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Quantifying Heat02:46

Quantifying Heat

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Thermal Energy Microscopically, thermal energy is the kinetic energy associated with the random motion of atoms and molecules. Temperature is a quantitative measure of “hot” or “cold”, which depends on the amount of thermal energy. When the atoms and molecules in an object are moving or vibrating quickly, they have a higher average kinetic energy (KE) (or higher thermal energy), and the object is perceived as “hot”, or it is described as being at a higher temperature. When the...
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Specific Heat01:16

Specific Heat

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The specific heat capacity of a substance refers to the energy required to increase the temperature of one gram of that substance by one degree Celcius. Specific heat capacity is often represented in calories (cal), grams (g), and degrees Celsius (oC), but can also be expressed in joules (J), kilograms (kg), and Kelvin (K), among other units.
For example, increasing the temperature of one gram of water by 1°C requires one calorie of heat energy and can be written as 1 cal/g-°C, or...
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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Heating and Cooling Curves02:44

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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, q, and its...
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Heat Flow and Specific Heat01:12

Heat Flow and Specific Heat

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Heat is a type of energy transfer that is caused by a temperature difference, and it can change the temperature of an object. Since heat is a form of energy, its SI unit is the joule (J). Another common unit of energy often used for heat is the calorie (cal), which is defined as the energy needed to change the temperature of 1 g of water by 1 °C, specifically between 14.5 °C and 15.5 °C, since the energy needed shows a slight temperature dependence. Another commonly used unit is...
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Network Covalent Solids02:18

Network Covalent Solids

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Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
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Related Experiment Video

Updated: Jan 21, 2026

Esophageal Heat Transfer for Patient Temperature Control and Targeted Temperature Management
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Achieving Lower District Heating Network Temperatures Using Feed-Forward MPC.

Nathan Zimmerman1, Konstantinos Kyprianidis2, Carl-Fredrik Lindberg2,3

  • 1Department of Automation in Energy and Environment, School of Business, Society and Engineering, Mälardalen University, Box 883, 721 23 Västerås, Sweden. nathan.zimmerman@mdh.se.

Materials (Basel, Switzerland)
|August 7, 2019
PubMed
Summary

Implementing advanced control strategies can significantly reduce district heating network temperatures, leading to substantial energy savings. This study demonstrates how predictive control lowers supply and return temperatures, optimizing energy efficiency in heating systems.

Keywords:
DHNMPCcontroldistrict heatingdynamic modellingenergy savingsfeed-forward

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Area of Science:

  • Energy Systems Engineering
  • Control Systems Theory
  • Sustainable Energy

Background:

  • Current district heating networks often operate at higher temperatures than necessary.
  • Existing control methods rely on operator experience and outdoor temperature, limiting efficiency.
  • Future energy demands necessitate optimized and lower operating temperatures for district heating.

Purpose of the Study:

  • To evaluate the feasibility of reducing supply and return temperatures in district heating networks.
  • To implement and assess feed-forward model predictive control (MPC) for temperature optimization.
  • To determine the impact of predictive control on energy savings and network stability.

Main Methods:

  • Development of a dynamic process model for district heating networks.
  • Implementation of two feed-forward MPC scenarios using historical load and load prediction.
  • Evaluation of controller performance in maintaining lower network temperatures and managing return temperatures.

Main Results:

  • Both control scenarios demonstrated significant load reduction, between 12.5% and 13.7%.
  • Accurate prediction of end-user demand and feedback improved return temperature stability.
  • The proposed control approach enables lower supply temperatures and enhances production-side energy savings.

Conclusions:

  • Feed-forward MPC is a viable strategy for lowering district heating network temperatures.
  • Optimized control reduces energy consumption and improves the efficiency of heat production.
  • Accurate demand forecasting is crucial for sustaining lower return temperatures and maximizing energy savings.