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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Multimachine Stability01:25

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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

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The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
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Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

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Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
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Related Experiment Video

Updated: Aug 10, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
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A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in

Youxi Hu1, Chao Liu1, Ming Zhang1

  • 1College of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK.

Sensors (Basel, Switzerland)
|February 11, 2023
PubMed
Summary

This study addresses the disassembly line balancing problem (DLBP) for stochastic parallel complete lines. A new hyper-heuristic algorithm optimizes disassembly lines for efficiency and profit, validated with gearbox disassembly.

Keywords:
disassemblydisassembly line balancing problemhyper-heuristic algorithmmulti-objective optimisationremanufacturing

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Area of Science:

  • Industrial Engineering
  • Operations Research
  • Sustainable Manufacturing

Background:

  • Remanufacturing extends product lifecycles and residual value.
  • Disassembly is crucial for component retrieval in remanufacturing.
  • Disassembly line balancing problem (DLBP) is key to efficient remanufacturing operations.

Purpose of the Study:

  • Extend the basic DLBP model to stochastic parallel complete disassembly lines (DLBP-SP).
  • Develop a multi-objective optimization algorithm for DLBP-SP.
  • Evaluate the proposed algorithm's performance and robustness.

Main Methods:

  • Developed an extended mathematical model for DLBP-SP.
  • Proposed a simulated annealing-based hyper-heuristic (HH) algorithm.
  • Conducted computational experiments and a gearbox disassembly case study.

Main Results:

  • The proposed HH algorithm effectively optimizes DLBP-SP considering workstations, workload, and profit.
  • Validated the algorithm's feasibility, superiority, stability, and robustness.
  • Demonstrated the application of DLBP to industrial equipment, specifically gearboxes.

Conclusions:

  • The novel HH algorithm provides a robust solution for multi-objective DLBP-SP.
  • The research expands DLBP applications to complex industrial equipment.
  • Optimized disassembly lines enhance the cost-effectiveness and efficiency of remanufacturing.