Embedded Sensors for Internal Relative Humidity of Concrete

1. Embedded Sensors for Internal Relative Humidity of Concrete D. A. Lange, Z.C. Grasley, R. Rodden American Concrete Institute October 24, 2004 San Francisco, CA

2. of 32 2 Overview Motivation Development of internal RH measurement system Correlation of RH to drying stresses Applications

3. of 32 3 Motivation Virtually all concrete durability issues dependent on state or movement of internal moisture Difficult and expensive to effectively monitor and characterize internal moisture Many potential applications in lab or field for a robust, inexpensive system

4. of 32 4 Development part 1: Advantages Commercially available Well-accepted Relatively high accuracy Digital readout Disadvantages Relatively expensive for high volume applications Not designed for embedment Size of measurement cavity

5. of 32 5 Development part 2: Advantages Relatively small size Commercially available Possibility of embedment Inexpensive Disadvantages Calibration very difficult Leadwire capacitance effect Analog signal requires circuitry for each sensor

6. of 32 6 Embedding the sensor Unique packaging concept PVC tube with Gore-Tex cap GoreTex allows vapor transmission but blocks liquid water and damaging ions

7. of 32 7 Leadwire length issue Some sensors successful, others not Device measures capacitance Capacitance of lead wires ? sensor sensitive to changes in LW length

8. of 32 8 Development part 3: Advantages Even smaller size Commercially available Possibility of embedment using GoreTex cap and plastic tube Inexpensive Digital (avoids capacitance issue) Also measures temp Disadvantages New (not widely used) No simple, inexpensive datalogging equipment developed yet Some specs: ±1.8% RH absolute accuracy 10-90% RH and 0.4° C absolute accuracy

9. of 32 9 Datalogging in the lab

10. of 32 10 Repeatability and accuracy

11. of 32 11 Development part 4: Challenges Storage of long-term measurements requires large, stable memory storage Maintaining ease of use as in the lab system Keeping cost down Ability to switch easily between lab and field without hardware adjustments Isolation of individual sensors

12. of 32 12 Field-ready system BX-24 Microprocessor: BX-24 is a relatively cheap programmable microcomputer with 16 general I/O, an onboard voltage regulator, and 32KB electronically erasable/programmable memory (EEPROM). Data can be uploaded from the BX24 through a standard RS232 (Serial) Port using the provided BasicX Environment. An onboard LED will flash green when in recording mode and red when each sensor is read. Rabbit SF1004: Rabbit SF1004 is a 4MB EEPROM. Data from the sensors is stored in the BX24 onboard EEPROM until 512 bytes have been collected. This data is then sent to the SF1004 for storage in its nonvolatile (i.e. memory not lost if power lost) memory. MU-1: This battery, made by MK Batteries, provides the BX24 with 12V which is then stepped down to 5.0V by the onboard voltage regulator. The battery supplies 35aH of power which will power the setup for an estimated 60 days (2 months). When deployed into the field, the batter will be hardwired to a solar panel which will keep the battery fully charged and the system should run indefinitely. SHT75: The Sensirion SHT75 sensors are humidity and temperature sensors which are embedded into the concrete at casting. Since the sensors are digital, there is no calibration needed and no worries with lead wire capacitance. BX-24 Microprocessor: BX-24 is a relatively cheap programmable microcomputer with 16 general I/O, an onboard voltage regulator, and 32KB electronically erasable/programmable memory (EEPROM). Data can be uploaded from the BX24 through a standard RS232 (Serial) Port using the provided BasicX Environment. An onboard LED will flash green when in recording mode and red when each sensor is read. Rabbit SF1004: Rabbit SF1004 is a 4MB EEPROM. Data from the sensors is stored in the BX24 onboard EEPROM until 512 bytes have been collected. This data is then sent to the SF1004 for storage in its nonvolatile (i.e. memory not lost if power lost) memory. MU-1: This battery, made by MK Batteries, provides the BX24 with 12V which is then stepped down to 5.0V by the onboard voltage regulator. The battery supplies 35aH of power which will power the setup for an estimated 60 days (2 months). When deployed into the field, the batter will be hardwired to a solar panel which will keep the battery fully charged and the system should run indefinitely. SHT75: The Sensirion SHT75 sensors are humidity and temperature sensors which are embedded into the concrete at casting. Since the sensors are digital, there is no calibration needed and no worries with lead wire capacitance.

13. of 32 13 Field-ready system

14. of 32 14 RH-stress relationship Kelvin-Laplace equation allows us to relate RH directly to capillary stress development Drying shrinkage Thermal expansion

15. of 32 15 Modeling drying stress gradient

16. of 32 16 Shrinkage strain components S is saturation factor, sigma is pore fluid pressure, k is bulk modulus of porous material, k0 is bulk modulus of solid hydration products.S is saturation factor, sigma is pore fluid pressure, k is bulk modulus of porous material, k0 is bulk modulus of solid hydration products.

17. of 32 17 Free shrinkage stress gradients

18. of 32 18 Free shrinkage stress gradients

19. of 32 19 Free shrinkage stress gradients

20. of 32 20 Fracture under full restraint related to gradient severity

21. of 32 21 Larger differential stress?earlier cracking

22. Potential Applications and Research Topics Drying shrinkage stress gradient modeling Size effect of drying shrinkage Curing effectiveness Diffusion rates Curling of pavements Autogenous shrinkage Temperature-RH relationship Structural monitoring

23. of 32 23 Size effect of drying shrinkage Severity of predicted drying stress gradient (using internal RH) may be used to model the drying shrinkage “size effect”

24. of 32 24 Autogenous shrinkage Mechanism for autogenous shrinkage same as external drying shrinkage Self-desiccation consumes capillary pore water Researchers have modeled autogenous shrinkage using internal RH P. Lura, Y.E. Guang, K. van Bruegel, Effect of Cement Type on Autogenous Deformation of Cement-Based Materials, ACI SP-220 (2004), 57-68.

25. of 32 25 Curing effectiveness Weight loss measurements are useful for characterizing various curing methods

26. of 32 26 On a real structure… Weight loss not always practical or possible RH can quantify effectiveness of various curing methods

27. of 32 27 Diffusion rates Diffusion is driven by concentration gradient RH is ratio of partial vapor pressure to “saturated vapor pressure” Vapor pressure is measure of concentration of water molecules in the air Measure of RH gradient is measure of gradient driving diffusion process

28. of 32 28 Pavement curling Restrained shrinkage gradient ? cracking Lack of restraint ? curling, which may ultimately lead to cracking under wheel load Models based on internal RH can predict curling

29. of 32 29 Temperature-RH relationship:

30. of 32 30 Thermal dilation maximum at intermediate internal RH

31. of 32 31 Structural monitoring “Smart Structures” becoming an increasingly popular means to monitor the health of real infrastructure Continuous hands-free measurement of RH may be useful for monitoring or predicting: Corrosion potential Moisture transfer with environment Salt infiltration Curing Saw-cut timing And modeling stress development due to drying (internal and external) and temperature change

32. of 32 32 Summary A new internal RH measurement system has been developed at UIUC: robust, inexpensive Download SW/HW docs https://netfiles.uiuc.edu/dlange/www/RHSystem.html Our current focus Modeling shrinkage and shrinkage stresses as function of RH/time Early-age stress development for saw-cut timing Many other applications in the field or lab