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Related Concept Videos

Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

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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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Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

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The practical equivalent circuits of single-phase two-winding transformers exhibit significant deviations from their idealized versions due to the inherent properties of winding resistance and finite core permeability. These properties result in real and reactive power losses, affecting the transformer's performance. Understanding these deviations is crucial for designing more efficient transformers.
In a practical transformer, each winding exhibits resistance and leakage reactance. The...
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Energy Losses in Transformers01:21

Energy Losses in Transformers

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In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
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Transformers01:26

Transformers

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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.
The iron core has a substantial relative permeability. Therefore, the magnetic field lines generated due to the current in one winding are almost entirely confined within the core, such that the same magnetic flux permeates each turn of both...
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Radiation: Applications01:17

Radiation: Applications

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The average temperature of Earth is the subject of much current discussion. Earth is in radiative contact with both the Sun and dark space; it receives almost all its energy from the radiation of the Sun and reflects some of it into outer space. Dark space is very cold, about 3 K, so Earth radiates energy into it. For instance, heat transfer occurs from soil and grasses, the rate of which can be so rapid that frost can occur on clear summer evenings, even in warm latitudes.
The average...
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Three-Winding Transformers01:19

Three-Winding Transformers

865
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.
In the per-unit equivalent circuit of a grounded Y-Y three-phase...
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Updated: Mar 15, 2026

A Basic Positron Emission Tomography System Constructed to Locate a Radioactive Source in a Bi-dimensional Space
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MTL_TX: A Multi-Task Transformer Model for Improved Radiation Time-Series Estimation.

Hongfang Zhang1, Adam Stavola1,2, Hal Ferguson1

  • 1Department of Electrical & Computer Engineering, Old Dominion University, Norfolk, VA 23529, USA.

Sensors (Basel, Switzerland)
|March 14, 2026
PubMed
Summary
This summary is machine-generated.

A new Multi-task Transformer (MTL_TX) model accurately estimates radiation doses at accelerator facilities. This advanced AI enhances safety for personnel and the public by predicting radiation levels using historical data.

Keywords:
Transformermulti-task learningradiation dose estimation

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Area of Science:

  • Nuclear Engineering
  • Artificial Intelligence
  • Radiation Safety

Background:

  • Controlling radiation doses is crucial for safety at facilities like the Thomas Jefferson National Accelerator Facility (JLab).
  • JLab utilizes multiple sensors to monitor beam current, energy, leakage, and radiation during operations.

Purpose of the Study:

  • To develop an accurate radiation dose estimation model for accelerator facilities.
  • To enhance safety for personnel and the public by predicting radiation levels.

Main Methods:

  • Developed a Multi-task Transformer (MTL_TX) model incorporating hierarchical feature embedding (HFE) and multi-level decomposition attention (MDA).
  • Utilized a multi-task learning (MTL) framework to leverage correlations among multiple sensors for individual estimations.

Main Results:

  • MTL_TX achieved an MSE of 0.1464, RMSE of 0.2353, and R2 of 0.8584 on 2018 data.
  • Demonstrated strong generalization with MSE of 0.1407, RMSE of 0.2263, and R2 of 0.8831 on unseen data from 2016-2019.

Conclusions:

  • The MTL_TX model significantly improves radiation dose estimation accuracy compared to state-of-the-art methods.
  • The developed model offers enhanced safety solutions for accelerator facilities and surrounding areas.