Optimal Velocity Research Articles

Study of the enhancement in the performance of a hybrid flat plate solar collector using water and air as working fluids

AbstractA hybrid flat solar collector was manufactured from basic materials to combine the effects of both water and air solar heaters. The reason is to increase the amount of heat delivered to water by doubling the heat sources, one from the direct beam of sun and the other from the hot air delivered by the air solar heater. In addition, the flow of water inside the solar heater is made in a thin layer so that much heat can be gained by water per unit time. The outlet hot air of the solar air heater enters air ducts that pass through the solar water heater. With a constant water flowrate of 0.0167 kg/s, three different air velocities (1.7, 2.1, and 2.4 m/s) were applied to determine the optimum air velocity that results in the maximum outlet water temperature and the maximum removal factor FR for the solar water heater. The experiment was run from 10:00 a.m. to 2:00 p.m. every day during June 2023 and the data was recorded every 15 min. The data obtained from the experiment showed that the lowest air speed (1.7 m/s) results in the highest outlet water temperature (63°C) and heat removal factor FR (0.74).

Eco-Driving on Hilly Roads in a Mixed Traffic Environment: A Model Predictive Control Approach

Human driving behavior significantly affects vehicle fuel economy and emissions on hilly roads. This paper presents an ecological (eco) driving scheme (EDS) on hilly roads using nonlinear model predictive control (NMPC) in a mixed traffic environment. A nonlinear optimization problem with a relevant prediction horizon and a cost function is formulated using variables impacting the fuel economy of vehicles. The EDS minimizes vehicle fuel usage and emissions by generating the optimum velocity trajectory considering the longitudinal motion dynamics, the preceding vehicle’s state, and slope information from the digital road map. Furthermore, the immediate vehicle velocity and angle of the road slope are used to tune the cost function’s weight utilizing fuzzy inference methods for smooth maneuvering on slopes. Microscopic traffic simulations are used to show the effectiveness of the proposed EDS for different penetration rates on a real hilly road in Fukuoka City, Japan, in a mixed traffic environment with the conventional (human-based) driving scheme (CDS). The results show that the fuel consumption and emissions of vehicles are significantly reduced by the proposed NMPC-based EDS compared to the CDS for varying penetration rates. Additionally, the proposed EDS significantly increases the average speed of vehicles on the hilly road. The proposed scheme can be deployed as an advanced driver assistance system (ADAS).

Performance Rating and Flow Analysis of an Experimental Airborne Drag-Type VAWT Employing Rotating Mesh

This paper presents the results of a performance analysis conducted on an experimental airborne vertical axis wind turbine (VAWT), specifically focusing on the MAGENN Air Rotor System (MARS) project. During its development phase, the company claimed that MARS could generate a power output of 100 kW under wind velocities of 12 m/s. However, no further information or numerical models supporting this claim were found in the literature. Extending our prior conference work, the main objective of our study is to assess the accuracy of the stated rated power output and to develop a comprehensive numerical model to analyze the airflow dynamics around this unique airborne rotor configuration. The innovative design of the solid model, resembling yacht sails, was developed using images in the related web pages and literature, announcing the power coefficient (Cp) as 0.21. In this study, results cover 12 m/s wind and flat terrain wind velocities (3, 5, 6, and 9 m/s) with varying rotational velocities. Through meticulous calculations for the atypical blade design, optimal rotational velocities and an expected Tip Speed Ratio (TSR) of around 1.0 were determined. Introducing the Centroid Speed Ratio (CSR), which is the ratio of the sail blade centroid and the superficial wind velocities for varied wind speeds, the findings indicate an average power generation potential of 90 kW at 1.4 rad/s for 12 m/s and approximately 16 kW at a 300 m altitude for a 6 m/s wind velocity.

Optimization of olive pomace dehydration process through the integration of computational fluid dynamics and deep learning

ABSTRACT This study introduces an innovative approach to optimize the dehydration process of olive pomace by combining computational fluid dynamics (CFD) and deep learning. Through CFD, it identifies the optimal air inlet velocity in a prototype of a passive direct solar dehydrator for olive pomace, which allows for the reduction of its moisture content for subsequent use as biomass. The prototype was simulated in ANSYS software, and this simulation consisted of the following steps: prototype design, meshing, selection of physical models, material assignment, boundary condition simulation, and validation of results with data obtained from the prototype. Following this process, it was concluded that the optimal air inlet velocity to the dehydration chamber is 0.1 m/s. Concurrently, an artificial neural network model was used to analyze data from sensors in the physical prototype, revealing that solar radiation and ambient temperature are the most influential variables on the temperature of the dehydration chamber. This analysis resulted in a predictive model for the optimization of the dehydration process, with a correlation coefficient of 0.9699 for temp_up and 0.9710 for temp_down, and a Willmott coefficient of 0.9999, demonstrating a high concordance between the model’s predictions and the experimental data. The model’s input variables include solar radiation, ambient temperature, and both external and internal air humidity. This integration of CFD and deep learning offers a promising methodology for improving olive pomace dehydration systems and the industry in general.

THE DEPENDENCE BETWEEN THE OPTIMAL MECHANICAL ANGULAR SPEED AND THE VARIABLE WIND SPEED FROM AN ENERGETIC POINT OF VIEW

This paper examines the fundamental elements required for operating a wind turbine (WT) at its maximum power point (MPP). It focuses on measuring the wind speed and the power output from the electric generator (EG) over time to establish the relationship between the optimal mechanical angular velocity (MAV) and the wind speed, denoted as the function ωOPTIM(V). This function is crucial for controlling the power output of the electric generator, ensuring that the WT operates at its maximum power point. The study analyzes the measurements taken from the turbines in Siliștea in Dobrogea, Romania. The paper concludes by presenting an algorithm to determine the function ωOPTIM(V).

Performance optimization of nanofluid-cooled photovoltaic-thermoelectric systems: A study on geometry configuration, steady-state and annual transient effects

In this study, we explored Photovoltaic-Thermoelectric (PV-TE) systems in-depth, addressing complexities in both steady-state and annual transient performance under realistic conditions. The analysis involved twelve distinct PV-TE configurations featuring diverse thermoelectric designs incorporating various semiconductors, multi-staging, non-uniform cross-sections, and material segmentation. Model 6, the PV-TE system with a multi-stage segmented rectangular design, emerged as the top performer, exhibiting a remarkable 12% increase in electric power output during peak sunlight compared to the base model, despite a marginal decrease in efficiency. Furthermore, this research delved into the potential of advanced nanofluid cooling, investigating options such as distilled water, titanium oxide, aluminum oxide, iron oxide, and graphene. The results underscores graphene nanofluid's superiority, demonstrating a significant enhancement in thermal management at an optimal flow velocity of 2 m/s. This improvement in thermal management refers to the effective heat dissipation and temperature control within the PV-TE system. This study underlines the critical role of strategic system design and component selection in optimizing the performance of PV-TE systems. By providing a comprehensive foundation for future developments in effective and sustainable energy solutions, this research contributes to advancing the understanding and implementation of PV-TE technology.

Wall Heat Transfer Characteristic of Parallel-plate Channel Filled with Open-cell Metal Foams in Large Flow Velocity Range

Abstract High porosity open-cell metal foams can be utilized to fill parallel-plate channels for achieving efficient cooling performance. A wall heat transfer model considering viscous and inertial heat effects is given based on local thermal non-equilibrium theory. Detailed investigations are conducted on influences of parameters on cooling performance. The results indicate that an optimum velocity exists; impacts of porosity and pore size varies with thermophysical properties of fluids and flow velocity; heat transfer resistance also depends on them; increasing foam thickness enhances cooling performance for air under identical velocities but has negligible effect for water; under identical flow rates, decreasing foam thickness improves cooling performance; enlarging base surface area is an effective approach at low flow velocities.

Numerical investigation on the heat storage/heat release performance enhancement of phase change cemented paste backfill body with using casing-type heat pipe heat exchangers

Cemented paste backfill mining technology that recycling tailings and waste rocks can effectively reduce heat damage. Heat pipe exchangers, demonstrating much higher thermal conductivity than water pipe exchangers, led to the development of a novel phase change backfill body system with a built-in casing heat pipe exchanger (HP-PCB). Numerical analysis revealed that, for the melt and solidification of a large amount of PCM, the temperature step phenomenon was observed at both heat storage and heat storage/heat release coexistence stages. Increased surrounding rock temperatures enhanced heat storage and heat release capacities, but reduced system energy efficiency. The optimal water flow velocity was identified at the laminar-turbulent transition flow rate, 0.32 m/s. An increase in water inlet temperature resulted in lower heat release capacity and system energy efficiency. The energy efficiency of the HP-PCB system exceeded that of the traditional water pipe-backfill system by 37.22%. At a surrounding rock temperature of 45 °C, cooling water velocity of 0.32 m/s, and a 6 °C inlet water temperature, the HP-PCB system achieved its highest energy efficiency coefficient, 86.38%. These findings highlight the HP-PCB system potential for efficient geothermal energy extraction in mine.

Energy Economization Using Connectivity-Based Eco-Routing and Driving for Fleet of Battery Electric Vehicles

Energy economizing using Connectivity-based eco-Routing and Driving (CeRD) is a key to conserve the resources of a fleet. This work takes maximum advantage by advising optimal energy consumption based route and velocity. Product delivery to several universities by group of Battery Electric Vehicles (BEVs), is considered. Problem contains certain constraints i.e., BEV load capacity, time window, resources restriction, speed bounds, battery charging/discharging limits and traffic. Simulation of Urban Mobility (SUMO) is used for the estimation of traffic and routes. Selection of route is based on energy consumption of traffic’s velocity. Once the traffic based energy consumptions are available, Dijkstra’s algorithm is then applied to select the route with least energy consumption. Clarke and Wright (C&W) algorithm is then applied to find the optimal sequence of visiting universities. Pontryagin’s Minimum Principle (PMP) is then applied to find the optimal velocity profiles for BEVs on the optimized routes. Results have shown 60-70% reduction in energy consumption along with improvement in charging rates as compared to the vehicles without CeRD assistance in different scenarios. Furthermore, results are validated for distance and time using online route planner, for energy efficiency using electric vehicles database and for energy consumptions using driver model based forward simulator.

Modeling of Wind Power Generation in Tegal Region using Matlab Simulink

The increasing energy demands require larger energy production. However, fossil energy sources are depleting, necessitating the use of renewable energy to replace fossil fuels and meet energy needs in Indonesia. Indonesia has a significant wind energy potential. Wind power generation modeling is carried out in one of the cities in Indonesia, namely Tegal. By using Matlab Simulink, it is expected to assist in predicting renewable energy production. Tegal is one of the regions with high wind speeds in Indonesia, specifically at 3 m/s. From the modeling, the optimal blade radius and rotor angular velocity that can generate maximum power at a wind speed of 3 m/s can be determined. Wind power generation in Tegal with a wind speed of 3 m/s has the potential to produce electrical power of 768.55 W.

Vehicle Driving Behavior Analysis and Unified Modeling in Urban Road Scenarios

To improve the simulation accuracy and efficiency of microscopic urban traffic, a unified modeling method considering the behavioral characteristics of vehicle drivers is proposed by considering the lane-changing vehicles on the inlet lanes of signalized intersections and their approach following vehicles on the target lanes as research objects. Based on the driver’s multidirectional, multi-vehicle anticipation ability and introducing lateral vehicle influence coefficients, the full velocity difference car-following model was extended to microscopic traffic models that consider the driver’s capacity for multi-directional, multi-vehicle anticipation. The extended model can describe longitudinal movements of lane changing and car followers using lateral vehicle influential parameters. The influences of traffic control signals and the type of lane change on drivers’ decisions were integrated into the model by reformulating the optimal velocity function of the basic car following the model. Similar modeling methods and components were applied to formulate four groups of experimental models and one group of test models. Vehicle trajectory data and manual observations were collected on urban arteries to calibrate and evaluate the research models, experimental models, and test models. The results show that the car-following behavior is more sensitive to the variation in the status of the lateral moving vehicle and change of lane-changing type compared to lane-changing behavior during the lane-changing process. In addition, when lane changing gradually encroaches on the target lane, the vehicle observes the driving conditions and adjusts its driving behaviors differently. This research helps to analyze travel characteristics and influence mechanisms of vehicles on urban roads, which is a guide for the future development of sustainable transportation and self-driving vehicles and promoting the efficient operation of urban transportation systems.

An eco-driving strategy for autonomous electric vehicles crossing continuous speed-limit signalized intersections

The rapid advancement of Vehicle-to-Everything communication (V2X) technology presents opportunities for enhancing traffic energy efficiency. With V2X, this paper introduces an eco-driving strategy for autonomous electric vehicles to navigate continuous signalized intersections. This strategy incorporates the realistic powertrain's working efficiency and constraints into the vehicle motion optimization. In the domain of the global path, we formulate a co-optimization problem of vehicle motion and powertrain operation to tap the vehicle energy-saving potential and derive an optimal velocity profile, considering constraints related to queue release and limit speed in intersections. In the short rolling time domain, we propose a predictive control approach for vehicle speed tracking and real-time powertrain control. Simulation results under various scenarios show the advantages of the proposed method in terms of energy consumption compared to the baseline and existing methods.

Parametric study of an empty diffuser geometric parameters and shape for a wind turbine using CFD analysis

This research examines the optimal 3D geometric parameters and shape of empty diffusers to enhance the mass flow rate of the HAWT rotor plane using a detailed parametric study. Previous works have investigated the use of diffusers to augment turbine power output; however, different curvature surfaces and the effects of all associated angles have not been considered for a thorough evaluation. This work mainly focuses on analyzing the effect of opening angles (2° to 22°), inlet shroud angles (8° to 24°), flange height ratios, flange angles (0° and 15°), and shape of the diffuser as well as flanges on velocity, pressure at the diffuser entry, and through the diffuser section at a wind speed of 4.5 m/s. At an inlet-shroud angle of 24° and an opening angle of 8°, with a diffuser flange height-throat diameter ratio of 0.3, the system achieved an 82.9% increase in flowrate. The diffuser with an inlet shroud-side lower stepped flange showed an optimum velocity of 9.12 m/s (maximum) and 8.2 m/s (average), resulting in a 102.66% and 82.2% increase in velocity, respectively. The percentage increase in velocity of the present study is 92.61%, compared with the previous maximum increase in rate of 53.8%, and then an increase in velocity of 38.81% was obtained. The optimum speed occurred at 0.175 m from the inlet section of the diffuser, indicating where the turbine should best be located. The CFD results from this work were validated with experimental data from the literature, showing a good agreement between the two. Integrated diffuser-turbine system simulation and experimental work with field tests are recommended as a way forward.

Swarm Division-Based Aircraft Velocity Obstacle Optimization Considering Low-Carbon Emissions

In the pursuit of sustainable aviation, this paper presents an innovative approach that adopts a swarm division strategy to enhance and refine the velocity obstacle (VO) method, guided by a low-carbon principle. A dynamic elliptical protection zone model forms the core of this innovative approach. Specifically, this dynamic elliptical protection zone is created based on the difference in aircraft velocity, and a swarm division strategy is introduced in this process. Initially, aircraft that share the same route and type, and have similar velocities and distances, are grouped into swarms. Then, the characteristics of the swarms, such as mass points, velocities, and protection zones, are recorded. Second, the collision cone (CC) between swarms is established, and planar geometrical analysis is used to determine the optimal relief velocity and heading of aircraft on the low-carbon objective while ensuring a safe interval between aircraft in the swarm during the relief period. Additionally, a swarm control algorithm is utilized to adjust the velocity of the aircraft by a small margin. Finally, simulation experiments are conducted using Python, revealing that the swarm relief efficiency of the enhanced VO method sees a notable increase of over 33%. Concurrently, the need for adjustments decreases by an average of 32.78%, while fuel savings reach as high as 70.18%. The strategy is real-time and operational, significantly reduces the air traffic controller (ATC) workload, improves flight efficiency and safety, and contributes positively to the reduction in carbon emissions, which is beneficial for the environment.

Feasibility and Reliability of Quadriceps Muscle Power and Optimal Movement Velocity Measurements in Different Populations of Subjects.

This study aimed to assess the feasibility and reliability of quadriceps maximal short-term power (Pmax) and corresponding optimal movement velocity (υopt-velocity at which the power reaches a maximum value) measurements in different populations of subjects. Five groups of subjects, fifty participants in each group, took part in the study: students; patients of the cardiac rehabilitation program; patients after stroke; older adults; and subjects of different ages who performed repetitive measurements with two different bicycles. The correlations calculated for the pairs of scores ranged from 0.93 to 0.99 for Pmax and from 0.86 to 0.96 for υopt (all with p < 0.001). Intraclass Correlations Coefficients (ICCs) varied from 0.93 to 0.98 for Pmax and from 0.86 to 0.95 for υopt. The standard error of measurement (SEM) varied from 16.9 to 21.4 W for Pmax and from 2.91 to 5.54 rotations(rot)/min for υopt. The coefficients of variation (CVs or SEM%) for Pmax and υopt in the stroke group were 10.6% and 11.4%, respectively; all other CVs were clearly lower than 10%. The minimal detectable change (MDC) varied from 46.6 to 59.3 W for Pmax and from 8.07 to 15.4 rot/min for υopt. MDC% varied from 9.53% to 29.3% for Pmax and from 8.19% to 31.7% for υopt, and was the highest in the stroke group. Therefore, the precision of measurements of Pmax and υopt was confirmed by very good indices of absolute and relative reliability. The proposed methodology is precise, safe, not time-consuming and feasible in older subjects and those with diseases.

Distributed Lyapunov-Based Model Predictive Control for AUV Formation Systems with Multiple Constraints

This paper focuses on the formation tracking issue of autonomous underwater vehicles (AUVs) subject to multiple constraints in three-dimensional space. We developed a novel distributed Lyapunov-based model predictive controller (DLMPC) with a fast finite-time extended state observer (FFTESO). Initially, the external disturbances and internal uncertainties of each AUV were precisely compensated using the designed FFTESO. Subsequently, we proposed DLMPC-based position tracking and velocity tracking controllers, which solved an online optimization problem to determine optimal velocities and control forces. This hierarchical framework effectively managed system constraints, such as state constraints and actuator saturation. Additionally, the Lyapunov-based backstepping control law was applied to construct stability constraints in the distributed optimization problem, ensuring the recursive feasibility and closed-loop system stability of the proposed scheme. Sufficient conditions and attraction regions to ensure stability were explicitly provided. Finally, the simulation results demonstrated that the proposed method improved both the convergence speed and tracking accuracy by at least 30% compared to other methods.

Numerical analysis of convective heat loss from a cylindrical–hemispherical receiver using a glass cover and an air curtain

AbstractIt is imperative to mitigate the convective heat loss from the receiver to improve the overall efficiency of the parabolic dish concentrator. In this study, the reductions of convective heat loss from the cylindrical‐hemispherical receiver are numerically analyzed and the model was validated by the experimental data from literature. In the first case, the impact of the glass cover on convective heat loss is examined under conditions of both natural and forced convections at various receiver orientations (γ = 0°, 30°, 60°, and 90°). Numerical results clearly demonstrate that the use of a glass cover significantly reduces the intrusion of surrounding air into the receiver cavity which leads to an enhancement of the stagnation zone inside the cavity and, as a consequence, a noticeable reduction in convective heat loss is observed. To perform analysis of the receiver with glass cover under forced convective condition, the wind velocities over the receiver are considered in the range of 1–6 m/s. The maximum reduction of convective heat loss using the glass cover is achieved to be 58.44% with wind velocity of 5 m/s at γ = 60°. In the second case, the influence of air curtain at the receiver aperture under natural convective heat loss conditions is analyzed. The analysis incorporates three variables: receiver orientation (γ = 0°–60°), nozzle width ( = 0.002–0.004 m), and nozzle outlet velocity ( = 0.5–3.5 m/s). The results show that the air curtain minimizes the outflow of receiver inside air and results in an improvement in the stagnation zone inside the cavity. The maximum effectiveness of the air curtain is found to be 43.2% at nozzle width of  = 0.004 m and nozzle velocity of  = 1.5 m/s at receiver orientation of 60°. It is also noteworthy that the optimal nozzle velocity decreases with the increase of nozzle widths.

Bidimensional Dynamic Magnetic Levitation: Sequential Separation of Microplastics by Density and Size.

There is a current gap in sample preparation techniques integrating the separation of microplastics according to their different material types and particle sizes. We describe herein the Bidimensional Dynamic Magnetic Levitation (2D-MagLev) technique, enabling the resolution of mixtures of microplastics sorting them by plastic type and particle size. Separations are carried out in a bespoke flow cell sandwiched between two ring magnets and connected to programmable pumps for flow control. The first separation dimension is based on sequential increases in the concentration of a paramagnetic salt (MnCl2), enabling magnetic levitation of microplastics with determined densities. The second dimension is based on increasing flow rate gradients and maintaining constant MnCl2 concentrations. This fractionates the magnetically levitating microplastics according to their different particle sizes. Microplastics are therefore collected by their increasing density, and the particles corresponding to each density are fractionated from smaller to larger size. Using polyethylene microspheres with defined density (1.03-1.13 g cm-3) and size (98-390 μm) as microplastic mimicking materials, we investigated their optimum threshold velocities for their size fractionation, potential effects of medium viscosity and sample loading, and types of flow rate gradients (linear, step). Performing a separation using a combination of step gradients in both MnCl2 concentration and flow rate, mixtures comprising microplastics of two different densities and three different particle sizes were separated. 2D-MagLev is simple, fast, versatile, and robust, opening new avenues to facilitate the study of the environmental presence and impact of microplastics.

Optimizing Vertical-Axis Wind Turbine Performance and Determining Optimal Velocity and Deflector Configuration Based on Wind Speed

In the realm of wind energy harnessing, Vertical-axis Wind Turbines (VAWTs) have emerged as promising alternatives. However, they face persistent challenges due to their low efficiency and poor self-starting properties. This study addresses these limitations and aims to unlock the full potential of VAWTs by conducting a comprehensive investigation. The focus of this research lies in determining the optimal operating velocities to enhance the performance of Savonius-type VAWTs, leveraging advanced deflectors. The study delves into an in-depth analysis of the optimal deflector distances and angles for the turbine, taking into account different geographical areas with varying wind velocities. To achieve this, a Savonius-type VAWT equipped with advanced wind deflectors was meticulously designed and tested. Utilizing SOLIDWORKS software, sophisticated turbine models were crafted, which were then subjected to rigorous analysis using ANSYS Fluent, Computational Fluid Dynamics (CFD) software. The research methodology involved conducting simulations across a range of wind velocities, spanning from 1 ms-1 to 8 ms-1, and changing the deflector distance from 100 cm to 150 cm from the centre of the turbine, and the deflector angle from 12 to 45 degrees. During the simulations, critical indicators of turbine performance, including moment coefficient, moment, force coefficient, and force acting on the blade, were closely examined. The study uncovered significant variations in the power output of the Savonius-type vertical-axis wind turbine (VAWT) fitted with an advanced deflector system, especially at lower wind speeds. Notably, the study revealed that at different wind velocities, the optimum deflector configuration changed, with the highest energy-generating capacity observed at 1 m/s for the wind turbine equipped with advanced deflectors. Outperforming the turbine lacking a deflector system, this inventive method demonstrates the capacity to notably boost energy generation. This novel method underscores the capacity for substantial improvements in energy production. Additionally, the research offers valuable insights into customized deflector distance and angle combinations, optimizing turbine performance for specific wind velocity ranges. By strategically positioning the deflectors, higher energy output can be achieved, making the VAWT system more adaptable and efficient across diverse wind conditions&#x0D;  &#x0D; Keywords: Vertical-axis wind turbine, Wind deflectors, Computational Fluid Dynamics, SOLIDWORKS, ANSYS Fluent

Velocity of Money and Productivity Growth: Explaining the 2% Inflation Target in the U.S. (1959–2007)

This article provides a macro-foundation for why the specific value of 2% is a valid inflation target. The approach postulates that innovations generate transactional cost savings by comparison to barter. The optimal velocity of money is derived as a function of productivity growth and of long-term and short-term interest rates, with coefficients reflecting the leverage ratio of depository institutions and the degree of bias in technical progress in the transaction technology. The model is tested for the U.S. (for aggregates M1, M1RS, and M1S) over the period 1959–2007. Setting the inflation target rate equal to the growth rate of velocity leads to an inflation rate near 2% and is akin to pursuing the Friedman k-% rule. This rule provides flexibility to prevent deflation. A long-term Taylor-type rule is derived. A robustness test is also conducted by extending the sample period up to 2023, covering sustained episodes of unconventional U.S. monetary policy.