A Process for Obtaining Material Sensitivities from a Single Computational Simulation Skip to main content

A Process for Obtaining Material Sensitivities from a Single Computational Simulation ID: 2022-022

An innovative method to derive material sensitivities using just one computational simulation, streamlining the research and development process in material science.

2022-022
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Technology Overview

This technology represents a significant leap in computational simulation methodologies, allowing for the extraction of material sensitivities from a singular computational effort. Traditionally, obtaining such data required multiple simulations under varying conditions, making this process both time-consuming and resource-intensive. The invention simplifies this by condensing the process into a single simulation, which not only saves time but also significantly reduces computational costs.


Key Advantages

  • Significant reduction in time and resources required for material sensitivity analysis
  • Elimination of the need for multiple simulations, thereby reducing computational costs
  • Enables more efficient research and development within material science
  • Supported by the US National Science Foundation, highlighting its credibility and potential impact

Problems Addressed

  • High computational costs associated with traditional material sensitivity analysis
  • Time-consuming processes required for conducting multiple simulations
  • Resource-intensive nature of traditional computational simulations in material science

Market Applications

  • Hospital and clinical settings for enhanced precision in ultrasound neuromodulation treatments
  • Integration within MRI systems for real-time adjustment of acoustic fields during treatments
  • Potential expansion to diagnostic applications, such as measuring the spatial extent of brain tumors

Additional Information

Technology ID: 2022-022
Sell Sheet: Download the Sell Sheet here
Market Analysis: Contact us for a more in-depth market report
Date Published: 28 March, 2025

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