Friction loss

Summary

The term friction loss (or frictional loss) has a number of different meanings, depending on its context.

In fluid flow it is the head loss that occurs in a containment such as a pipe or duct due to the effect of the fluid's viscosity near the surface of the containment.
In mechanical systems such as internal combustion engines, the term refers to the power lost in overcoming the friction between two moving surfaces.
In economics, frictional loss is natural and irrecoverable loss in a transaction or the cost(s) of doing business too small to account for. Contrast with tret in shipping, which made a general allowance for otherwise unaccounted for factors.

Engineering Friction loss is a significant engineering concern wherever fluids are made to flow, whether entirely enclosed in a pipe or duct, or with a surface open to the air.

Historically, it is a concern in aqueducts of all kinds, throughout human history. It is also relevant to sewer lines. Systematic stud

Official source

https://en.wikipedia.org/wiki/Friction_loss

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (18)

Related publications

Related people (2)

Related people

Related units (2)

Related units

Related concepts

Related courses (18)

This course aims at understanding the basic equations behind macroscopic and microscopic transport phenomena (mass, heat and momentum).

Water resources engineering designs systems to control the quantity, quality, timing, and distribution of water to support human demands and the needs of the environment.

Les aménagements hydrauliques sont indispensable pour garantir l'approvisionnement en énergie écophile et renouvelable, de même que l'approvisionnement en eau de bonne qualité et en quantité suffisante pour lutter contre la faim, la pauvreté et les maladies dans le monde.

Related courses

Related lectures (35)

Related lectures

Related publications (18)

Flow Boiling of Carbon Dioxide at Different Channel Orientations for the Thermal Management of Future Detector Technologies at the High-Luminosity Large Hadron Collider at CERN

David Schmid

The global warming potential (GWP) of working fluids in thermodynamic cycles and their environmental impact have been gaining considerable attention within the recent years. The global objectives on climate protection are becoming increasingly ambitious, whereas the general demand for refrigeration appliances with enhanced cooling capacities is constantly growing all over the world. One promising approach to reconcile these contradictory expectations is the replacement of synthetic working fluids with natural refrigerants.The European Organization for Nuclear Research (CERN) supports the development of green technologies within the upgrades of their future accelerator facilities and Carbon Dioxide (CO2) has been identified as an eco-friendly candidate with excellent heat transfer characteristics that has the potential for replacing detrimental refrigerants in future scientific and industrial cooling applications. Inspired by the positive experiences with several mid-scale refrigeration systems, the ATLAS and CMS experiments decided to use CO2 as working fluid for the thermal management of their future Particle Tracker detectors requiring cooling capacities in the order of 0.5 MW.Pressure drop and heat transfer properties are key factors for designing thermodynamic cycles properly. Motivated by the lack of experimental data of flow boiling CO2 in vertical directions, a comprehensive research program has been launched to investigate the two-phase flow behaviour of CO2, in particular in vertical up- and downward direction. As a first step, a test facility to study the two-phase flow characteristics has been built. The setup allows measurements of the significant two-phase flow parameters in horizontal, vertical up- and downward direction in macro-scale pipes with inner diameters of 8 mm. The test conditions of the experiments cover saturation temperatures from -25 °C to +5 °C and the mass velocity ranges from 100 kg m^-2 s^-1 to 450 kg m^-2 s^-1.The performance of pressure drop models has been analyzed with data sets of 512 measurements in horizontal and 295 data points for each vertical up- and downflow direction respectively. 18 frictional pressure drop models have been compared to the horizontal data set and 21 void fraction correlations have been combined with the frictional pressure drop models accounting for the static head, resulting in 378 factorial combinations to anticipate the pressure losses in vertical directions. The best models have been identified for the entire data sets for all flow directions. Moreover, a subdivided analysis, split up according to the flow regimes, has been carried out to highlight the most accurate prediction methods with regard to the flow regimes.The heat transfer properties of flow boiling CO2 have been investigated in vertical upward direction with diabatic measurements of 5 kW m^-2 and 11 kW m^-2 respectively. The dryout phenomena is observed to be influenced by the heat flux, the mass velocity and the saturation temperature. To avoid operation at reduced heat transfer coefficients, a correlation to predict the dryout inception is suggested. The comparison of the data set to established prediction methods reveals, that the heat transfer coefficients of vertical upflow are generally underpredicted. As a consequence, an enhancement factor for vertical upflow of two-phase CO2 is suggested for two prediction models.

EPFL2022

Instrumentation development for wall shear-stress applications in 3D complex flows

Elena Berca

In the turbomachines field, friction losses are intensively studied due to their important influence in the overall efficiency of the machine. The parameter helping in quantifying these friction losses is the wall shear-stress. Its role is essential for the qualification of the boundary layer separation tendency and the losses prediction. Thus, the first aim of this PhD is to characterize the boundary layer development, in the cone of the Francis turbine. Afterwards, in the second part of this study, a new multidirectional wall shear-stress sensor is designed, manufactured and tested for the turbomachines applications. To develop this knowledge and the tools for flows prediction in the draft tube, EPFL joined major manufacturers in the context of the European initiative EUREKA project n° 1625. In the first part of the thesis, an experimental campaign is leaded in the cone of the nq 92 Francis turbine, to characterize the wall stress, using the hot-film technique. 6 operating points were investigated, covering a large operating range – from 70% to 110% from best efficiency point flow rate. For this specific draft tube, the efficiency characteristic has a sever drop, close to the best efficiency point, and the wall shear stress evolution in this region is pointed out. The calibration and measurement procedures are exposed and the accuracy study is performed. The evolution of the wall shear-stress steady values related to the spatial position of sensor – 16 positions were explored – and to the corresponding operating point is analyzed. A boundary layer separation tendency for the part load operating points is pointed out, as well as the bend influence on the spatial evolution of the wall shear-stress. These results were used to validate numerical calculation in the draft tube. Additional LDV measurements combined with the wall shear-stress results allowed to reconstruct the boundary layer. The best fit for representing the boundary layer is obtained with a composite power law. However the 3D boundary layer is complex and a profound knowledge is needed. From the unsteady point of view, in the runner outlet section, the amplitude of the wall shear-stress fluctuations obtained synchronous with the runner's rotating frequency is predominant. For the partial load operating points, the main fluctuations magnitude is obtained for the rope passage frequency and its amplitude depends on 2 parameters: the σ value and the proximity of the rope to the wall. To increase the knowledge for the boundary layers in turbomachines, it is necessary to explore fully 3D unsteady boundary layers, both in the fixed and rotating parts of the machine. Thus a multidirectional sensor with specific requirements is needed for the turbomachines application: a miniature hot film probe, which can be implemented in the complex geometry of the turbines, a multidirectional one, to take into account the complex character of the flow, mainly the strongly 3D flow, a sensor with a sensitivity and dynamic, allowing to obtain the main flow unsteady characteristics (guide vanes wake, runner blades wake, rope frequency, turbine-circuit interaction frequency, etc.), a good electrical isolation between the surface of the probe, which comes in contact with the water, and with the hot-film support. In this way, the second aim of this PhD becomes the design and development of a new multidirectional wall shear-stress sensor for turbulent boundary layer research for turbomachines applications. The development of the new multidirectional sensor implies technological developments using microtechnology, as MEMS offers opportunities for developing and manufacturing sensors with regard to complex applications, allowing, in the same time, a high accuracy at low cost. The new sensor represents a bridge between 2 different disciplines: micromechanical technology and fluid mechanics. Its concept is based on the heat transfer generated by a hot film with a general top-area of 1.12 × 0.1 mm and a thickness of 110 nm. The film, in platinum, is maintained at a constant temperature, of 65°C, by a feed-back electronic. Key process steps in fabrication of the new device are lithography, bulk micromachining, thin film deposition, surface micromachining, lift-off and chemical mechanical polishing. The manufacturing of new miniature wall shear-stress sensor is based on a combination of these techniques. A specific development is performed for the achievement of an insulating surface to reduce the heat conduction between the hot film and the sensor body, on which the hot film is deposed. This surface is obtained by manufacturing silicon dioxide layers, of 4 µm, by DRIE technique, in order to create high-aspect-ratio silicon pillars, which are then oxidized and/or refilled with LPCVD oxide or nitride. One of the major criteria for the trenches filling was the surface planarity at the end of the refill. 2 parameters are optimized: the thickness and the silicon pillars arrangement. Thermal numerical computations were carried out using Ansys and they allowed the achievement of the optimum thermal isolation thickness between the heated structures and the surrounding structures. During the development of the new wall shear-stress probe, the main topics, achievements and contributions can be categorized into: design of a new wall shear-stress sensor, fabrication steps development, validation and optimization of the design, numerical simulations of the thermal behavior of the heated-films, manufacturing of the new device. The new sensor is characterized in terms of time response, electrical insulation between the surface of the probe, which comes in contact with the water, and the hot-film, and reliability. The sensor is robust, with a good sensitivity for water measurements. The main improvements, which make the current device distinct, are its design for a directional response for 3D turbulent boundary layer study and the insulating surface for substantially reduction of the heat losses by conduction between the film and the surrounding substrate.

EPFL2007

The milling process has been continuously optimized from many aspects: forces, velocities, stability, quality. Numerous papers have been published that report results in the domain of toolpath optimization with criteria such as raising the quality of the machined part, obtaining a stable machining process and maximizing the material removal rate. However, only recently researchers have started investigating the ecological impact of machining processes. With the constantly increasing prices of electrical energy and all environmental problems caused by the production and waste of the energy, it has become indispensable to look for ways to optimize machining processes from the energy consumption aspect, too. It is in this domain, then, that the work described in this dissertation contributes – to add a new criterion for the sustainable operation of machine tools: reducing the energy consumption during the use phase of the machine tool. The total energy spent in a machining process is the sum of power spent by all machine tool subsystems multiplied by the time that they are working. Therefore, the operating strategies for increasing energy efficiency for the high-speed machining processes must be oriented towards the reduction of the total machining time (productive and unproductive) and reduction of instantaneous consumed power in the machining process or, preferably, both. There are many causes for milling process time and energy inefficiency. The major sources of potential time reductions include: (i) the issues related to the geometry and topology of the toolpath („air-time”, overlapping segments, gouge and uncut regions, orientation of the toolpath), (ii) the issues related to the kinematics of the feed drives (the feed velocity/acceleration profile). The possible domains for power consumption reduction are related to the forces that exist in the machining process (cutting, inertial, gravitational and friction forces). The power invested to overcome the cutting force is necessary for the machining process but its consumption should be optimized through constant cutting engagement and feedrate scheduling strategies. The other forces are responsible for the pure mechanical power loss and they should be minimized. The optimization variables for inertial and gravitational forces include the feed motion profile and moving mass configuration, while friction losses are load and/or velocity dependent. In addition, there are some power losses in the electric components of machine tool drives (electrical power losses), whose dependency on velocity and mechanical load can also be modeled. Despite many research efforts to analyze and model the phenomena causing inefficiency of the machining process, they are usually not taken into account during milling process planning. In fact, rare are the attempts to use this knowledge to optimize the milling process with more than one of the above mentioned criteria. The reason for that lies in the fact that increasing the instantaneous values of tool engagement and feedrate in order to minimize total machining time also increases the consumed power and, indirectly, deteriorates the tool and/or destabilizes the cutting process. The existence of conflicting criteria in the objective functions imposes the use of evolutionary algorithms for multiobjective optimization. The process of experimental validation of such an optimization model requires costly and complex external hardware setup and it is also time consuming. Hence, there is an emerging need for the development of an accurate model, which would be used for the simulation of the milling process and testing the competing optimization strategies. The ultimate goal of contemporary manufacturing science and engineering is the development of a holistic virtual machine tool system. The motivation of this PhD research is to contribute to this objective by developing the “virtual milling process for prismatic parts (produced by 2.5D milling)”. This category of objects is selected, because the majority of CNC milling tasks can be performed using 2.5D milling. A very large number of mechanical parts are prismatic (their geometry consists exclusively of features that represent 2D contours extruded in a perpendicular direction). Parts that are even more complex are usually produced from a blank by a 2.5D roughing and 3D–5D finishing. Therefore, development of an accurate model of a 2.5D milling process represents a significant contribution to manufacturing engineering. Starting with above given problem description, we have defined the following research objectives: 1. Model power and energy consumption of a 2.5D milling machine as a function of the toolpath geometry (curvature and continuity), cutting engagement, real feedrate profiles and spindle rotational speed, taking into account moving mass configuration, all power losses (mechanical and electrical) in feed-axis and spindle drives and electromechanical constraints of servo drives; 2. Design an integrated software environment for simulation of the developed models; 3. Validate the model experimentally; 4. Demonstrate the potential of its use for multi-objective process optimization. Cutting engagement calculation is performed by using two competing methodologies, in order to make a comparison of their performances. The first one, the pixel based method, is based on discrete image processing, while the other, the exact method, is based on Boolean operations and vector geometry. The tests performed in more than 20 feature/toolpath combinations demonstrate that the exact method is more precise whereas the pixel-based method is computationally much faster. The machine tool operator commands a constant feedrate value. During the process, based on his/her subjective judgment, he/she can manually tune it to keep the process in the desired boundaries. One of the objectives of this research is to predict the real feedrate values so that they can be integrated in the part program before the process start. The feasible profiles of feed velocities for each toolpath segment are analyzed by answering the following questions: can the commanded feedrate be achieved and with what sequence of acceleration and deceleration phases, how much the tool has to slow down in corners and how does the feedrate profile degenerate in segments where the commanded feedrate cannot be reached? In order to determine all forces and torques, a machine tool model is developed. The following subsystems are modeled as rigid bodies (without vibrations): feed motor shaft, transmission, lead screw/nut pair, lead screw bearings, guides (sliding and rolling design), table with the workpiece and electrospindle (rotor, stator and bearings). All kinetic variables (linear and angular speeds; cutting, inertial and friction forces and torques) are then calculated in the joints of this multi-body system. The modeling of all speeds, forces and torques that occur in the machine tool system during the machining process, allows for calculation of various indicators of process time and energy efficiency: material removal rate, total machining time, useful power (invested in cutting), power loss due to the friction in the joints, power losses in electrical motors, electrical energy consumption of feed and spindle drives. In order to assess the accuracy and the reliability of the developed model two sets of experiments have been performed. The model validation is performed on several subsystem levels and the simulation results show a very good compliance with the experimental results. The first experimental setup consists of the force dynamometer, to measure cutting force components in linear axis directions, two laser optical position sensors, to measure the real feedrate and the power sensor, to measure the total power consumption of the machine tool electrical motors. The machining process was performed on the 6-axis machining center C.B. Ferrari A152 and the data acquisition platform was developed in LabVIEW 2010. The second experimental setup consists of the torque dynamometer, to measure the cutting torque directly on the spindle, the built-in current sensor that measures the motor current proportional to the electrical power consumed by the spindle and, again, the power sensor, to measure the total power consumption of the machine tool electrical motors. This time, MIKRON HPM 600U, a 5-axis milling machine equipped with the controller iTNC530, was used for the experimentation. The developed model is ready for practical implementation. Several examples have been prepared to demonstrate its capabilities in the domains of milling process simulation, sensitivity analysis and prospective optimization strategies. These examples include the prediction of various kinetostatic variables for given toolpaths, choice of the optimum machining strategy (minimization of machining time, moving mass and energy consumption) and process optimization by feedrate scheduling (reduction of cutting force fluctuation). As a conclusion, the major contribution of this PhD research is the development of a comprehensive rigid-body dynamics model of a machine tool system, aimed for the generation, simulation and optimization of 21⁄2D milling process plans. The model features several novelties compared to existing approaches: (i) it takes into account the machine tool rigid body dynamics and real tool kinematics in toolpath planning, (ii) it predicts all mechanical and electrical power losses in the machine tool system (iii) it allows the modeling of machine tool system electromechanical constraints. The model was experimentally validated on two real machine tools in different workshops and its capabilities for the simulation of different toolpath patterns and optimization of process parameters were successfully demonstrated using several examples.

EPFL2012