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Transformers with Off-Nominal Turns Ratios01:25

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In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
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Three identical single-phase transformers can be configured to form a three-phase transformer connection, which involves high-voltage and low-voltage windings. The high-voltage windings are denoted by capital letters A-B-C, while the low-voltage windings are labeled with lowercase letters a-b-c, representing their respective phases. This notation helps distinguish between the high and low voltage sides of the transformer.
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A device that transforms voltages from one value to another using induction is called a transformer. A transformer consists of two separate coils, or windings, wrapped around the same soft iron core. However, they are electrically insulated from each other.
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Traverse angle computations are a critical component of surveying, used to compute the internal angles within a closed traverse. A traverse consists of a series of connected lines forming a closed loop, often used for land boundary delineation or mapping. Calculating the internal angles ensures accuracy in the traverse geometry and is essential for checking survey data integrity.The process begins with known azimuths and bearings of the traverse sides. Internal angles at each vertex are...
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Metasurface Vision Transformer: A Generic AI Model for Metasurface Inverse Design.

Jiahao Yan1, Jilong Yi1, Churong Ma1

  • 1Guangdong Provincial Key Laboratory of Nanophotonic Manipulation, Institute of Nanophotonics, College of Physics and Optoelectronic Engineering Jinan University Guangzhou China.

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Summary
This summary is machine-generated.

Metasurface inverse design is revolutionized by MetasurfaceViT, a universal AI model. It enables one-shot structure design for diverse optical applications by learning from augmented data, overcoming limitations of previous fixed-condition models.

Keywords:
Vision Transformerartificial intelligenceinverse designmetasurfaces

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Area of Science:

  • Optics and Photonics
  • Artificial Intelligence
  • Materials Science

Background:

  • Metasurfaces offer precise control over light properties (amplitude, phase, polarization) for advanced optical applications.
  • Current deep learning models for metasurface inverse design lack universality and require retraining for new parameters like wavelength or polarization.

Purpose of the Study:

  • To develop a universal, AI-driven inverse design model for metasurfaces that operates across various conditions.
  • To enable efficient, one-shot design of metasurface structures for arbitrary optical requirements.

Main Methods:

  • Introduced MetasurfaceViT, a Vision Transformer-based AI model for metasurface inverse design.
  • Utilized a large dataset of Jones matrices, augmented with physics-informed data.
  • Employed pretraining with masked wavelength and polarization channels to enable reconstruction of full-wavelength Jones matrices.

Main Results:

  • MetasurfaceViT achieved over 99% prediction accuracy for physically realistic designs.
  • Demonstrated successful one-shot design of multiplexed holograms, printings, and broadband achromatic metalenses.
  • Showcased the model's versatility for arbitrary wavelength, polarization, and application requirements.

Conclusions:

  • MetasurfaceViT represents a significant advancement towards a universal paradigm for optical inverse design.
  • The developed AI model overcomes the limitations of fixed-condition designs, paving the way for more adaptable and efficient metasurface engineering.