Design Parameters. For the railway case study, two kinds of parameters can be di erentiated. The rst group of parameters correspond to real numbers (or function of real numbers) such as Kinetic energy, communication or physical movement delay, track length, track slope (function of position) or traction acceleration (function of speed), or breaking force. The other group of parameters is rather a choice of decomposition of a whole track map into several distributed one, and the corresponding distributed interlocking. Thus, such parameters are a set of subsets of the track map database tuples. One can also consider a varying number of trains. The parameters may be related, such as minimal and maximal kinetic energy, or minimal or maximal slope, or traction acceleration.
Design Parameters. DSE is used in building automation to: (a) identify the optimal equipment and control settings for an existing building; (b) study the equipment scal- ability over different building thermal characteristics. In the following we highlight the key design parameters used in the building automation case study: • Equipment Design Parameters: tuning these parameters lead to iden- tify the optimal thermal supply settings to a building using Fan Coil Units (FCUs).
Design Parameters. (i) The design storm shall be a 100-year return period, for a 1-day, 2-day or 5-day duration storm event whichever generates critical hydraulic conditions in the impacted drainage system that is within the watershed either upstream or downstream of the Concession Highway (an “Impacted Drainage System”); and
Design Parameters. For the automotive case study, two categories of parameters can be differ- entiated: The first group of design parameters that can be varied during an DSE experiment defines the vehicle: vehicle mass, aerodynamic drag coeffi- cient cw, rolling friction coefficient crr, battery capacity C, and the full load curve, defined by the maximum engine speed nmax and the maximum torque Mmax. The second set of parameters defines the route the vehicle takes to get from the start position to its destination. These parameters can be de- scribed as a set of coordinates. For a typical DSE experiment in the context of INTO-CPS, the first set of parameters, defining the vehicle, is most likely the more relevant group. The vehicle design parameters can depend on each other, e.g. the battery capacity has an influence on the total mass.
Design Parameters. The required structural CIPP wall thickness shall be based on the guidelines in the appendix of ASTM F1216-93 and with design parameters and physical properties listed in this section. Design formula used shall be ASTM F1216-93. For fully deteriorated, use Equation X1.3 & X1.4 and for partially deteriorated, use Equation X1.1 & X1.2. Any layers of the tube that are not saturated with resin prior to insertion into the existing pipe shall not be included in the structural CIPP wall thickness: SITE SPECIFIC INFORMATION
Design Parameters. In the agricultural case study, we have two categories of parameters. The rst category de nes the robot and its operation conditions. The second category de nes the parameters of the surrounding environments. The rst category has internal dependencies, like total weight, wheel size/operation speed, sensors and control software. But there are also dependencies between the two categories, the wheel slip will a ect the operating speed and the surface type will a ect the wheel slip. Crop type will a ect the width of the robot because the robot needs to t the row distance for the current crop. Current placement of the robot in the environment has a signi cant impact on how the controller should operate in terms of movement and operational strategy.
Design Parameters. In the agricultural case study, we have two categories of parameters. The first category defines the robot and its operation conditions. The second category defines the parameters of the surrounding environments. The first category has internal dependencies, like total weight, wheel size/operation speed, sensors and control software. But there are also dependencies between the two categories, the wheel slip will affect the operating speed and the surface type will affect the wheel slip. Crop type will affect the width of the robot because the robot needs to fit the row distance for the current crop. Current placement of the robot in the environment has a significant impact on how the controller should operate in terms of movement and operational strategy.
Design Parameters. 1. The political agreement from 22.05.2023 states that ministerial approval of a hydrogen infrastructure construction project depends on Energinet’s ability to demonstrate concrete, long-term demand and willingness-to-pay from future users of the hydrogen infrastructure. Another political agreement about financing, which may specify this requirement further, is currently underway.
Design Parameters. 6.4.7.2.1 Conveyor specifications Take-out conveyors (02EAB21 and 00XXX00) Xxxxxxxx 0000xxx Belt width 1800 Belt speed 3.2m/s Drive system Single drive motor arrangement Idler roll diameter 127mm Stacker feed xxxxxxxx Xxxxxxxx 0000xxx Belt width 1800 Belt speed 3.2m/s Drive system Single drive motor arrangement Idler roll diameter 127mm Xxxxxxxx xxxxxxxxx Xxxxxxxx 0000xxx Belt width 1800 Belt class ST1600 CONTRACT 42 ECC3 COVER PAGES Belt speed 3.2m/s
Design Parameters. This chapter lists the standards and constraints that will control the project, including applicable codes,ordinance, and regulations. A brief Code Summary for the project will be included.
