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This paper deals with the distribution of sources, transport, and exhaust of particles in a tokamak. Knowledge and understanding of all the physical phenomena involved in the global particle buildup are necessary to study and predict density regimes and subsequently to develop optimized scenarios for tokamak operation in order to control heat and particle exhaust. Neutral particles and their interactions with plasma are central in this perspective. This paper discusses the impact of varying the intensity of particle fueling in 2D transport simulations of a WEST discharge. Simulations are performed with an updated version of SOLEDGE-HDG that allows a more realistic transport of neutrals using a self-consistent diffusive model based on charge exchange and ionization processes. New code capabilities allow the entire WEST poloidal cross section to be simulated in a realistic configuration for both geometry and the range of control parameters. A gas puff scan illustrates the main features of the sheath-limited, high-recycling, and detached regimes, such as the buildup of the temperature gradient and the pressure drop in the scrape-off layer (SOL), the target temperature falling to 1 eV, and the ionization source moving away from the targets, as well as the particle flux rollover. A crude estimate of wall erosion is also provided, showing the respective role of each plasma wall component in each of these regimes. [ABSTRACT FROM AUTHOR]

Modern on-demand mobility concepts have the potential to drive the mobility transition. Increasing attention is being paid to DRT (Demand Responsive Transportation) services that enable the bundling of trips with the help of dynamic routing algorithms. Many providers use a stop-based operating concept for this purpose. The transport between so-called virtual stops promises a higher fraction of shared trips and shorter vehicle detours. The aim of this paper is to investigate multiple stop network designs and their impacts on the efficiency of the operation. For this purpose, three stop network generation approaches were derived from literature and applied to the simulation environment MATSim. A scenario in the city center of Berlin is simulated, where all inner car trips are replaced by DRT. Comparing the stop network design against a door-to-door service, the results suggest a trade-off between a reduction of vehicle kilometers (up to 18%) and increased walking distances (up to 250 meters on average). [ABSTRACT FROM AUTHOR]

New transport technologies have historically influenced how cities are shaped, while urban form is known to influence travel behaviour. But this reciprocal relationship is seldom operationalized in practice due to the disciplinary gap between urban design and transport planning. The two are often linked through a 'predict and provide' workflow, which is problematic in the context of emerging technologies such as AVs. This paper argues for a more iterative design and transport simulation workflow, through design experiments. One design experiment is illustrated using Sketch MATSim, to investigate the impact of network design on the performance of shared automated vehicles. [ABSTRACT FROM AUTHOR]

This paper deals with the distribution of sources, transport, and exhaust of particles in a tokamak. Knowledge and understanding of all the physical phenomena involved in the global particle buildup are necessary to study and predict density regimes and subsequently to develop optimized scenarios for tokamak operation in order to control heat and particle exhaust. Neutral particles and their interactions with plasma are central in this perspective. This paper discusses the impact of varying the intensity of particle fueling in 2D transport simulations of a WEST discharge. Simulations are performed with an updated version of SOLEDGE-HDG that allows a more realistic transport of neutrals using a self-consistent diffusive model based on charge exchange and ionization processes. New code capabilities allow the entire WEST poloidal cross section to be simulated in a realistic configuration for both geometry and the range of control parameters. A gas puff scan illustrates the main features of the sheath-limited, high-recycling, and detached regimes, such as the buildup of the temperature gradient and the pressure drop in the scrape-off layer (SOL), the target temperature falling to 1 eV, and the ionization source moving away from the targets, as well as the particle flux rollover. A crude estimate of wall erosion is also provided, showing the respective role of each plasma wall component in each of these regimes.

Objective The size of Neogene reservoir formation in rifted basins is closely linked to deep oil and gas accumulation and three-dimensional transport systems. Methods This study examines the differential oil and gas charging issues associated with target traps in Neogene fault basins. Using the eastern steep slope of the Miaoxibei Uplift in the Bohai Sea as an example, we analyze the components of the oil and gas accumulation system in steep slope zones by evaluating fault conduction capability and dividing the dominant injection segments. Subsequently, oil and gas migration simulations are conducted under the control of the fault injection section. Results The research findings are as follows: ① The accumulation system in the steep slope zone consists of deep hydrocarbon accumulative sand bodies, large boundary faults, and late shallow faults. ② The dominant hydrocarbon sinks in the three parts of the accumulation system interact with each other, forming a dominant migration path that is reflected in the overlapping fault charging section with the target trap. The middle section of the main migration fault on the east side of the Miaoxibei Uplift is a strong charging area, while the northern section is a medium charging area. Among the secondary migration faults, faults 4, 6, and 8 have developed strong charging sections, while faults 1, 2, and 11 have developed medium charging sections. ③ Structural migration simulations reveal that the oil and gas accumulation area develops in the middle of the steep slope zone in the east of the Miaoxibei Uplift, with two main migration routes in the east and one in the south. The typical sand traps in fault No. 3 have developed four accumulation zones, with accumulation zone C being the most significant. Conclusion In conclusion, these research findings can serve as a reference for well deployment in target areas, and the technical methods employed can provide support for hydrocarbon accumulation analysis.

To optimize the design of cushioning packaging and slow down the quality decline of Hami melon during the storage caused by resonance during transportation, Hami melon and its packaging corrugated cartons were used as research objects, and five layers of stacking height were set to simulate vibration test at variable frequency during transportation combined with spectrum analysis plus Hanning window function to determine the natural frequency of each stacked packaging parts, followed by simulated fixed frequency vibration tests during transportation. The results show that adding Hanning window function effectively improves the accuracy of the spectral analysis; The natural frequencies of the 5-layer packaging parts are 9.88, 54.75, 10.06, 10.31, and 10.42 Hz, respectively; Under 10 Hz fixed frequency vibration, the peak accelerations of the packaging parts in each layer are 5.99, 3.18, 6.37, 6.56, 6.81 g, vibration transmission rates of 53.61%, 28.52%, 57.07%, 58.76%, 61.02% respectively. Under the vibration at 54.75 Hz fixed frequency, the peak accelerations for each layer of packaging parts are 1.29, 6.34, 0.99, 0.87, 0.23 g, respectively, and vibration transmission rates are 8.38%, 45.04%, 6.47%, 6.04%, 0.75%, respectively. The research provides a reference for other packaging parts to seek more accurate resonance frequencies so as to effectively avoid the resonance frequency in the process of transportation and achieve the purpose of internal fruit damage reduction. [ABSTRACT FROM AUTHOR]

Excess commute (EC) refers to the sub-optimal allocation of workers to jobs in an urban region in terms of minimal commute distances. This article investigated EC for the Munich metropolitan area using a microscopic agent-based modeling suite. We first considered the optimization strategy, comparing the traditional zone-based transportation problem to a microscopic routine. Zonebased optimization is computationally efficient, but it underestimates EC due to spatial biases, even when the zone system is highly disaggregate. We then applied the optimized job-worker assignment to a microscopic travel demand model, assigning workers to jobs of the same job sector at a shorter distance from their home, accounting for multi-worker households. With shorter commutes, there was a substantial shift toward active modes. However, we only observed moderate impacts on total travel demand, with the overall effect dampened due to compensatory behavior between mandatory and discretionary travel. Finally, the outputs from the demand model were used by a microscopic assignment model to calculate externalities attributable to EC. Because of the complexity of travel demand, we conclude that the EC indicator alone would overestimate the benefits of policies targeting jobs-housing balance. [ABSTRACT FROM AUTHOR]

Leaky urban drainage networks (UDNs) exfiltrating wastewater can contaminate aquifers. Detailed knowledge on spatiotemporal distributions of water-dissolved, sewer-borne contaminants in groundwater is essential to protect urban aquifers and to optimize monitoring systems. We evaluated the effect of UDN layouts on the spreading of sewer-borne contaminants in groundwater using a parsimonious approach. Due to the UDN's long-term leakage behavior and the existence of non-degradable sewer-borne contaminants (equivalent to a conservative and constant contaminant source), we employed a concept of horizontal line sources to mimic the UDN layout. This does not require the consideration of bio-degradation processes or temporal delay and effectively bypasses the vadose zone, thus reducing computational requirements associated with a full simulation of leakages. We used a set of synthetic leakage scenarios which were generated using fractals and are based on a real-world UDN layout. We investigated the effects of typical leakage rates, varying groundwater flow directions, and UDN's layouts on the shape of the contaminant plume, disregarding the resulted concentration. Leakage rates showed minimal effects on the total covered plume area, whereas 89% of the variance of the plume's geometry is explained by both the UDN's layout (e.g., length and level of complexity) and groundwater flow direction. We demonstrated the potential of applying this approach to identify possible locations of groundwater observation wells using a real UDN layout. This straightforward and parsimonious method can serve as an initial step to strategically identify optimal monitoring systems locations within urban aquifers, and to improve sewer asset management at city scale. [ABSTRACT FROM AUTHOR]

We evaluate three strategies that transit operators might consider to increase ridership: a) increasing service on bus routes serving the highest share of low-income riders, b) increasing service on those bus routes with the highest ridership, and c) further providing the high-ridership routes identified in strategy (b) with exclusive bus lanes. In each scenario, we double the service frequency of buses on the focus routes and reduce the frequency on all other routes to maintain the total vehicle revenue miles, making the changes roughly cost-neutral. We tested these scenarios for Oshkosh, Wisconsin, and Atlanta, Georgia, using a modeling framework that combines CityCast, a commercially available data-driven planning tool to replicate observed travel patterns, and MATSim to simulate how travelers would change the route, mode, and time-of-day of the trips they make in response to the service changes. The results show substantial ridership gains for all but one scenario, suggesting that these strategies may provide a promising, low-cost means of increasing transit ridership in some contexts. However, impacts varied across the two case studies, indicating that local conditions play a role.

The unreasonable development and pollution of groundwater have caused damage to the groundwater system and environmental problems. To prevent this, the concept of "groundwater vulnerability" was proposed, and various evaluation methods were developed for groundwater protection. However, with changing climatic conditions and human activities, groundwater vulnerability is now emphasizing physical processes. This study aims to review and analyze the principles and applications of process-based groundwater vulnerability methods to achieve the source protection of groundwater resources. It introduces the assessment method and elaborates on pollutant migration processes and numerical simulation technology. Relevant articles from the past 30 years are reviewed to show the evolution of process-based groundwater vulnerability assessment. The study also discusses current research trends and proposes future development paths. It concludes that process-based groundwater vulnerability assessment will become the mainstream method, and modern technologies such as artificial intelligence will be necessary to solve challenges and achieve sustainable development. [ABSTRACT FROM AUTHOR]

To enable the deployment of battery electric vehicles (BEVs) as passenger cars in the private transport sector, suitable charging infrastructure is crucial. In this paper, a methodology for the efficient spatial distribution of charging infrastructure is evaluated by investigating a scenario with a 100% market penetration of BEVs of (around 1.3 million vehicles) in Berlin, Germany. The goal of the evaluated methodology is the development of various charging infrastructure scenarios—including public and private charging—which are suitable to cover the entire charging demand. Therefore, these scenarios are investigated in detail with a focus on the number of public charging points, their spatial distributions, the available charging power, and the necessary capital costs. For the creation of these charging infrastructure scenarios, a placement model is developed. As input, it uses the data of a multi-agent transport simulation (MATSim) scenario of the metropolitan area of Berlin to evaluate and optimize different distributions of charging infrastructure. The model uses a genetic algorithm and the principle of multi-objective optimization. The capital costs of the charging points and the mean detour car drivers must undertake are used as the optimization criteria. Using these criteria, we expect to generate cost-efficient infrastructure solutions that provide high usability at the same time. The main advantage of the method selected is that multiple optimal solutions with different characteristics can be found, and suitable solutions can be selected by subsequently using other criteria. Besides the generated charging scenarios for Berlin, the main goal of this paper is to provide a valid methodology, which is able to use the output data of an agent-based, microscopic transport simulation of an arbitrary city or area (or even real driving data) and calculate different suitable charging infrastructure scenarios regarding the different optimization criteria. This paper shows a possible application of this method and provides suggestions to improve the significance of the results in future works. The optimized charging infrastructure solutions for the Berlin scenario show capital costs of between EUR 624 and 2950 million. Users must cover an additional mean detour of 254 m to 590 m per charging process to reach an available charging point. According to the results, a suitable ratio between the charging points and vehicles is between 11:1 and 5:1. A share of fast charging infrastructure (>50 kW) of less than ten percent seems to be sufficient if it is situated at the main traffic routes and highly frequented places. [ABSTRACT FROM AUTHOR]

Extra virgin olive oil (EVOO) is imported/exported globally. However, little is known about the qualitative effects of the transport conditions, and, consequently, they are not usually controlled. This study simulates temperature fluctuations in summer (18–42.5 °C, 12 h–12 h, one week) and winter (4–16.5 °C, 12 h–12 h, one week), to examine their effect on EVOO quality. The EVOO samples undergo evaluation with chemical analyses before and immediately after treatment and after 24 weeks of storage (at room temperature in the dark). The simulated summer conditions cause oil oxidation. This situation bears a connection to an increased lipid oxidation rate, peroxide value, 1.2/1.3 diacylglycerol ratio, rancid score, and rancid‐related volatile compounds. The simulated winter conditions also cause oil oxidation. In this case, the rancid score and the rancid‐related volatile compound content show similarities to the samples exposed to the simulated summer conditions. In winter conditions, the temperature fluctuations seem to play a key role in the rancid defect appearance. Eleven of the 15 (summer) and 10 of the 15 (winter) samples are downgraded from the category of "extra virgin" to "virgin" after 24 weeks of bottle storage. Practical applications: Transportation conditions constitute a critical factor in determining extra virgin olive oil quality. Transport is a critical control point in maintaining the quality of extra virgin olive oil, which can be transported without any specific controls. The obtained results improve the knowledge regarding the risks related to transport in hot and cold seasons, assessing the oxidative damages in both conditions on three different cultivars. A better understanding of the degradation phenomena during transportation helps develop specific technologies and practices (e.g., controlled‐temperature transportation, thermal insulation materials, use of digi‐sense nonreversible temperature labels, and so on) to counter the phenomena and evaluate the costs and limits of the existing protocols. [ABSTRACT FROM AUTHOR]

The proliferation of car sharing services in recent years presents a promising avenue for advancing sustainable transportation. Beyond merely reducing car ownership rates, these systems can play a pivotal role in bolstering grid stability through the provision of ancillary services via vehicle-to-grid (V2G) technologies - a facet that has received limited attention in previous research. In this study, we analyze the potential of V2G in car sharing by designing future scenarios for a national-scale service in Switzerland. We propose an agent-based simulation pipeline that considers population changes as well as different business strategies of the car sharing service, and we demonstrate its successful application for simulating scenarios for 2030. To imitate car sharing user behavior, we develop a data-driven mode choice model. Our analysis reveals important differences in the examined scenarios, such as higher vehicle utilization rates for a reduced fleet size as well as in a scenario featuring new car sharing stations. These disparities translate into variations in the power flexibility of the fleet available for ancillary services, ranging from 12 to 50 MW, depending on the scenario and the time of the day. Furthermore, we conduct a case study involving a subset of the car sharing fleet, incorporating real-world electricity pricing data. The case study substantiates the existence of a sweet spot involving monetary gains for both power grid operators and fleet owners. Our findings provide guidelines to decision makers and underscore the pressing need for regulatory enhancements concerning power trading within the realm of car sharing. • We develop an agent-based simulator for generating car sharing trips. • Our simulation leverages a data-driven mode choice model based on Gradient Boosted Trees. • A scenario-based study reveals the possible benefits of implementing V2G for car sharing in the future. • A sweet spot exists where both grid operator and car sharing fleet owner benefit from V2G. [ABSTRACT FROM AUTHOR]

This paper presents a synthetic travel demand for the Greater São Paulo Metropolitan Region of Brazil, entirely based on open data and representative of the observed travel demand. The open-source and extendable pipeline creates a path from raw data to the synthetic travel demand and, further, to the downstream agent-based mobility simulation. An advantage of this approach is that it enables the reproduction of the synthetic travel demand and, therefore, provides the foundation of repeatability of downstream studies. Furthermore, as the methodology is based on open data, the study’s outcomes are easily accessible to the broad research and practice-oriented community.

To enable the deployment of battery electric vehicles (BEVs) as passenger cars in the private transport sector, suitable charging infrastructure is crucial. In this paper, a methodology for the efficient spatial distribution of charging infrastructure is evaluated by investigating a scenario with a 100% market penetration of BEVs of (around 1.3 million vehicles) in Berlin, Germany. The goal of the evaluated methodology is the development of various charging infrastructure scenarios—including public and private charging—which are suitable to cover the entire charging demand. Therefore, these scenarios are investigated in detail with a focus on the number of public charging points, their spatial distributions, the available charging power, and the necessary capital costs. For the creation of these charging infrastructure scenarios, a placement model is developed. As input, it uses the data of a multi-agent transport simulation (MATSim) scenario of the metropolitan area of Berlin to evaluate and optimize different distributions of charging infrastructure. The model uses a genetic algorithm and the principle of multi-objective optimization. The capital costs of the charging points and the mean detour car drivers must undertake are used as the optimization criteria. Using these criteria, we expect to generate cost-efficient infrastructure solutions that provide high usability at the same time. The main advantage of the method selected is that multiple optimal solutions with different characteristics can be found, and suitable solutions can be selected by subsequently using other criteria. Besides the generated charging scenarios for Berlin, the main goal of this paper is to provide a valid methodology, which is able to use the output data of an agent-based, microscopic transport simulation of an arbitrary city or area (or even real driving data) and calculate different suitable charging infrastructure scenarios regarding the different optimization criteria. This paper shows a possible application of this method and provides suggestions to improve the significance of the results in future works. The optimized charging infrastructure solutions for the Berlin scenario show capital costs of between EUR 624 and 2950 million. Users must cover an additional mean detour of 254 m to 590 m per charging process to reach an available charging point. According to the results, a suitable ratio between the charging points and vehicles is between 11:1 and 5:1. A share of fast charging infrastructure (>50 kW) of less than ten percent seems to be sufficient if it is situated at the main traffic routes and highly frequented places.

Serving both passenger and freight demand with the same vehicle fleet is an ambition that led to the development of several innovative vehicle concepts [10, 26]. This study proposes a simulation-based methodology to investigate the execution of freight tours with an On-Demand fleet of autonomous, modular vehicles while giving priority to passenger transport. Based on assumptions regarding the operational scheme, tour pricing and delivery time windows, the software Multi-Agent Transport Simulation (MATSim) is extended. The developed methodology is then applied to a Berlin-wide freight delivery scenario. The results show that when using a relatively large vehicle fleet, passenger waiting time statistics barely change. However, it has to be noted that the study should be repeated with different (smaller) fleet sizes. A rough cost analysis for the freight operator suggests that there is a large saving potential when using autonomous On-Demand vehicles instead of an owned fleet. Because of the uncertainty of price composition, further studies to quantify this saving potential have to be made. [ABSTRACT FROM AUTHOR]

This paper presents a synthetic travel demand for the Greater São Paulo Metropolitan Region of Brazil, entirely based on open data and representative of the observed travel demand. The open-source and extendable pipeline creates a path from raw data to the synthetic travel demand and, further, to the downstream agent-based mobility simulation. An advantage of this approach is that it enables the reproduction of the synthetic travel demand and, therefore, provides the foundation of repeatability of downstream studies. Furthermore, as the methodology is based on open data, the study's outcomes are easily accessible to the broad research and practice-oriented community. [ABSTRACT FROM AUTHOR]

Hörl and Balac [1] describe a data pipeline to generate a synthetic travel demand for Paris and Île-de-France. The data set consists of households, persons and their daily activity chains. It can be used in transport simulation, energy analysis and other research fields such as epidemiology. This data-in-brief article describes in detail the generated data set and how it can be regenerated based on publicly available and open data. The characteristics and pre-processing steps for the input data sets are covered in detail.

Today, there exist a number of standards designed to assist packaging engineers with implementing suitable laboratory testing regimes for road transport. However, these standards generally focus on translational vibrations and do not include other motions that may affect survival rates during transport (e.g., pitch and roll). The standards also do not account for the significant variations in vibration (root mean square [rms]) levels that are clearly evident during transport. Further, the analysis and interpretation of vibration frequency spectra typically ignore the possible presence of harmonics or shocks. Most standards also advocate some form of time compression to reduce testing duration by artificially amplifying the simulated vibrations. Each of these individual approaches combines to render the simulated vibrations currently in use unrepresentative of what occurs during transport, thereby making it difficult to optimise packaging systems. This article focuses on road transport shocks and vibrations and highlights the shortcomings of proposing and making changes to test methods based on limited data obtained from specific transport scenarios. It argues that only once all the evidence, taking into account a broader set of scenarios from multiple studies, has been collected and the correct scientific analysis applied, should changes to test protocols be proposed and implemented. The paper includes specific recommendations for further evidence collection and analysis for each of the main issues associated with road transport vibrations, namely, spectral shape, rms levels and test duration, nonvibratory events such as shocks and multiaxis vibrations. [ABSTRACT FROM AUTHOR]

Reinforcement learning is an efficient, widely used machine learning technique that performs well when the state and action spaces have a reasonable size. This is rarely the case regarding control-related problems, as for instance controlling traffic signals. Here, the state space can be very large. In order to deal with the curse of dimensionality, a rough discretization of such space can be employed. However, this is effective just up to a certain point. A way to mitigate this is to use techniques that generalize the state space such as function approximation. In this paper, a linear function approximation is used. Specifically, SARSA (λ) with Fourier basis features is implemented to control traffic signals in the agent-based transport simulation MATSim. The results are compared not only to trivial controllers such as fixed-time, but also to state-of-the-art rule-based adaptive methods. It is concluded that SARSA (λ) with Fourier basis features is able to outperform such methods, especially in scenarios with varying traffic demands or unexpected events. [ABSTRACT FROM AUTHOR]

The aim of this publication is to present the application possibilities of modern traffic simulation and planning software in both technical education and research. This article basically implements this using two software, PTV Vissim and PTV Visum, by presenting several transport models created using the two applications. The topic is given special relevance by today's digitalization trend, which also extends to the field of transport planning. [ABSTRACT FROM AUTHOR]

Solving Vehicle Routing Problems (VRPs) is one very important step for modeling and simulating urban freight transportation and especially urban last-mile delivery. It is observed in several studies, that tour plans consist of a very high number of vehicles needed because vehicles only drive one tour. For the next tour, a new vehicle with new fixed costs is needed. This also starts in the beginning of its temporal availability. This article intends to answer the question: how tour plan and fleet size changes when vehicles can reload at the depot and run another tour within its temporal availability. The possible effects are shown in two studies for Berlin: (i) food retailing delivery and (ii) parcel delivery for one district of Berlin. The studies have different designs and policy cases to see the effects under different situations. The present research shows that reloading within the delivery tour leads to a significant reduction of vehicles needed and therefore to lower costs for the carrier. If one tour is not limited by the vehicle's capacity but by the vehicle's temporal availability no saving can be observed. This was the case for parcel delivery with light parcel delivery trucks. When using smaller vehicles, e.g. cargo bicycles for last mile delivery from local city hubs, vehicle capacity is the limiting factor and therefore also significant saving can be observed. As another consequence it is possible to get rid of artificially inserted breaks in time-windows for more realistic traffic. The article also critically addresses the problem of increasing computation time. [ABSTRACT FROM AUTHOR]

Flathead grey mullet has a great potential as a low trophic level aquaculture species, however captive rearing is still hampered by the lack of well-established production protocols. Here we examined the effects of transport time and egg loading density on water quality, egg survival, hatching success and early larvae performance when shipped for 8, 16 and 24 h at 500 and 1500 eggs L−1. When no water conditioners were used, survival immediately after transport was consistently over 60% up to 16 h shipment for both densities tested, with minimum values of 40% for 1500 eggs L−1. Density and transport time did not influence hatching rate (p >.05) which ranged between 31 and 54% after 8 and 16 hour transport. However, manipulation after 8 and 24 h transport led to a significant drop in early larvae survival regardless the density tested (20% and 5% respectively) compared to 16 h transport (40%) (p <.05). Hence, the results indicate that grey mullet is sensitive when manipulated as early hatched larvae and when eggs undergo blastophore closure at circa 20 h post-fertilization. The tested egg stocking densities do not deteriorate water quality to lethal levels in terms of pH, NO 2 and NO 3 especially for short and medium transportation times, however, 24 h transportation induces an accumulation of ammonia affecting the long-term survival of larvae. When basic technology is available (i.e. no water conditioners, refrigerated vehicles), we suggest manipulating grey mullet eggs at 28 h post fertilization for best results in terms of hatching rate and early larvae survival. • Grey mullet eggs transport is safe at a maximum of 1500 eggs L−1 up to 16 h with no disinfection or water conditioners. • Water quality in fully closed systems at 24 °C do not deteriorate over safe limits over 16 h. • Transport and handling of grey mullet eggs should be avoided at 20 h post- fertilization and as early hatched larvae. • Survival at the start of exogenous feeding is drastically reduced after 24 h transport. [ABSTRACT FROM AUTHOR]

The modifiable areal unit problem is of great importance in geographic science. The use of a specific zoning impacts the social and economic imbalances that can be generated in the deployment of services, facilities, and infrastructure. In this article, GIS is used together with simulation and optimization tools to analyse the effects of bus frequency changes in the levels of service and horizontal equity derived from different types of territorial zoning. The city of Palma (Balearic Islands, Spain) was chosen as a case study for the method, for which different geographical areas are used: neighbourhoods, census sections, cadastral blocks, and a 400 × 400 m mesh. The results show significant variations of the optimal frequencies obtained, depending on the type of zoning used. In general, smaller zonings show much higher sensitivity for the detection of imbalances between the population and bus service level. Likewise, orthogonal zonings also prove useful for identifying service and population concentration over other zonings. The use of large spatial units could lead to the misdiagnosis of needs and the implementation of actions that do not actually improve the level of service or the equity of the transport service. It is recommended to consider combining zonings of different sizes simultaneously, in order to accurately highlight imbalances and to argue for transport service improvements.

Solving Vehicle Routing Problems (VRPs) is one very important step for modeling and simulating urban freight transportation and especially urban last-mile delivery. It is observed in several studies, that tour plans consist of a very high number of vehicles needed because vehicles only drive one tour. For the next tour, a new vehicle with new fixed costs is needed. This also starts in the beginning of its temporal availability. This article intends to answer the question: how tour plan and fleet size changes when vehicles can reload at the depot and run another tour within its temporal availability. The possible effects are shown in two studies for Berlin: (i) food retailing delivery and (ii) parcel delivery for one district of Berlin. The studies have different designs and policy cases to see the effects under different situations. The present research shows that reloading within the delivery tour leads to a significant reduction of vehicles needed and therefore to lower costs for the carrier. If one tour is not limited by the vehicle's capacity but by the vehicle's temporal availability no saving can be observed. This was the case for parcel delivery with light parcel delivery trucks. When using smaller vehicles, e.g. cargo bicycles for last mile delivery from local city hubs, vehicle capacity is the limiting factor and therefore also significant saving can be observed. As another consequence it is possible to get rid of artificially inserted breaks in time-windows for more realistic traffic. The article also critically addresses the problem of increasing computation time. [ABSTRACT FROM AUTHOR]

More and more, tropical fruit are subjected to accelerated ripening at receiving markets until "ready to eat." We propose a kinetic model that incorporates the effects of temperature and ethylene on the firmness behavior of "Keitt" and "Kent" mangoes. Stiffness of individual mangoes, as measured by the acoustic firmness tester, was measured repeatedly over time. The firmness model assumes fixed levels of ethylene, established after the climacteric peak, that steadily induces production of softening enzymes that subsequently denaturalize. The initial level of these enzymes is assumed to be zero due to either the tree factor for freshly harvested mangoes, or due to chilling injury for reefer transported mangoes. The kinetic parameter set for "Keitt" mangoes was estimated based on a Spanish batch, freshly harvested and ripened under dynamic temperature scenarios, combined with a reefer transported Brazilian batch stored at four constant temperatures. Firmness data from reefer transported batches, from Brazil, Ivory Coast and Mali, stored at four constant temperatures were used to estimate a set of kinetic parameters for the "Kent" mangoes. Only a partial set of "Kent" kinetic parameters could be established due to the often already advanced stage of softening at the time of arrival. The effect of ethylene was investigated by applying external ethylene levels, varying from 0 to 100 μL L−1. The effect of external application of ethylene was modeled by estimating EF, the ethylene factor, being a reflection of the internal ethylene level and ethylene sensitivity. The effect of ethylene application on softening was sometimes huge. For an Israeli "Keitt" batch a fifty times higher EF was found when the firmness behavior of low- (without ethylene application) and high temperature (with ethylene application) stored sub-batches were compared. However, this effect was sometimes also small, especially for reefer transported mangoes. For commercial application, a reliable prediction of the time until "ready to eat" is not possible because of the current inability to assess EF. Nevertheless, the proposed model described mango softening accurately, irrespective of the sourcing area and includes the effects of storage temperature and ethylene application. [ABSTRACT FROM AUTHOR]

Simulation modeling is a well-known and recurrent approach to study the performance of urban systems. Taking into account the recent and continuous transformations within increasingly complex and multidimensional cities, the use of simulation tools is, in many cases, the only feasible and reliable approach to analyze such dynamic systems. However, simulation models can become very time consuming when detailed input-space exploration is needed. To tackle this problem, simulation metamodels are often used to approximate the simulators’ results. In this paper, we propose an active learning algorithm based on the Gaussian process (GP) framework that gathers the most informative simulation data points in batches, according to both their predictive variances and to the relative distance between them. This allows us to explore the simulators’ input space with fewer data points and in parallel, and thus in a more efficient way, while avoiding computationally expensive simulation runs in the process. We take advantage of the closeness notion encoded into the GP to select batches of points in such a way that they do not belong to the same high-variance neighborhoods. In addition, we also suggest two simple and practical user-defined stopping criteria so that the iterative learning procedure can be fully automated. We illustrate this methodology using three experimental settings. The results show that the proposed methodology is able to improve the exploration efficiency of the simulation input space in comparison with non-restricted batch-mode active learning procedures. [ABSTRACT FROM AUTHOR]

The work proposes a methodological approach to studying and assessing the environmental sustainability of the transport system of the city. The authors have selected parameters for assessing the environmental sustainability of the transport system and identified significant factors affecting environmental sustainability. A coefficient of environmental sustainability of the urban transport system and a formula for its calculation are proposed. A simulation was used to assess the amount of emissions of harmful substances from the car exhaust gases if the demand structure changes with respect to the means of transport and transportation methods. The paper presents the results of changing the parameters of the traffic flow and demand by means of transport and transportation methods when introducing a parking fee in the central part of the city, changing the cost of parking and expanding the paid parking area.

In this paper, we present the initial results of a fundamental study of the impact of the magnetic configuration on the detachment behaviour and heat exhaust in HL‐2M simulation for low power. Starting from typical HL‐2M single‐null shapes, the plasma density at the core–edge interface is varied from 1 × 1019 to 8 × 1019 m−3 to investigate the detachment plasma characteristics. The additional X‐point near the primary X‐point and target is invested in snow flake plus (SF+) and snow flake minus (SF−) configurations. Detachment at the outer target is also studied in these simulations. The degree of detachment and the radiation location are investigated using the SOLEDGE2D simulation results. It is found that advanced divertor configurations result in a deeper detachment under the same plasma density and in a reduction in the detachment threshold. [ABSTRACT FROM AUTHOR]

We have developed an extended kinetic model for the thermal force F ∇ ∥ T on test impurity particles in plasmas. This model makes use of a combination of the plasma ion heat flux qGM derived from the generalized moment equations (E. Zawaideh et al., Phys. Fluids 1988, 31) and the numerical algorithm presented earlier (Y. Homma, A. Hatayama, J. Comput. Phys. 2013, 250). The applicable condition extends from collisional to weakly collisional plasmas, and F ∇ ∥ T weakens when the plasma collisionality decreases. A test simulation is performed assuming a tentative weakly collisional plasma. The results show that it can have a non‐negligible influence on transient impurity transport in a DEMO‐scale tokamak to take into account the effect of plasma collisionality in thermal force modelling. [ABSTRACT FROM AUTHOR]

This article presents a system dynamics model to analyze the growth of cars and the effect of different policies on carbon emissions from the transport sector. The simulation model used in this work was built using the methodology of systems dynamics (SD) developed by Jay W. Forrester at the Massachusetts Institute of Technology (MIT). The model was applied to the transport sector of the city of Bogota, Colombia for a period of time between 2005 and 2050. The information used to feed the model comes from reliable sources such as DANE (National Administrative Department of Statistics) and EIA (U.S Energy Information Administration). Four scenarios were proposed that relate urban development policy and environmental policy. The main results indicate that the number of cars in Bogota can reach up to 13 million vehicles in 2050 and the projection of CO2 emissions would reach 34 million TonCO2 in the absence of an appropriate environmental policy. [ABSTRACT FROM AUTHOR]

Dynamic ride hailing with passenger pooling has become a popular form of urban transport and is a growing sector around the globe. The area where these services operate is often limited to densely populated inner city districts, whereas non-pooled options are often available in larger areas. In this paper, we introduce a simulation-based methodology that allows to optimize the service area of a ride hailing service using an agent-based simulation and apply it to the taxi demand of Berlin, Germany. Three different criteria are used for the optimization, which take the average vehicle occupancy, the revenues collected per area or both into account. The results show that for the given parameters a service area that focuses on an extended central area and some areas around may be profit-maximizing for operators. [ABSTRACT FROM AUTHOR]

Dynamic transport simulators are intended to support decision makers in transport-related issues, and as such it is valuable that the random variability of their outputs is as small as possible. In this study we analyse the output variability caused by random seeds of a multi-agent transport simulator (MATSim) when applied to a case study of Santiago de Chile. Results based on 100 different random seeds shows that the relative accuracies of estimated link loads tend to increase with link load, but that relative errors of up to 10 % do occur even for links with large volumes. Although the proportion of links having large relative errors is roughly the same for all of the investigated seeds, it is shown the variations of individual link loads between seeds largely dominate variations between the two last iterations within a seed. [ABSTRACT FROM AUTHOR]

This paper describes the design of SimPark, an agent-based micro-simulator with state-of-the-art parking components. The goal is to allow the simulation of parking policies and strategies while capturing their effects on traffic flow and personal schedules. Though individuals’ parking strategies are an important part of the simulator, they are out of scope in the presented research. All other components of the simulator are discussed in depth and compared with existing parking simulators. [ABSTRACT FROM AUTHOR]

Traffic generates congestion and air pollution, especially in cities. These are among the reasons why environmentally friendly solutions are promoted. Bike sharing (bs) is intended to strengthen cycling and public transport. Nevertheless, scarcely any transport models at the present time consider cycling or bs, in either detail or holistically. We thus made a start here and reproduced the processes of cycling and modelled station based bs to depict e.g. station choice, renting and returning processes in detail. We included the interaction with other means of transport, especially bs and public transport. Moreover we provided a within day rescheduling for bs trips, as agents might not find a bike or parking. To minimize such cases, we implemented a choice probability, with which agents only start their bs trip, if sufficient bikes or parking spots are available. In general, such models can bring monetary, environmental and temporal benefits, since they can show potential for improvement without great cost. [ABSTRACT FROM AUTHOR]

With the rapid economic development in China, the amount of plastic waste (PW) generated has greatly increased and much of the waste is currently not treated. To reduce greenhouse gas (GHG) emissions from recycling of PW, we estimated the PW flow and considered methods to improve the household PW recycling system in Tianjin by adjusting processes during transportation and establishing a PW recycling factory in Zi'ya Industrial Park. The goal of the study was to identify reasonable improvements for the recycling system and clarify the environmental load. Geographic information system (GIS) technology was used to simulate transport processes for comparing GHG emissions from the transport processes between the present case and an improved case. Life cycle assessment (LCA) was used to compare GHG emissions between a projected scenario and a baseline scenario. Estimated GHG emissions during transport processes in the improved case were reduced by about 12,197 t CO eq per year compared to the present case, equivalent to about 65.9 % of the total emissions in the present case. GHG emissions in the projected scenario were about 101,738 t CO eq less per year than the baseline scenario, equivalent to about 75.5 % of the total emissions in the baseline scenario. [ABSTRACT FROM AUTHOR]

Human mobility is a key element in the understanding of epidemic spreading. Thus, correctly modeling and quantifying human mobility is critical for studying large-scale spatial transmission of infectious diseases and improving epidemic control. In this study, a large-scale agent-based transport simulation (MATSim) is linked with a generic epidemic spread model to simulate the spread of communicable diseases in an urban environment. The use of an agent-based model allows reproduction of the real-world behavior of individuals’ daily path in an urban setting and allows the capture of interactions among them, in the form of a spatial-temporal social network. This model is used to study seasonal influenza outbreaks in the metropolitan area of Zurich, Switzerland. The observations of the agent-based models are compared with results from classical SIR models. The model presented is a prototype that can be used to analyze multiple scenarios in the case of a disease spread at an urban scale, considering variations of different model parameters settings. The results of this simulation can help to improve comprehension of the disease spread dynamics and to take better steps towards the prevention and control of an epidemic.