dimensionless parameter

简明释义

无因次参数

英英释义

例句

1.The Froude number is another important dimensionless parameter 无量纲参数 used to compare inertial and gravitational forces in fluid flow.

弗劳德数是另一个重要的无量纲参数，用于比较流体流动中的惯性力和重力。

2.In heat transfer analysis, the Nusselt number serves as a dimensionless parameter 无量纲参数 that relates convective to conductive heat transfer.

在热传递分析中，努塞尔数作为一个无量纲参数，将对流与导热传递联系起来。

3.When analyzing chemical reactions, the Damköhler number acts as a dimensionless parameter 无量纲参数 that compares reaction rates to transport rates.

在分析化学反应时，达姆科勒数作为一个无量纲参数，比较反应速率与传输速率。

4.The Reynolds number is a crucial dimensionless parameter 无量纲参数 used in fluid mechanics to predict flow patterns in different fluid flow situations.

雷诺数是流体力学中一个重要的无量纲参数，用于预测不同流动情况下的流动模式。

5.In engineering, the Strouhal number is a dimensionless parameter 无量纲参数 that describes oscillating flow mechanisms.

在工程中，斯特劳哈尔数是一个描述振荡流动机制的无量纲参数。

作文

In the field of science and engineering, the concept of a dimensionless parameter plays a crucial role in simplifying complex equations and enhancing our understanding of various physical phenomena. A dimensionless parameter is a quantity that has no units; it is a pure number obtained by normalizing the variables involved in a problem. This normalization process allows scientists and engineers to compare different systems without being affected by the specific units used in measurements. For instance, in fluid dynamics, the Reynolds number is a famous dimensionless parameter that helps predict flow patterns in different fluid flow situations, whether they be laminar or turbulent.The significance of dimensionless parameters can be seen in their ability to reduce the number of variables in a mathematical model. By using dimensionless parameters, researchers can condense the information contained in a system into fewer numbers, making it easier to analyze and interpret results. For example, in heat transfer problems, the Nusselt number serves as a dimensionless parameter that relates the convective heat transfer to conductive heat transfer. This allows engineers to design more efficient heat exchangers without needing to know the exact dimensions or properties of the fluids involved.Moreover, dimensionless parameters facilitate the scaling of experiments. When conducting experiments, especially in fluid mechanics, it is often impractical to replicate real-world conditions in a laboratory setting. By utilizing dimensionless parameters, researchers can ensure that the results obtained from small-scale models can be accurately extrapolated to larger systems. This principle is known as dynamic similarity, where the dimensionless parameters of the model and the prototype must match for the results to be valid.In addition, dimensionless parameters are essential in the realm of non-dimensional analysis. This analytical technique involves transforming variables into dimensionless parameters to simplify the governing equations of a system. The Buckingham π theorem is a popular method used in this analysis, which states that if there are n variables in a problem and k fundamental dimensions, then the variables can be expressed in terms of (n-k) dimensionless parameters. This theorem is widely used in engineering fields to derive relationships between different physical quantities.Furthermore, the use of dimensionless parameters extends beyond just fluid dynamics and heat transfer. In chemical engineering, reaction rates can also be expressed in terms of dimensionless parameters to understand the influence of various factors on reaction kinetics. Similarly, in structural engineering, the use of dimensionless parameters can help assess the stability of structures by relating different forces acting on them without the need for specific units.In conclusion, dimensionless parameters are invaluable tools in the fields of science and engineering. They allow for the simplification of complex systems, enhance the comparability of different scenarios, and facilitate the scaling of experimental results. By utilizing dimensionless parameters, researchers and engineers can gain deeper insights into the behavior of various physical phenomena, leading to more efficient designs and solutions. Understanding and mastering the concept of dimensionless parameters is essential for anyone looking to make significant contributions in these fields.

在科学和工程领域，无量纲参数的概念在简化复杂方程和增强我们对各种物理现象的理解方面发挥着至关重要的作用。无量纲参数是一个没有单位的量；它是通过规范化问题中涉及的变量而获得的纯数字。这种规范化过程使科学家和工程师能够在不受测量单位影响的情况下比较不同的系统。例如，在流体动力学中，雷诺数是一个著名的无量纲参数，它帮助预测不同流体流动情况下的流动模式，无论是层流还是湍流。无量纲参数的重要性体现在它们能够减少数学模型中的变量数量。通过使用无量纲参数，研究人员可以将一个系统中包含的信息浓缩为更少的数字，从而更容易分析和解释结果。例如，在热传递问题中，努塞尔数作为一个无量纲参数，将对流热传递与导热传递联系起来。这使得工程师能够在不需要知道所涉及流体的确切尺寸或特性的情况下设计更高效的热交换器。此外，无量纲参数促进了实验的缩放。当进行实验时，尤其是在流体力学中，通常在实验室环境中复制现实世界条件是不切实际的。通过利用无量纲参数，研究人员可以确保从小规模模型获得的结果可以准确地外推到更大的系统。这个原理被称为动态相似性，即模型和原型的无量纲参数必须匹配，以确保结果的有效性。此外，无量纲参数在无量纲分析领域也是必不可少的。这种分析技术涉及将变量转换为无量纲参数以简化系统的控制方程。巴克ingham π定理是一种广泛应用于此分析的方法，它指出，如果问题中有n个变量和k个基本维度，则这些变量可以用(n-k)个无量纲参数表示。该定理在工程领域广泛用于推导不同物理量之间的关系。此外，无量纲参数的使用不仅限于流体动力学和热传递。在化学工程中，反应速率也可以用无量纲参数来表示，以理解各种因素对反应动力学的影响。同样，在结构工程中，使用无量纲参数可以帮助评估结构的稳定性，通过将作用于它们的不同力联系起来，而无需具体单位。总之，无量纲参数是科学和工程领域中不可或缺的工具。它们使复杂系统的简化成为可能，增强了不同场景的可比性，并促进了实验结果的缩放。通过利用无量纲参数，研究人员和工程师能够更深入地洞察各种物理现象的行为，从而导致更高效的设计和解决方案。理解和掌握无量纲参数的概念对于任何希望在这些领域做出重大贡献的人来说都是至关重要的。