Related Experiment Video
Updated: Apr 18, 2026
11:53
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
13.6K
Multi-objective genetic algorithm for the optimization of a flat-plate solar thermal collector
Optics Express
|January 22, 2015
Summary
We optimized a solar thermal collector using a genetic algorithm to maximize solar absorptance and minimize thermal emittance. This approach yielded highly efficient collector designs competitive with record-setting values.
Area of Science:
- Materials Science
- Renewable Energy Engineering
- Computational Optimization
Background:
- Flat-plate solar thermal collectors are crucial for renewable energy.
- Optimizing solar absorptance (α) and thermal emittance (ε) is key to collector efficiency.
- Existing optimization methods may not efficiently explore the trade-offs between α and ε.
Purpose of the Study:
- To develop and apply a multi-objective genetic algorithm for optimizing flat-plate solar thermal collectors.
- To determine optimal geometrical parameters for maximizing solar absorptance and minimizing thermal emittance.
- To identify Pareto-optimal solutions for the trade-off between solar absorptance and thermal emittance.
Main Methods:
- Development of a multi-objective genetic algorithm.
- Application of the algorithm to a solar collector with an Al substrate and NiCrOx/SnO(2) coatings.
- Evaluation of geometrical parameters to maximize α and minimize ε.
Main Results:
- The multi-objective genetic algorithm generated a set of Pareto-optimal solutions.
- Achieved high solar absorptance (α) and low thermal emittance (ε).
- A specific solution demonstrated α = 97.8% and ε = 4.8%, competitive with literature records.
Conclusions:
- The developed multi-objective genetic algorithm is effective for optimizing solar thermal collectors.
- The optimized collector designs offer high performance in terms of solar absorptance and thermal emittance.
- The Pareto-optimal solutions provide valuable insights for designing next-generation solar thermal technologies.
Related Concept Videos
01:20Maxwell-Boltzmann Distribution: Problem Solving
3.2K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
3.2K
01:28Methods of Medium Optimization
63
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
63
01:27Thermal expansion and Thermal stress: Problem Solving
2.5K
San Francisco's Golden Gate Bridge is exposed to temperatures ranging from -15 °C to 40 °C. At its coldest, the main span of the bridge is 1275 m long. Assuming that the bridge is made entirely of steel, what is the change in its length between these temperatures?
To solve the problem, first, identify the known and unknown quantities. The initial length (L) of the bridge is 1275 m, the coefficient of linear expansion (α) for steel is 12 x 10-6/°C, and the change in temperature (ΔT) is 55...
To solve the problem, first, identify the known and unknown quantities. The initial length (L) of the bridge is 1275 m, the coefficient of linear expansion (α) for steel is 12 x 10-6/°C, and the change in temperature (ΔT) is 55...
2.5K
01:26Optimization Problems
197
Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
197
02:44Heating and Cooling Curves
29.1K
When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance,...
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance,...
29.1K
01:02Fluid Pressure over Flat Plate of Variable Width
2.2K
When a flat plate is submerged in a fluid, the fluid exerts pressure on the plate. This pressure can lead to many different phenomena, including drag and buoyancy. To understand the behavior of the fluid over a flat plate of variable width, it is essential to analyze the distribution of the pressure exerted.
The pressure distribution on the plate can be calculated by determining the force that acts on a differential area strip of the plate. Thus, the magnitude of the force is equal to the...
The pressure distribution on the plate can be calculated by determining the force that acts on a differential area strip of the plate. Thus, the magnitude of the force is equal to the...
2.2K