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New Laplace convolution integrals involving exponential, error, and parabolic cylinder functions with applications in heat transfer and linear viscoelasticity

This paper derives new Laplace convolution integrals involving exponential, error, and parabolic cylinder functions, extends them via repeated integration and differentiation, and applies the results to solve heat transfer and linear viscoelasticity problems while yielding new integral representations for error functions.

Original authors: González Santander, Juan Luis

Published 2026-08-25
📖 5 min read🧠 Deep dive

Original authors: González Santander, Juan Luis

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Heat is a restless traveler. It flows from hot places to cold ones, smoothing out differences in temperature until everything reaches a balance. In the physical world, this movement is rarely simple. When heat moves through a solid block, it follows a predictable path, but when that block is layered with different materials, or when the heat source itself changes in complex ways, the mathematics of the flow becomes incredibly difficult. Engineers and scientists have long relied on a powerful mathematical tool called the Laplace transform to untangle these problems. Think of this tool as a translator that converts a messy, changing situation in time into a cleaner, static picture that is easier to solve. Once the solution is found in this static picture, the tool translates it back into the real world of time and temperature.

However, even with this translator, some problems remain stubborn. There are specific combinations of functions—mathematical descriptions of how things grow, decay, or spread—that appear in real-world scenarios like the cooling of a laser-heated metal or the stretching of a rubber-like material, yet no one had found a direct way to calculate the heat flow for these specific cases. The existing tables of solutions, which act like reference manuals for engineers, simply did not contain the answers for these particular mixtures. Without these answers, scientists had to rely on approximations or complex computer simulations, which are often slow and can hide the underlying physical truth.

A researcher at the University of Oviedo in Spain has now filled these gaps by deriving a new set of exact solutions for these stubborn problems. By applying a specific rule known as the convolution theorem—which essentially describes how two different processes blend together over time—the author calculated new integrals, or mathematical sums, that describe exactly how heat and stress behave in these complex situations. The work focuses on three specific types of mathematical functions that often appear together in nature: exponential functions that describe rapid growth or decay, error functions that describe how a sharp boundary smooths out over time, and parabolic cylinder functions that describe how waves or particles spread in a curved path.

The results are not just abstract numbers; they provide precise formulas for real-world scenarios. For instance, the paper shows how to calculate the temperature inside a semi-infinite solid (a material that is effectively endless in one direction) when it is heated by a surface that is losing heat to the air, or when it is struck by a laser pulse that fades away in a very specific, non-linear way. In one application, the new formulas describe the temperature of a metal rod when a sudden burst of energy is released deep inside an insulating material nearby. In another, the formulas predict how a viscoelastic material—one that behaves like both a solid and a thick liquid, such as certain plastics or biological tissues—will stretch when pulled by a force that changes strength over time.

What makes this work particularly valuable is that it does not just offer approximations; it provides exact, closed-form solutions. This means the answers are written out as complete mathematical expressions that can be evaluated directly, without needing to run a computer simulation step-by-step. The author verified these new formulas using standard mathematical software to ensure they are correct. Furthermore, the research demonstrates that these new integrals can be extended to solve even more complex problems by repeatedly applying the same mathematical operations, allowing for a wider range of physical situations to be modeled with precision.

The paper also reveals a side benefit of this work: it uncovers new ways to represent the error function and its related variations. These functions are fundamental to statistics and physics, describing everything from the spread of a gas to the probability of an event. By finding new integral representations for them, the research adds to the fundamental toolkit available to scientists. The author notes that while some of these results could be derived through other, much more difficult methods, the use of the Laplace convolution theorem makes the process direct and manageable. This suggests that there are likely many other complex physical problems waiting to be solved by applying this same systematic approach to different combinations of functions.

Ultimately, this research bridges the gap between theoretical mathematics and practical engineering. It takes problems that were previously too difficult to solve exactly and provides the precise tools needed to understand them. Whether it is designing better thermal protection for spacecraft, understanding how heat moves through the human body, or predicting how new materials will deform under stress, these new formulas offer a clearer, more accurate picture of how the physical world behaves when heat and matter interact in complex ways. The work stands as a reminder that even in a field as established as heat transfer, there are still fundamental pieces of the puzzle waiting to be found, and that the right mathematical perspective can turn a seemingly impossible calculation into a clear, solvable equation.

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