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相关概念视频

Moisture Content and Bulking of Aggregate01:10

Moisture Content and Bulking of Aggregate

183
The moisture content of aggregates is a crucial factor in construction, particularly in concrete mixing, as it influences the total water required in the mix. Moisture content represents the water coated on the exterior surface of the aggregate existing in a saturated and surface-dry condition. The total water content of a moist aggregate is the sum of its moisture content and water absorption.
When aggregates are exposed to rain or sit in stockpiles, they absorb moisture, which must be...
183
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...
84
Design Example: Managing Concrete Workability01:14

Design Example: Managing Concrete Workability

103
This example deals with managing the workability of concrete for a raft foundation project under hot weather conditions. Workability is crucial for ensuring the concrete is easy to place, compact, and finish. In this scenario, a slump test — a common method to measure the workability of fresh concrete — initially indicated low workability. This was attributed to the rapid water loss from the concrete mix, exacerbated by the high temperatures causing the course aggregates to heat up.
103
Dynamic Modulus of Elasticity of Concrete01:16

Dynamic Modulus of Elasticity of Concrete

427
The dynamic modulus of elasticity assesses how a concrete structure deforms under impact or dynamic loads. It is typically higher than the static modulus of elasticity, measured under slow, steady loading conditions.
The sonic test is a common method to determine the dynamic modulus. In this test, a concrete beam, sized either 6 x 6 x 30 inches or 4 x 4 x 20 inches, is clamped at its center. Vibrations are initiated at one end of the beam by an electromagnetic exciter unit powered by...
427
Factors Affecting Workability01:24

Factors Affecting Workability

94
The workability of concrete is a critical characteristic that influences the ease of mixing, handling, and finishing the concrete. It is affected by several factors including water content, aggregate properties, and admixtures like air entrainment. Water plays a fundamental role as it lubricates the concrete mix, facilitating easier movement and placement. However, the water requirement varies depending on the texture and shape of aggregates. Finer particles and angular, rough-textured...
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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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用多目标颗粒群集优化为基础的面包构成型建模方法预测面包停滞.

Yusheng Zhang1, Hui Yu1, Haiyu Zhang1

  • 1China Agricultural University, College of Engineering, Beijing, China.

Journal of texture studies
|June 12, 2023
PubMed
概括
此摘要是机器生成的。

使用多目标粒子群优化 (MOPSO) 的新食品构成模型方法快速检测到面包缩. 这种方法有效地识别了爬行测试参数,并预测了粘弹性参数,以改善面包质量监测.

关键词:
空气流激光器是什么?面包拖延延时间爬行 爬行 爬行 爬行 是一个一般化的凯尔文模型.多重目标多重目标.粒子群集优化 粒子群集优化

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科学领域:

  • 食品科学与技术 食品科学与技术
  • 材料科学 材料科学 材料科学
  • 计算智能是一种计算智能.

背景情况:

  • 目前的面包盗窃检测方法复杂且效率低下.
  • 准确地描述面包的粘弹性特性对于监测面包的衰减至关重要.
  • 需要优化算法来处理复杂的食品模型.

研究的目的:

  • 开发一种快速高效的食品构成模型方法,用于检测面包缩.
  • 使用多目标粒子群集优化 (MOPSO) 来识别爬行测试参数.
  • 用粘弹性参数和水分含量来预测面包衰老.

主要方法:

  • 空气流激光检测技术用于非破坏性风湿学测试.
  • 多目标粒子群优化 (MOPSO) 来识别一般化的凯尔文模型.
  • 极端学习机器回归 (ELM) 用于预测水分含量和衰减.

主要成果:

  • 与FEA和NLR相比,MOPSO表现出优越的全球搜索能力,避免了局部优化.
  • 相关系数 (R) 达到0.847,湿度含量预测的根平均平方误差 (RMSE) 为0.021.
  • 空气流激光检测与MOPSO相结合,有效地确定了面包的粘弹性参数,用于停滞监测.

结论:

  • 拟议的基于MOPSO的方法提供了一种方便和有效的方法来检测面包缩.
  • 该技术适用于在工业环境中分析复杂食品的高维粘弹性模型.
  • 该研究为识别粘弹性参数和监测各种食品中衰老提供了宝贵的参考资料.