perspective of Sea Ice Thickness

Arctic navigation has become operational in recent decades with the decline in summer sea ice. To assess the navigability of trans-Arctic passages, combined model and satellite sea ice thickness (CMST) data covering both freezing seasons and melting seasons are integrated with the Arctic Transportation Accessibility Model (ATAM). The trans-Arctic navigation window and transit time are thereby obtained daily from modeled sea ice fields constrained by satellite observations. Our results indicate that the poorest navigability conditions for the maritime Arctic occurred in 2013 and 2014, particularly in the Northwest Passage (NWP) with sea ice blockage. The NWP has generally exhibited less favorable navigation conditions and shorter navigable windows than the Northern Sea Route (NSR). For instance, in 2013, Open Water (OW) vessels that can only safely resist ice with a thickness under 15 cm had navigation windows of 47 days along the NSR (45% shorter than the 2011–2016 mean) and only 13 days along the NWP (80% shorter than the 2011–2016 mean). The longest navigation windows were in 2011 and 2015, with lengths of 103 and 107 days, respectively. The minimum transit time occurred in 2012, when more northward routes were accessible, especially in the Laptev Sea and East Siberian Sea with the sea ice edge retreated. The longest navigation windows for Polar Class 6 (PC6) vessels with a resistance to ice thickness up to 120 cm reached more than 200 days. PC6 vessels cost less transit time and exhibit less fluctuation in their navigation windows compared with OW vessels because of their ice-breaking capability. Finally, we found that restricted navigation along the NSR in 2013 and 2014 was related to the shorter periods of navigable days in the East Siberian Sea and Vilkitskogo Strait, with local blockages of thick ice having a disproportionate impact on the total transit. Shorter than usual navigable windows in the Canadian Arctic Archipelago and Beaufort Sea shortened the windows for entire routes of the NWP in 2013 and 2014.

Robust Operations Management on Mars

We compare both deterministic and robust stochastic approaches to the problem of scheduling a set of scientific tasks under processing time uncertainty. While dealing with strict time windows and minimum transition time constraints, we provide closed-form expressions to compute the exact probability that a solution has to remain feasible. Experiments, taking uncertainty on the stochastic knowledge itself into account, are conducted on real instances involving the constraints faced and objectives pursued during a recent twoweek Mars analog mission in the desert of Utah, USA. The results reveal that, even when using very bad approximations of probability distributions, solutions computed from the stochastic models we introduce, significantly outperform the ones obtained from a classical deterministic formulation, while preserving most of the solution’s quality.

Development of conceptual provisions to effectively manage the activities of a multimodal transport operator

Modern market requirements for transportation of cargo flows according to the «quality, speed, and cost» criteria were studied. It was found that multimodal routes have the lowest delivery time, high reliability, and minimum transit time, which provides a more accurate level of control of costs, traffic schedules, and transport safety. It was determined that the effectiveness of multimodal transportation schemes depends on a degree of realization of resource capabilities and management technologies of a multimodal transport operator (MTO). The functional features and the MTO classification were generalized, which makes it possible to generate the MTO business model as a responsible integrator of transport and logistic processes, rather than consider it only from the point of view of the organizer of mixed transportation schemes. The technology of the organizational transportation process was systematized, based on which a system of strategic goals and key performance indicators (KPI) was developed, which makes it possible to determine the «bottlenecks» according to the main business processes of a multimodal transportation operator. The modified multifactor DuPont model was proposed, which makes it possible to establish the priority of factor evaluation of more time-stable indicators based on determining the levers of the MTO resource efficiency with greater coverage of factors. The performed research can become the basis for further development of the multimodal cargo transportation system based on the development of the model for optimal management of the MTO business processes.

Quantization and Structure of Electromagnetic and Gravitational Fields

Following Relativistic Alpha Field Theory (RAFT) here it is started with the solution of the field parameters α and α′ in the combined electromagnetic and gravitational fields. The field parameters α and α′ are described as the functions of the particle charge, particle mass, electrical potential, gravitational potential, gravitational constant, gravitational mass and speed of the light in vacuum. The mentioned parameters are presented by using identity between the constant ratio of Planck mass and Planck length and between gravitational mass and gravitational length. It is shown that the minimal electrical length is limited by the electric charges or by the electrical particle mass. It is also confirmed that the energy conservation constant is valid both in an electromagnetic central symmetric field as well as in a gravitational field. Further, the numerical quantities of the minimal and maximal radial densities for the spherically symmetric particles are also valid in the central symmetric electromagnetic fields, as well as, in the gravitational fields. The quantization of the combination of the central symmetric electromagnetic and gravitational fields is dominant in the region of the minimal length and twice of that length. Therefore, the quantization is applied to the mentioned region, both in central symmetric electrical fields and in the combination of the central symmetric electrical and gravitational fields. It is determined that the minimal distance between two quantum states should be less than 10-35 m. The related minimal transition time can be obtained by using the transition speed equal to the speed of the light in vacuum. Calculation of the energy uncertainty, the shortest transition time, the generic state, the shortest physically possible time and the time effectively spent by the controlled system or control algorithm are presented systematically. The mentioned parameters are calculated both in the case of central symmetric electrical field, as well as, in the combination of the electrical and gravitational fields.

Traversable asymptotically flat wormholes with short transit times

We construct traverseable wormholes by starting with simple four-dimensional classical solutions respecting the null energy condition and containing a pair of oppositely charged black holes connected by a non-traverseable wormhole. We then consider the perturbative back-reaction of bulk quantum fields in Hartle–Hawking states. Our geometries have zero cosmological constant and are asymptotically flat except for a cosmic string stretching to infinity that is used to hold the black holes apart. Another cosmic string wraps the non-contractible cycle through the wormhole, and its quantum fluctuations provide the negative energy needed for traversability. Our setting is closely related to the non-perturbative construction of Maldacena, Milekhin, and Popov (MMP), but the analysis is complementary. In particular, we consider cases where back-reaction slows, but fails to halt, the collapse of the wormhole interior, so that the wormhole is traverseable only at sufficiently early times. For non-extremal backgrounds, we find the integrated null energy along the horizon of the classical background to be exponentially small, and thus traversability to be exponentially fragile. Nevertheless, if there are no larger perturbations, and for appropriately timed signals, a wormhole with mouths separated by a distance d becomes traverseable with a minimum transit time . Thus is smaller than for the eternally traverseable MMP wormholes by more than a factor of 2, and approaches the value that, at least in higher dimensions, would be the theoretical minimum. For contrast we also briefly consider a ‘cosmological wormhole’ solution where the back-reaction has the opposite sign, so that negative energy from quantum fields makes the wormhole harder to traverse.

Evaluating the Vulnerability of Time-Sensitive Transportation Networks: A Hub Center Interdiction Problem

Time-sensitive transportation systems have received increasing research attention recently. Examples of time-sensitive networks include those of perishable goods, high-value commodity, and express delivery. Much research has been devoted to optimally locating key facilities such as transportation hubs to minimize transit time. However, there is a lack of research attention to the reliability and vulnerability of time-sensitive transportation networks. Such issues cannot be ignored as facilities can be lost due to reasons such as extreme weather, equipment malfunction, and even intentional attacks. This paper proposes a hub interdiction center (HIC) model for evaluating the vulnerability of time-sensitive hub-and-spoke networks under disruptions. The model identifies the set of hub facilities whose loss will lead to the greatest increase in the worst-case transit time. From a planning perspective, such hubs are critical facilities that should be protected or enhanced by preventive measures. An efficient integer linear programming (ILP) formulation of the new model is developed. Computational experiments on a widely used US air passenger dataset show that losing a small number of hub facilities can double the maximum transit time.