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The values of the constraints are determined using the finite element method developed in another paper [Rajasekaran, Equations for tapered thin-walled hybrid composite spatial members of generic section. Solids and Structures, submitted for publication].
The results produced by this model allow the decision-maker to investigate the relationships between objective function values, values of the decision variables, values of the constraints, dual variables (the reduced costs), and the sensitivity of the objective function.
A Matlab simulation has been employed using the Kern's method of design of extended surface heat exchanger to determine the behavior on varying the values of the constraints and studying the overall behavior of the heat exchanger with their variation for both cases of triangular and square pitch arrangements, along with the values of pressure drop.
Table 5 Values of the constraints to avoid collisions between manipulator bodies, laser beam and object bodies Manipulator bodies (mm) Laser beam (mm) x direction ≥450.0 - y direction - - z direction ≥0.0 - Manipulator bodies ≥0.0 ≥0.0 Object ≥0.0 - Car part 1 ≥0.0 ≥0.0 Car part 2 ≥0.0 ≥0.0.
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Table 1 presents the values of the constraint parameters used in this paper.
The specific values of the constraint used to generate this figure are Pr { D l u ≥ 50 } ≤ 0.01 ∀ u. Results presented in Figure5b show a similar behavior as those in Figure5a.
In practice, we can choose the initial penalties based on the maximum value of the constraint that is associated with each of the penalty variables.
The tracking error due to the deadzone and disturbance can be suppressed within the predefined error boundary simply by tuning the gain value of the constraint switching function and without the addition of an extra compensator.
The results show that the quantity of impact motions with the forcing period fully depends on the value of the constraint stiffness and such period-one multi-impact motions predominantly occur in low frequency and small clearance domain.
A multiplier λ α(t T) is associated with each constraint α at each time point T. The value of the multiplier is determined by the value of the constraint at that time T. We here determine the value by fitting equation (1) to the data and we interpret λ α(t T), the value of the multiplier α at time T, as the contribution of transcription pattern α at that time.
Although the energy-increment-based selective constraints perform better than the equal constraint, it does not perform as well as the empirical selective constraints estimated from the JTT, WAG, LG, and KHG, indicating the good quality of their empirical values of the selective constraints.
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