Concrete Maturity Prediction Using Embedded Thermocouples
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for predicting concrete maturity are inadequate, leading to improper curing, reduced strength, and inefficiencies in production line coordination due to environmental influences and the lack of flexible, accurate temperature monitoring systems.
Innovation Solution
A method and system using real-time temperature measurements and environmental parameter sensors to predict concrete maturity, incorporating thermocouples and energy production calculations, which allows for precise temperature control and optimization of curing processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional maturity prediction methods are used, then production time can be reduced, but measurement precision and reliability of maturity prediction deteriorate due to environmental influences
Solution Approach 1:
The system continuously monitors temperature through embedded sensors and feeds this data back to the prediction algorithm, which adjusts maturity estimates in real-time based on actual temperature deviations from standard conditions. This closed-loop feedback mechanism compensates for environmental variations and improves prediction accuracy while maintaining optimized production scheduling
Solution Approach 2:
The system transforms the fixed 28-day standard curing condition into dynamic parameter adjustments by applying Arrhenius-based temperature correction factors. The maturity prediction adapts to varying temperature conditions by calculating equivalent age at reference temperature, allowing accurate predictions under different environmental conditions without extending production time
2Measurement precision
If embedded sensors with built-in electronics are used, then temperature monitoring precision improves, but device complexity and cost increase
Solution Approach 1:
The patent uses simple thermocouple sensors as intermediaries that convert temperature into electrical signals without requiring complex embedded electronics. These passive sensors are paired with external data processing systems that perform the maturity calculation algorithms, separating the sensing function from the computation function and reducing overall system complexity
Solution Approach 2:
The thermocouple sensors are self-generating devices that produce electrical signals directly from temperature differences without requiring external power sources or complex circuitry. The sensors service themselves by converting thermal energy into measurable electrical signals through the Seebeck effect, eliminating the need for batteries or power management electronics
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables accurate prediction of concrete strength and maturity, optimizing production time, avoiding errors in curing periods, and effectively utilizing production capacity by regulating temperature within safe limits.
Implementation Method 1
temperature measurements are carried out by using one or more temperature sensors comprising one or more thermocouples embedded into the concrete
Implementation Method 2
Setting of cement is an exothermic process and the temperature is a key parameter that has significant impact on the process
Data Source
Figure 1A~1C
Figure 2A~2B
Figure 3A~3B
AI summary
A method for predicting the maturity of a concrete (36) during the curing process is disclosed. The method comprises the fol lowing steps: - pred icting at least one future temperature ( Θ n +1) with in the concrete (36); - performing at least one temperature measurement (Bl, B2, B3, B4, B5), preferably a real-time temperature measurement of the concrete (36); - transmitting the at least one temperature measurement (B1, B2, B3, B4, B5) wirelessly from at least one temperature sensor (26, 26') to an external device, such as a server (44); and - determining the energy production (ΔΟ n) within the concrete (36).