Flow Demand Research Articles

Estimating the Effects of Freeway Weaving Section Length on Level of Service Based on Microsimulation

At freeway weaving sections, traffic congestion and accidents are frequent because of the disturbance generated by merging or diverging vehicles. To reduce the disturbance and accordingly improve the level of service (LOS), an appropriate length of weaving section should be established. According to the US-HCM, the weaving section density, which is a surrogate for LOS, is determined by weaving length, traffic volume, and weaving volume ratio. However, it is not yet clear whether the US-HCM accurately estimates the density for various traffic conditions. The purpose of this study is to evaluate the effects of weaving length under various traffic conditions through microscopic traffic simulation VISSIM. The GA optimization method is applied to build the car-following and lane-changing models in VISSIM. The results show that weaving length is a critical determinant of LOS and short weaving length significantly increases traffic congestion. Increasing the length of the weaving section is a good countermeasure for alleviating traffic congestion. This study also proposes the appropriate weaving section length, with which the upstream LOS can be maintained in the weaving section. These results would serve as valuable information in the planning or design phase of a weaving section given that the flow demands are specified.

Veno-Pulmonary Arterial Extracorporeal Membrane Oxygenation in Severe Acute Respiratory Distress Syndrome: Should We Consider Mechanical Support of the Pulmonary Circulation From the Outset?

Veno-Pulmonary Arterial Extracorporeal Membrane Oxygenation in Severe Acute Respiratory Distress Syndrome: Should We Consider Mechanical Support of the Pulmonary Circulation From the Outset?

Identifying asynchronies: Early cycling

Mechanical ventilation is a lifesaving treatment but can be associated with some complications such as ventilator-induced lung injury, ventilator associated pneumonia or ventilation induced diaphragm dysfunction. Although partial ventilatory support is preferred to limit some of the complications associated with controlled mechanical ventilation, there could be some problems like asynchrony between the patient and the ventilator. Asynchronies occur when the ventilator’s breath delivery does not match the patient’s ventilatory pattern or is inadequate to meet their flow demand. Asynchronies can lead to patient’s discomfort, prolong mechanical ventilation, intensive care unit stay and mortality. Early cycling occurs when the patient’s neural inspiratory time is longer than the inspiratory time imposed by the ventilator. It is a common cause of double trigger.

A Novel High Gain Non-Isolated Three-Port DC–DC Converter for DC Microgrid Applications

In this paper, a high gain nonisolated three-port bidirectional DC–DC converter is proposed to interface solar photovoltaic and battery energy storage system to DC bus with a reduced number of components. Four modes of operation based on the power flow and load demand are identified. The operating principle of the proposed converter and its operational waveform for all four modes of operation is described in this paper. The steady-state analysis of the proposed converter is performed to determine the voltage gain of the converter in all four modes of operation. The steady-state analysis is done for both continuous conduction mode and discontinuous conduction mode; and the boundary condition. The reduced number of components to achieve high-voltage gain ensures the lowering of the cost and weight of the converter. The analytical results are validated utilizing the simulation results from PSCAD and hardware results. Also, the results indicate that the ripple in the current and voltage is reduced significantly.

Refined Calculation of Multi-Objective Ecological Flow in Rivers, North China

The concepts and calculation of basic, suitable, and fine ecological flow are put forward, and an integrated multi-method to calculate the ecological flow in rivers under multi-objectives is explored. Based on this, a refined calculation theory and method of a multi-objective ecological flow division based on time and space is proposed. That is, three commonly used methods, namely, the hydrology method, the hydraulics method, and the habitat method, are selected to finely calculate the ecological flow demand at different periods, in different sections, and under different ecological objectives. This approach breaks through the traditional ecological water demand calculation method based on hydrology and develops a river ecological flow calculation method based on water environmental protection objectives. A refined calculation method of ecological flow division based on time and space is developed to ensure that the ecological-hydrological process in rivers and lakes meets the ecological flow demand in different periods, different reaches, and different ecological objectives. Taking eight rivers entering Baiyangdian Lake as an example, the ecological flow demand in different river sections under different ecological objectives at different times is calculated to ensure the ecological flow process. The results show that the range of basic ecological flow demand range is 0.07–3.87 m3/s, the range of suitable ecological flow demand is 0.51~10.74 m3/s, and the range of fine ecological flow demand is 0.71~20.29 m3/s. In terms of spatial distribution, Ping River has the lowest demand for ecological flow, and the Zhulong River has the largest. In terms of the interannual ecological demand, those of the Baigou River, Fu River, Xiaoyi River, and Zhulong River are larger. In the demand process across the year, the demand is the largest from July to September, while the demand is the smallest from March to May. Similarly, most rivers face such problems as a sharp decline in runoff, drying up of the river, and an urgent need to restore ecology in northern China. This study also has insights and reference significance for other regions.

Low Carbon Electric Vehicle Charging Coordination in Coupled Transportation and Power Networks

As a part of the global decarbonization agenda, the electrification of the transport sector involving the large-scale integration of electric vehicles (EV) constitutes one of the key initiatives. However, the upstream generation carbon emissions associated with EV charging demand are still accountable which should not be overlooked. In this context, efficient coordination of EV flows and their charging demand in the coupled transportation and power networks promise significant decarbonization potential. Nevertheless, such potential can only be realized under adequate incentive mechanisms. In this article, a novel low carbon EV charging coordination approach in coupled transportation and power network is proposed and formulated as a bi-level optimization. In the upper level, an AC optimal power flow problem is formulated and solved to determine the optimal operation for power system. Then the carbon emission flow tracing is performed to compute rational locational-differentiated price signals. Given price-based incentives, the lower level employs traffic user equilibrium to describe the distribution of EV path flow and charging demands taking into account the uncertain traffic condition, and the aggregate charging demands are fed back to the upper level. The bi-level problem is solved iteratively through a modified particle swarm algorithm with enhanced convergence properties. Case studies demonstrate the effectiveness of the proposed coordination method in effectively mitigating the global carbon emission of the coupled networks.

FluxPAW: A standalone software to calculate flux-based plant available water

<h2>Abstract</h2> Soil water contents at field capacity (FC), the limiting point (LP), and the wilting point (WP) delimit the fractions of soil water availability, the plant available water (PAW). FC is primarily a function of soil hydraulic properties, whereas LP and WP depend on soil, plant, and atmospheric conditions. The difference between FC and WP is called total available water, whereas FC minus LP is the readily available water. The flux-based method (FBM) predicts PAW from unsaturated soil water flow, rooting characteristics, and atmospheric water demand. This paper presents FluxPAW, a software to calculate PAW using the FBM algorithm.

Research on the Economic Dispatch of Power Systems with a High Proportion of Renewable Energy based on Improved PSO

The penetration rate of renewable energy sources represented by wind power and photovoltaics in the power grid is increasing, adding complexity to unit dispatch. In this paper, a multi-objective optimization model is established for power systems containing wind power and photovoltaic economic dispatch. Firstly, the power generation cost of traditional units, the emission cost of traditional units, the power generation costs of wind turbines and photovoltaics, and the output characteristics of wind power and photovoltaics are analyzed. Secondly, a multi-objective economic dispatch model with the lowest power generation cost, the smallest emission cost, and the smallest power generation cost of new energy units are established, and the power flow balance constraint, supply and demand balance constraint, unit output constraint, and node voltage constraint are considered. Then the improved particle swarm algorithm is proposed to solve the multi-objective function to obtain better convergence and optimal solution. Finally, the simulation is carried out in the IEEE-30 node system and the HRP-38 system, which compares and illustrates the similarities and differences of the solution results of various algorithms under multi-objective and verifies the effectiveness of the algorithm.

Study on Water Regulation of Yong’an River Basin Based on Ecological Flow Guarantee

Water resources are the necessary guarantee to support the development of human society and one of the most important resources to maintain the health and stability of the ecological environment. With the gradual increase of China’s population and the gradual increase of water consumption for industry, life and agriculture, the water consumption for ecological environment can not be met. As a result, some rivers have dried up, biological habitat has been lost and species diversity has been reduced. Therefore, how to ensure the river ecological flow is a very urgent problem to be solved. This paper selects Yong’an River Basin as the research object. Yong’an river is a mountainous river with the characteristics of uneven distribution of natural runoff throughout the year and seasonal water shortage. At present, the ecological flow demand of the river has not been considered in the reservoir operation. In this paper, four different scheduling schemes are set up according to the two constraints of ecological base flow and target ecological flow. Finally, the reservoir group operation scheme with better water supply assurance rate and ecological flow assurance rate is determined.

The Barrier Effect and Pedestrian Mobility/Accessibility on Urban Highways: An Analysis Based on the Belo Horizonte/Minas Gerais/Brazil Ring Road

Historically, public policies in Brazil and many developing countries have prioritized individual motorized modes of transport. The urban space of Brazilian cities has been repeatedly remodeled, often to meet the demands of vehicle flow, to the detriment of spaces for pedestrian use. Part of the transport infrastructure, particularly the highways, are obstacles to the population’s mobility, constituting the barrier effect and expanding the physical separation of the communities that reside or transit between the adjacent neighborhoods. Based on the proposed mobility and accessibility indicators extracted from the Origin and Destination Survey databases, this article aims to analyze pedestrian mobility and access to cross the Celso Mello Azevedo Ring Road, located in Belo Horizonte/Brazil. The results indicate that, over the period analyzed, the flows of foot crossings were significantly reduced, even in areas where population growth was recorded. The evidence also shows the prevalence of crossings by motorized modes, whose mobility and access are characterized by a tangible inequality in spatial distribution, linked to the occupation pattern of the surroundings, one consequence of which is the expressive volume of accidents involving pedestrians on the highway.

Augmenting CCAM Infrastructure for Creating Smart Roads and Enabling Autonomous Driving

Autonomous vehicles and smart roads are not new concepts and the undergoing development to empower the vehicles for higher levels of automation has achieved initial milestones. However, the transportation industry and relevant research communities still require making considerable efforts to create smart and intelligent roads for autonomous driving. To achieve the results of such efforts, the CCAM infrastructure is a game changer and plays a key role in achieving higher levels of autonomous driving. In this paper, we present a smart infrastructure and autonomous driving capabilities enhanced by CCAM infrastructure. Meaning thereby, we lay down the technical requirements of the CCAM infrastructure: identify the right set of the sensory infrastructure, their interfacing, integration platform, and necessary communication interfaces to be interconnected with upstream and downstream solution components. Then, we parameterize the road and network infrastructures (and automated vehicles) to be advanced and evaluated during the research work, under the very distinct scenarios and conditions. For validation, we demonstrate the machine learning algorithms in mobility applications such as traffic flow and mobile communication demands. Consequently, we train multiple linear regression models and achieve accuracy of over 94% for predicting aforementioned demands on a daily basis. This research therefore equips the readers with relevant technical information required for enhancing CCAM infrastructure. It also encourages and guides the relevant research communities to implement the CCAM infrastructure towards creating smart and intelligent roads for autonomous driving.

Evaluation of Minimum and Suitable Ecological Flows of an Inland Basin in China Considering Hydrological Variation

Ecological flows in rivers are critical to the health and stability of river ecosystems, especially for inland drylands where ecological conditions are rapidly deteriorating. Climate change and human activities lead to hydrological variation, which in turn alters the hydrological and ecological balance of local ecosystems. Therefore, it is important to study the ecological flow under hydrological variation. In this study, the second-largest inland river basin in China, the Hei River Basin, was selected as the case study. The heuristic segmentation method, monthly minimum average flow method, the Lyon method, the average flow in the driest month method, and the monthly frequency method were employed to calculate the minimum and suitable ecological flow considering hydrological variation. Then, the results of the minimum and suitable ecological flow were evaluated and compared by the Tennant method. Finally, the ecological flows were recommended for the Hei River Basin after comparison and evaluation. Results show that: (1) It is necessary and feasible to calculate ecological flow demand considering hydrological variation in the Hei River Basin. (2) The evaluation results of the minimum ecological flow are mostly at a good level or above, and those of the suitable ecological flows are mostly at the optimum range. (3) Three scenarios with different periods and frequencies were set up to obtain suitable ecological flow; and it shows that the suitable ecological flow of scenario 3 (50% frequency in all months) has the best ecological benefits, and scenario 2 (frequency is taken as 75% in spring and autumn, 50% in summer, and 80% in winter) has the best comprehensive benefits. This study can provide important reference for water resources development and utilization and ecological protection in the Hei River Basin.

Dynamic Simulation Study on Water-Supply Volume of the Hanjiang-to-Weihe River Water Diversion Project

The calculation of water supply is affected by many factors, such as water requirements, water-supply capacity, etc., which change with time and the environment. The traditional calculation methods are generally used under several fixed operating situations. The scenarios are too few to cover the various situations encountered in actual operations and take insufficient account of boundary conditions, such as reservoir inflow, water requirements, etc. The water-supply schemes facilitated by these methods are finite and not adaptable to the ever-changing, producing environment. Therefore, based on a traditional water supply-demand balance analysis, this study established a dynamic calculation model that takes into account different variables, such as reservoir inflow, ecological flow, and water demand. This study also constructed a dynamic simulation system based on the comprehensive, integrated platform and dynamic calculation model, which shortens the calculation period from a month to a day. The results show that the water-supply assurance rates calculated under different conditions reach higher than 93.9% for domestic and production, and higher than 50.9% for agriculture, which all exceed the design assurance rates. Additionally, the dynamic calculation model can significantly improve the calculation efficiency, playing an important role in the formulation of the project-operation plan and project-benefit evaluation.

MiFi: Bounded Update to Optimize Network Performance in Software-Defined Data Centers

A controller needs to solve the multi-commodity flow problem and globally update the network under tight time constraints to maintain optimal network configurations. This centralized optimization in data centers involves many variables and constraints, which has a slow convergence speed and little scalability. In this paper, we propose MiFi, which aims to Minimize Flow cost or intuitively average transmission delay (delay or latency of flows), under reconfiguration budget constraints in data centers. Thus, we formulate this optimization problem as a constrained Markov Decision Process and propose a set of algorithms to solve it in a scalable manner. We first develop a propagation algorithm to identify the flows mostly affected in terms of latency and configuration in the next update. Then, we set a limitation range (the subset of switches requiring network updates) for updating them to improve adaptability and scalability by updating a less number of flows each time to achieve fast operations. Further, based on the Drift-Plus-Penalty method in Lyapunov theory, we propose a heuristic policy without prior information of flow demand and a renewal policy with a performance guarantee to minimize the additive optimality gap. To the best of our knowledge, MiFi is the first paper that studies the range and frequency of flow reconfigurations, which has both theoretical and practical significance in the area. Emulations and numerical simulations, which are much better than the estimated theoretical bound, show that MiFi outperforms the state of the art algorithms in terms of latency by over 45% while making improvements in adaptability and scalability.

Energy Contour Forecasting Optimization with Smart Metering in Distribution Power Networks.

Smart metering systems development and implementation in power distribution networks can be seen as an important factor that led to a major technological upgrade and one of the first steps in the transition to smart grids. Besides their main function of power consumption metering, as is demonstrated in this work, the extended implementation of smart metering can be used to support many other important functions in the electricity distribution grid. The present paper proposes a new solution that uses a frequency feature-based method of data time-series provided by the smart metering system to estimate the energy contour at distribution level with the aim of improving the quality of the electricity supply service, of reducing the operational costs and improving the quality of electricity measurement and billing services. The main benefit of this approach is determining future energy demand for optimal energy flow in the utility grid, with the main aims of the best long term energy production and acquisition planning, which lead to lowering energy acquisition costs, optimal capacity planning and real-time adaptation to the unpredicted internal or external electricity distribution branch grid demand changes. Additionally, a contribution to better energy production planning, which is a must for future power networks that benefit from an important renewable energy contribution, is intended. The proposed methodology is validated through a case study based on data supplied by a real power grid from a medium sized populated European region that has both economic usage of electricity-industrial or commercial-and household consumption. The analysis performed in the proposed case study reveals the possibility of accurate energy contour forecasting with an acceptable maximum error. Commonly, an error of 1% was obtained and in the case of the exceptional events considered, a maximum 15% error resulted.

A modified Gould-Dincer method to assess yield of carry-over reservoirs with environmental water requirements

Protecting freshwater systems to ensure sustainability requires diagnosing threats over a broad range of scales, from local to global. There is growing acceptance that environmental flows must be protected to sustain river channels and floodplain ecosystems downstream of reservoirs. Meeting environmental water requirements has proven difficult because they reduce water yield available for human use – a particular challenge in regions already experiencing declining water availability with climate change. A further challenge is the difficulty of assessing the impact of environmental water requirements on water availability for other purposes. This paper provides a modification of the Gould-Dincer method to assess the yield of carry-over reservoirs subject to environmental water requirements. The method characterizes reservoir inflows using readily available flow characteristics (annual mean and Cv). We develop and test the method using ten examples with well-understood environmental water requirements and a range of annual flow Cv s. We then demonstrate this method at continental scale, to investigate the impact on yield of providing high-reliability supply including environmental water requirements, under a changing climate. According to our results, considering climate change and environmental flow provision simultaneously, the decline in water yield is projected to be about 27% and 18% respectively for Australia and US (based on hypothetical reservoirs capacity of one times mean annual inflow). Adapting environmental flow demands to future hydrological conditions results in a 2% and 3% increase in Australia and US-wide yield for human use respectively. While further testing is needed, the method provides a simple and rapid way to estimate the impact of providing environmental flow on yield, applicable at global scale.

Numerical modelling of the cooling water system of a 106MW Hydro-Power Plant using EPANET

The present paper studies the behavior of the new proposed cooling water pumps for a 106 MW Hydro-Power Plant using EPANET. This case-study Hydropower Plant, located in the south of Romania and equipped with two Francis units 53 MW each, processing a 269m gross head, presently goes through a rehabilitation process. The cooling water system of this Hydro-Power Plant consists in four centrifugal pumps, two for each unit, and two additional pumps for the 130 MVA step-up transformer. The rehabilitation process involves the replacement of these pumps. A numerical model following the exact configuration of the cooling water system in what regards pipes diameters, lengths and roughness was designed in EPANET. The focus is to verify if the required pressure is ensured at the cooling water consumers of the plant considering their specific flow demand and if the velocity in the system pipes is within the acceptable limits during the power production process.

Therapeutic Neovascularization for Refractory Angina-Are We Any Closer?

Therapeutic Neovascularization for Refractory Angina-Are We Any Closer?

Identifying asynchronies: work shifting and double triggering

Mechanical ventilation supports the work of breathing, improves gas exchange, and unloads the respiratory muscles, all of which require good synchronization between the patient and the ventilator. Asynchronies occur when the ventilator’s breath delivery does not match the patient’s neural ventilatory pattern or is inadequate to meet the patient’s flow demand. Patient–ventilator asynchrony can be easily detected by observing the patients in those extreme situations in which they fight the ventilator; nevertheless, the vast majority of asynchronies occur without major clinical signs and go undetected or corrected without measuring patient's respiratory effort (either esophageal pressure or electrical activity of the diaphragm). Synchrony problems are common, occurring in perhaps as many as 25% of patients receiving invasive ventilation and up to 80% of patients receiving noninvasive ventilation. In this concise review, we describe work shifting and double triggering asynchronies. Keywords: Patient-ventilator asynchronies, work shifting, double triggering

Joint Application-Aware Oblivious Routing and Static Virtual Channel Allocation

Application-aware oblivious routing that supports flow-specific routing and static virtual channel (VC) assignments can achieve better performance than conventional oblivious routing by accounting for traffic demands of various flows in a given application. However, because these prior approaches consider the application-aware routing and static VC assignment steps separately, they unnecessarily impose routing restrictions to avoid deadlocks. In this letter, we propose a joint application-aware oblivious routing and static VC allocation framework that optimally solves both problems together to enable better deadlock-free performance. The experimental results show that our approach can achieve up to 30% better performance than the state-of-the-art application-aware oblivious routing algorithms and substantially better still in comparison with conventional oblivious routing approaches.