Multimode Operation Research Articles

The effects and conflicts of co-opetition in a rail-water multimodal transport system.

This study investigates a rail-water multimodal transport system composed of a railway company, a liner company, and an emerging multi-modal operator. Based on the co-opetition game, we discuss decision strategy preference and conflict from a multi-stakeholder perspective to optimize individual profit and system efficiency. It is found that although the invasion of multi-modal operators into the market poses a threat to competition, their service effort directly affects the market demand and promotes the profits of each carrier. The free-riding and market expansion effects triggered by service effort interact with each other. However, multi-modal operators can cope with the negative impact of the free-riding effect through the service strategy and promote system efficiency optimization. Specifically, discussing each carrier's decision-making preferences for maximizing profits, we find that the multi-modal operators' strategy can achieve the Pareto optimal of triple-win, and the system efficiency is also optimal simultaneously.

High-Speed Optical Mode Switch in Lithium Niobate on Insulator

Mode-division-multiplexing technology is highly attractive to increase the capacity of optical interconnects. Various multimode operations have been investigated, among which optical mode switches provide one of the most important functions in mode-division-multiplexing systems. However, current optical mode switches have a non-negligible switching time, which can lead to an undesired cumulative delay in the optical network. In this contribution, we propose and experimentally demonstrate an optical mode switch using a three-waveguide-coupling structure in the lithium niobate on insulator platform. The demonstrated optical mode switch has an insertion loss of 4.3 dB, an extinction ratio of 17.1 dB, and a switching time of below 28 ps. This work paves the way for future chip-scale high-speed mode-division-multiplexing systems.

Comparison of the Multimodal Transport Operator’s and a Freight Forwarder’s Liability Limit in International Transport. Case Study

Abstract Understanding the limits of freight forwarders' liability helps to predict the scope of indemnification to the customer in case of damage or loss of cargo. The absence of international agreements regulating the limit of the liability limit of freight forwarders makes it difficult for customers to find freight forwarders with the most favorable conditions. A large number of factors, such as the type of forwarding contract, the country of registration of the forwarder, the status of the forwarder, existing international agreements, etc. can significantly affect the degree of liability of the forwarder. In this paper, the legislation regulating forwarding and the activities of the multimodal transport operator will be considered. In addition, the standard conditions of the forwarding contract, the most commonly used in the selected countries, will be analyzed. On the basis of the conducted research, a case study will be presented, which will indicate the practical influence of various factors on the liability limit of the forwarder and the multimodal transport operator.

Multimodal Multi-User Mixed Reality Human–Robot Interface for Remote Operations in Hazardous Environments

In hazardous environments, where conditions present risks for humans, the maintenance and interventions are often done with teleoperated remote systems or mobile robotic manipulators to avoid human exposure to dangers. The increasing need for safe and efficient teleoperation requires advanced environmental awareness and collision avoidance. The up-to-date screen-based 2D or 3D interfaces do not fully allow the operator to immerse in the controlled scenario. This problem can be addressed with the emerging Mixed Reality (MR) technologies with Head-Mounted Devices (HMDs) that offer stereoscopic immersion and interaction with virtual objects. Such human-robot interfaces have not yet been demonstrated in telerobotic interventions in particle physics accelerators. Moreover, robotic operations often require a few experts to collaborate, which increases the system complexity and requires sharing a multi-user Augmented Reality (AR) workspace. The multi-user telerobotics with shared control in the AR has not yet been approached in the industrial state-of-the-art. In this work, the developed MR human-robot interface using the AR HMD is presented. The interface adapts to the constrained wireless networks in particle accelerator facilities and provides reliable high-precision interaction and specialized visualization. The multimodal operation uses hands, eyes and user motion tracking, and voice recognition for control, as well as offers video, 3D point cloud and audio feedback from the robot. Multiple experts can collaborate in the AR workspace locally or remotely, share the robot’s control and monitor robotic teleoperation. Ten (10) operators tested the interface in intervention scenarios in the European Organization for Nuclear Research (CERN) with complete network characterization and measurements to conclude if operational requirements were met and if the network architecture could support single and multi-user communication load. The interface system has proved to be operationally ready at the Technical Readiness Level (TRL) 8 - and was validated through successful tests and demonstration in single and multi-user missions. Some areas of system limitations and further work were identified, such as optimising the network architecture for multi-user scenarios or high-level interface actions applying automatic interaction strategies with the robot depending on network conditions.

Closed-loop Control of SI←→RCCI Mode Transitions in a Multi-Mode Combustion Engine

The primary barrier to implementing the RCCI mode in on-road vehicles is its limited operating range due to excessive pressure rise rates and complexity of combustion control during mode switching. The feasible operating range of the RCCI mode is only a subset of the speed-load range of conventional spark ignition (SI) engines. Therefore, a multi-mode engine concept operating in RCCI and SI modes can cover required engine operating range and can improve engine performance in terms of thermal efficiency and emissions. The goal of this study is to develop a model-based closed loop control of an SI-RCCI multi-mode engine. To this end, a gain scheduled model predictive controller (MPC) is developed for SI-RCCI-SI mode switching. A Kalman filter is designed for state estimations. The control architecture includes; a supervisory controller that determines the optimal operating mode based on the requested engine load and speed, and gain scheduled MPC and a Kalman filter. The controller performance is validated on a 2-liter multi-mode engine for SI-RCCI-SI mode switching at different engine loads (NMEP) and combustion phasings (CA50). The controller is capable of tracking NMEP and CA50 in both modes and during mode transitions while maintaining air-fuel ratio near stoichiometry in SI mode and constraining the maximum pressure rise rate (MPRR) below 8 bar/CAD in the RCCI mode.

DualGNN: Dual Graph Neural Network for Multimedia Recommendation

One of the important factors affecting micro-video recommender systems is to model the multi-modal user preference on the micro-video. Despite the remarkable performance of prior arts, they are still limited by fusing the user preference derived from different modalities in a unified manner, ignoring the users tend to place different emphasis on different modalities. Furthermore, modality-missing is ubiquity and unavoidable in the micro-video recommendation, some modalities information of micro-videos are lacked in many cases, which negatively affects the multi-modal fusion operations. To overcome these disadvantages, we propose a novel framework for the micro-video recommendation, dubbed Dual Graph Neural Network (DualGNN), upon the user-microvideo bipartite and user co-occurrence graphs, which leverages the correlation between users to collaboratively mine the particular fusion pattern for each user. Specifically, we first introduce a single-modal representation learning module, which performs graph operations on the user-microvideo graph in each modality to capture single-modal user preferences on different modalities. And then, we devise a multi-modal representation learning module to explicitly model the user’s attentions over different modalities and inductively learn the multi-modal user preference. Finally, we propose a prediction module to rank the potential micro-videos for users. Extensive experiments on two public datasets demonstrate the significant superiority of our DualGNN over state-of-the-arts methods.

A data-based framework for automatic road network generation of multi-modal transport micro-simulation

<abstract> <p>In microscopic traffic simulation, the fidelity of the road network model has a significant impact on the difference between the simulation and the actual urban traffic state. Accurately matching data on the simulated road network and the surroundings has become a central concern in traffic simulation research. This study provides a multi-source data-based framework for automatic road network generation (ARNG) to address the issue of manual procedures in the creation of the simulated road network and surroundings. First, the proposed method of fusion and matching of diverse road network data is used to acquire the basic road network information, and the combining of the features of different road network data can enhance the authenticity of the basic road network. Second, a multi-modal simulation road network is developed based on multi-modal traffic operation data to serve as the simulation operation's foundational environment. To address the requirements of the dynamic evolution of the simulated road network, an editor for the dynamic road network is built based on spatial closest neighbor matching. The case study illustrates the process of building the simulated road network and environment in the old city zone of Suzhou. Real-world examples demonstrate that the data-based ARNG approach provided in this study is highly automatic and scalable.</p> </abstract>

ПОСТАНОВКА ЗАДАЧИ ОПТИМИЗАЦИИ МАРШРУТОВ ГРУЗОВЫХ МУЛЬТИМОДАЛЬНЫХ ПЕРЕВОЗОК

The article deals with the urgent task of increasing the efficiency of multimodal transportation of goods based on the optimization of delivery routes. The task is formulated in terms of the subject area of interest to the transportation customer. The mathematical statement of the problem is presented in the form of a graph model that takes into account dynamic changes in the requirements of both the consignor and the consignee. According to the authors, this approach to solving the logistics problem allows the multimodal operator to respond to changes in a timely manner and gives some advantages when choosing an effective route in the face of sanctions pres-sure and border closures.

A mixture of probabilistic predictable feature analysis for multi-mode dynamic process monitoring

In modern industrial processes, the demand for safety and reliability is increasingly prioritized, spawning quantities of related research on process monitoring models. It is significant for process monitoring to consider multi-mode operating conditions simultaneously. This work proposes an efficient method based on multi-mode probabilistic predictable feature analysis (MPPFA) for complex industrial process monitoring. A strategy combining deep auto-encoder (DAE) and Gaussian mixture model (GMM) is first designed to extract low-dimensional features and identify possible running modes. In line with the obtained features, original training samples are classified into corresponding Gaussian distributions with reasonable probabilities. Further, local PPFA models are established based on the separated training batches. Five monitoring statistics, including TP2, SPEP, and DIP for PPFAs, TD2 and SPED for DAE, are defined to detect abnormalities. The proposed method is first applied to a three-phase flow facility, and its superiority over comparison methods has been verified. The effectiveness of the proposed method is further demonstrated through an experiment on a practical coal pulverising system.

Optimal Multi-Mode Flexibility Operation of CHP Units with Electrode Type Electric Boilers: A Case Study

With the in-depth development of flexibility retrofit in combined heat and power (CHP) units, the unit commitment mode of energy supply equipment in CHP plants is more flexible. This paper presents a multi-mode flexible operation method for CHP plants with electrode electric boilers. Firstly, a simulation model of the operation characteristics of each unit in different operation modes is established, and the corresponding features of electrical and thermal outputs are obtained. Subsequently, a decision-making model of the unit commitment mode of energy supply equipment is set up, and the selection rules of the unit commitment mode of the unit under low heat load, medium heat load, and high heat load are achieved. Finally, under different unit operation combinations, a plant-level optimum load dispatch model is obtained, and the actual operating data of the CHP plant is used for optimization and comparison analysis. The results show that compared to the unit commitment mode of high back pressure and low-pressure cylinder cutting-off (HBP + LPCC), the unit commitment mode of high back pressure and extraction heating (HBP + EH) has more room for energy-saving optimization. Under the premise of safe and reliable operation, the high back pressure (HBP) unit can be loaded as much as possible. While in the combined operating of HBP + EH, the energy-saving space for optimized load dispatching is not large, so a fixed proportion of the electrical load may be considered; under the auxiliary service subsidy policy, the input power of the electric boiler can be appropriately increased; the greater the heat load of the whole plant, the more pronounced the energy-saving effect of optimum load dispatch.

Model Predictive Control for Four-Switch Buck–Boost Converter Based on Tuning-Free Cost Function With Smooth Mode Transition

Four-switch buck-boost (FSBB) converter has the capability of bidirectional voltage step-down and step-up, which has attracted attentions in the fields of energy storage and solar energy. However, it faces the challenges in multimode operation and smooth mode transition, which rely on the complex mode detection scheme and cumbersome parameter tuning. In this article, the inherent limitation is analyzed through inconsistent frequency response and noncontinuous duty cycle operation region aspects. Then, a model predictive control (MPC) method characterized by tuning-free cost function is presented to achieve multimode control and smooth transition simultaneously. With the goal of ensuring the reference current tracking under inconsistent frequency response, a duty cycle and current ripples prediction are presented for all switching combinations. Then, a tuning-free cost function is utilized to overcome the gaps in noncontinuous duty cycle operation region and a smooth mode transition is achieved. Further, the robustness of the current tracking capability is analyzed mathematically considering the inductance variation and stray resistance variation. Finally, a comparative experiment proves the effectiveness. And it shows that the method can improve the efficiency by 0.4% compared with the traditional four-mode control.

Design and Optimization of a Multimode Amphibious Robot With Propeller-Leg

This article describes the design, optimization, and performance evaluation of a novel multimode motion robot named SHOALBOT, which with multimode operations depends on only one type of propulsion device and can work flexibly in the amphibious environment including running on beaches, grasslands, seabed, and swimming in the water. Robots that work in water need to minimize the number of drive components to improve reliability and reduce communication pressure, our unique design enables the robot to rely on a kind of propulsion device named propeller-leg to have the ability to run rapidly in the seaside and seabed, and swim with multi-degrees-of-freedom in the water (such a propulsion system contains only four driving elements), and it can make the robot complete more work content and improve its adaptability to the environment. Running is more stable than swimming and will not disturb the animals in the water, but when the robot encounters a high obstacle with a large area coverage, switching the motion mode to the swimming mode can pass directly over obstacles instead of detouring or giving up work, this can improve work efficiency. We analyzed and optimized propeller-leg by simulation combined with the open water test, the propeller-leg's thrust in the water before and after optimization differs by 400% according to the test results. We optimized the minimum difference between the forward and reverse thrust of the propeller-leg to improve the stability of the robot movement process and optimized the difference from 25% to 3%. This article provides sufficient technical details and completeness, and through a series of performance evaluation experiments validated that the SHOALBOT has excellent movement ability in the amphibious environment compared with other published amphibious robots of the same size.

Major Challenges towards Energy Management and Power Sharing in a Hybrid AC/DC Microgrid: A Review

A fundamental strategy for utilizing green energy from renewable sources to tackle global warming is the microgrid (MG). Due to the predominance of AC microgrids in the existing power system and the substantial increase in DC power generation and DC load demand, the development of AC/DC hybrid microgrids (HMG) is inevitable. Despite increased theoretical efficiency and minimized AC/DC/AC conversion losses, uncertain loading, grid outages, and intermittent complexion of renewables have increased the complexity, which poses a significant threat toward system stability in an HMG. As a result, the amount of research on the stability, management, and control of HMG is growing exponentially, which makes it imperative to recognize existing problems and emerging trends. In this survey, several strategies from the most recent literature developed to address the challenges of HMG are reviewed. Power flow analysis, power sharing (energy management), local and global control of DGs, and a brief examination of the complexity of HMG’s protection plans make up the four elements of the review technique in this article. During critical analysis, the test system employed for validation is also taken into consideration. A comprehensive review of the literature demonstrates that MILP is a frequently employed technique for the supervisory control of HMG, whereas tweaking bidirectional converter control is the most common approach in the literature to achieve efficient power sharing. Finally, this review identified the limitations, undiscovered challenges, and major hurdles that need to be addressed in order to develop a sustainable control and management scheme for stable multimode HMG operation.

Integration of rail freight with dry ports: A route for seaport regionalisation

Due to economic and geographical causes, the reformation of rail freight transport is now in progress in a number of countries. Railroads are ideal for moving huge quantities of non-bulk, specialised, and bulk cargo. Malaysia's rail network has developed in comparison to other modes. However, its administration and contributions are little researched and frequently unclear in the current literature. In this country, rail is mostly used for passenger transportation, and the amount of rail freight in maritime trade is negligible compared to road freight. This scenario affects the efficacy of inter-regional and intra-regional freight delivery, diminishes the competitiveness of seaports, creates a monopoly for road freight transport, and depletes road infrastructure for extensively facilitated road freight transit. This article focuses on investigating concerns about existing rail freight transport and its improvement methods, the influence of rail freight transport on seaport competitiveness, and the relationship between rail freight transport and seaport dwell time. An exploratory factor analysis (EFA) was conducted to achieve the goals of this work. Approximately forty (40) Malaysian rail operators, their clients, and multimodal transport operators participated in the online survey. The findings indicate that the primary challenges with the Malaysian rail system are performance, transit time reliability, and capacity use. Improving the rail infrastructure will have a good impact on the service dependability, freight distribution, and operation management of a seaport. By enforcing institutional integration, expanding infrastructure support systems, and successfully managing infrastructure maintenance, the rail system may be enhanced. By synchronising seaport operation, efficiency, management, and container rotation, rail freight operations can enhance seaport transit time. To maintain trade competitiveness and provide a balanced freight distribution network, the role of rail freight must be increased.

A cantilever-based, ultrahigh-vacuum, low-temperature scanning probe instrument for multidimensional scanning force microscopy.

Cantilever-based atomic force microscopy (AFM) performed under ambient conditions has become an important tool to characterize new material systems as well as devices. Current instruments permit robust scanning over large areas, atomic-scale lateral resolution, and the characterization of various sample properties using multifrequency and multimodal AFM operation modes. Research of new quantum materials and devices, however, often requires low temperatures and ultrahigh vacuum (UHV) conditions and, more specifically, AFM instrumentation providing atomic resolution. For this, AFM instrumentation based on a tuning fork force sensor became increasingly popular. In comparison to microfabricated cantilevers, the more macroscopic tuning forks, however, lack sensitivity, which limits the measurement bandwidth. Moreover, multimodal and multifrequency techniques, such as those available in cantilever-based AFM carried out under ambient conditions, are challenging to implement. In this article, we describe a cantilever-based low-temperature UHV AFM setup that allows one to transfer the versatile AFM techniques developed for ambient conditions to UHV and low-temperature conditions. We demonstrate that such a cantilever-based AFM offers experimental flexibility by permitting multimodal or multifrequency operations with superior force derivative sensitivities and bandwidths. Our instrument has a sub-picometer gap stability and can simultaneously map not only vertical and lateral forces with atomic-scale resolution, but also perform rapid overview scans with the tip kept at larger tip–sample distances for robust imaging.

Effect of external cavity length on the coherence properties in a multimode semiconductor laser

Investigation of the coherence properties of a multimode semiconductor diode laser subjected to an external optical feedback is reported. Suitable multimode Lang-Kobayashi rate equations are solved numerically for this investigation. Suppression of threshold reduction has been found to occur for relatively long cavity delay times and for relatively high modal operation. This investigation provides numerical evidence of the role of multimode operation on the laser coherence without having to use any explicit decoherence element in the external cavity.

Understanding the factors associated with one-way and round-trip carsharing usage based on a hybrid operation carsharing system: A case study in Beijing

As carsharing is promoted in many cities, studying the factors related to station-level demand under multi-mode operating carsharing systems will help better develop carsharing programs. In this paper, the number of transactions is calculated to represent the carsharing demand based on the data from a one-way and round-trip hybrid operation carsharing system in Beijing. The generalized additive model is then conducted with carsharing demand as the dependent variable and five groups of independent variables: station attributes, public transit, built environment, weather, and consumption features. The main results are: (1) the one-way station has a substitution effect on the round-trip station; (2) the one-way and round-trip stations not only have considerable demand in places well served by transit but also can play different and complementary roles in areas underserved by transit; (3) the percentage of residential POIs, the POI-mixed entropy, and the number of cars per household are the most statistically significant factors; (4) weather conditions such as precipitation, high temperatures, and poor air quality play a positive role in carsharing usage; (5) personalized incentives help attract more usage, while the positive effect is minor; (6) both population density and average consumption are highly nonlinear to carsharing usage. Population densities of around 10,000 people/km2 have the largest positive effect on one-way station usage and around 6,500 people/km2 have the largest negative effect on round-trip station usage. When the average consumption exceeds 100 RMB, the usage of one-way stations decreases more rapidly compared to round-trip stations. This study can help the operators understand and refine their business strategies, and can provide insights into determining the location and mode of carsharing stations.

Fuel property impacts on gaseous and PM emissions from a multi-mode single-cylinder engine

The U.S. Department of Energy’s Co-Optima initiative has focused on improving fuel economy and vehicle performance while reducing emissions through the simultaneous development of emerging sustainable fuels with beneficial properties and advanced combustion strategies. A major thrust has been the development of advanced compression ignition (ACI) combustion strategies of gasoline range fuels in combination with spark-ignited (SI) combustion in a single engine capable of multi-mode operation to achieve high power density with enhanced part load efficiency. The aim of this study was to further the understanding of how emissions from both ACI and SI strategies operating on the same fuels in the same engine are impacted by different fuel properties. This investigation focused on particulate matter (PM) and gaseous hydrocarbon emissions from 6 different fuels across 3 different combustion modes on the same single-cylinder engine designed for multi-mode operation: SI combustion, partial fuel stratification (PFS), and spark-assisted compression ignition (SACI). In each of these modes, 3 different CA50 phasings were studied such that all 6 fuels could be studied at the same phasings. Three of the six different fuels used were specially formulated in a previous investigation to study the impact of fuel distillation and aromatic content while maintaining the research octane number (RON) and octane sensitivity. Additionally, neat isooctane and two ethanol containing fuels (RD5-87 and Co-Optima E30) were studied. Different fuel and phasing impacts on emissions were observed across the three combustion modes. Fuel properties were found to impact soot PM and particle number more than the CA50 phasing, while the phasing had more impact on NOx emissions. The NOx emissions were reduced in the PFS mode for all fuels compared to SI combustion, but the SACI combustion mode did not reduce NOx emissions. Although PFS produced low soot PM emissions like SI, total PM mass emissions were significantly higher due to large organic carbon (OC) PM mass contribution. Both PFS and SACI had greater particle number emission than SI operation with small nuclei mode particles dominating in PFS compared to large agglomeration particles in SACI.

Speed Range Extension of Dual-Stator PM Machine Using Multi-Mode Winding Switching Strategy

In this paper, a novel winding switching (WS) strategy is proposed for the speed range extension of a dual-stator permanent magnet machine (DS-PMM), which can achieve simple and effective dynamic mode conversion over an entire operating region. Two types of WS circuits with an inverter and two switch groups were first designed to enable the winding reconfiguration of the machine, which could operate in three modes. The WS principle was then elucidated by introducing simplified equivalent circuits. Besides, the torque–speed curves of the machine under different operating modes were analyzed, based on the mathematical model. A speed-based WS controller was, subsequently, designed to generate the WS control signal and realize the multi-mode operation according to real-time operating conditions. The feasibility of the proposed WS strategy for extending the speed range of the DS-PMM was, finally, verified by experiments.

Multimode Operation Mechanism Analysis and Power Flow Flexible Control of a New Type of Electric Energy Router for Low-Voltage Distribution Network

Due to limitations of topology, the series architecture electric energy router (SA-EER) for low-voltage distribution network (LVDN) has the disadvantages that the energy transmission range is limited to 100% and reactive powers are unable to operate flexibly. For this reason, a new type of EER with series-parallel architecture (SPA-EER) is constructed in this paper, and it can break through the above disadvantages in SA-EER. In addition to series-parallel architecture, a two-degree-of-freedom power flow flexible control strategy (TDF-PFFCS) is proposed to further support the realization of these two breakthroughs. According to TDF, the operation states of SPA-EER can be discriminated into 6 modes, and then their operation mechanisms are analyzed. Considering the rated capacity limitations of LVDN ports and power electronic converters in SPA-EER, the operation ranges of TDF are discussed, and constraint relationships between TDF and these rated capacities are further established, so as to avoid the issue of over-limit rated capacities. Finally, the simulation results prove that the constructed SPA-EER and proposed TDF-PFFCS can achieve the transmission targets that the maximum allowable amounts of active and reactive powers are 200% and 120% respectively, which provides new design ideas and solutions for EERs to realize the high-power energy flexible transmission.