JP6940915B2 - Prediction method of crack occurrence time and early detection method of alkali-silica reaction, - Google Patents

Description

The present invention is a method for predicting the occurrence time of cracks in a hardened cementum, particularly cracks due to an alkali-silica reaction, by analyzing digital images of concrete and mortar (hereinafter referred to as "hardened cementum"). , The present invention relates to a method for detecting an alkali-silica reaction at an early stage.

In the alkali-silica reaction, the silica gel in the reactive aggregate reacts with the alkali metal ions in the concrete under high pH conditions, and the alkali silica gel generated by absorbing water absorbs water and expands, resulting in cracks in the hardened cement material. This is a phenomenon that occurs. Since the cracks caused by this alkali-silica reaction have a hexagonal shape, they can be distinguished from the cracks caused by other deterioration such as drying shrinkage by the shape of the cracks. This alkali-silica reaction is known as one of the main causes for reducing the durability of the hardened cementum.
Therefore, in order to ensure the durability of the hardened cementum, it is necessary to predict the time when cracks will occur and take measures such as reinforcement in advance.

Conventionally, in the method of measuring cracks, the strain value measured by a strain gauge attached to the concrete surface is used in accordance with JIS A 1129-1 to 3 “Method for measuring length change of mortar and concrete”. However, when this method is used for predicting the occurrence time of cracks due to the alkali-silica reaction, there are the following problems (i) to (iv).
(I) The attached strain gauge may block water that affects the alkali-silica reaction, and the strain value may not be measured accurately.
(Ii) Moisture may cause the strain gauge to peel off, making measurement impossible.
(Iii) Since the measurement with the strain gauge is limited to one point, it is difficult to measure the strain value at which the crack occurrence location can be predicted at a plurality of points.
(Iv) Since cracks due to the alkali-silica reaction are progressive, it is difficult to predict the growth of cracks by measuring strain at one point.
Therefore, in order to predict cracks due to the alkali-silica reaction that occurs in a hexagonal shape due to this progress, it is necessary to capture the time course of strain distribution on a surface of a certain area where cracks are a concern.

By the way, the method described in Patent Document 1 is a method of tracking cracks due to an alkali-silica reaction over time. Specifically, a monitoring hole having a small diameter is drilled in a concrete structure, and the wall surface of the hole is formed. Scan with the first sensor, perform the primary diagnosis of the alkali-silica reaction by image analysis, check the residual load capacity if there is a need for follow-up, and further if the residual load capacity is greater than or equal to the required load capacity. In order to confirm the progress of the alkali-silica reaction, a second sensor is installed on the wall surface of the hole to monitor the progress of cracks. However, this method requires drilling holes in the concrete structure, and the tracking work is complicated.

Japanese Unexamined Patent Publication No. 2014-189961

Therefore, an object of the present invention is to provide a method for easily predicting the crack occurrence time of a hardened cementum with high accuracy and a method for early detecting an alkali-silica reaction of a hardened cementum.

As a result of examining a prediction method that meets the above object, the present inventor calculates a prediction formula based on the time course of strain on the surface of the hardened cement material grasped by using the digital image correlation method, and the prediction formula and cracks are found. The present invention has been completed by finding that the time when cracks occur can be easily predicted with high accuracy from the maximum principal strain value generated. That is, the present invention is a method for predicting a crack occurrence time having the following configuration.

[1] At least, cracks are made using the prediction formula that includes the maximum principal strain value and time as variables, which are derived through the following steps (A) to (C), and the maximum principal strain value set in the following steps (D). A method of predicting the time of crack occurrence, which calculates and predicts the time of occurrence of cracks.
(A) Image acquisition step of acquiring a digital image of the surface to be acquired of the cemented hardened body over time (B) Strain is calculated using the digital image correlation method based on the digital image, and the maximum main strain is calculated based on the strain. Time-dependent change calculation step of maximum principal strain to calculate the time-dependent change of strain (C) Based on the time-dependent change of the maximum principal strain, a prediction formula including the maximum main strain value and time as variables is derived by fitting. Derivation step (D) Maximum main strain value setting step of presetting the maximum main strain value at the time of crack occurrence [2] The crack occurrence time according to the above [1] in which the cementitious hardened material contains a reactive aggregate. Prediction method.
[3] The method for predicting the crack occurrence time according to the above [1] or [2], wherein the crack is a crack generated by an alkali-silica reaction.
[4] Early detection of the alkali-silica reaction, which detects the alkali-silica reaction at an early stage by the appearance of the turtle-shaped strain in the image of the distribution of the maximum principal strain obtained through the following steps (a) and (b) at least. When the alkali-silica reaction is detected by the method, the time when cracks occur is calculated and predicted using the prediction formula derived through the step (C) and the maximum principal strain value set in the step (D). The method for predicting the crack occurrence time according to any one of the above [1] to [3].
(A) Image acquisition step of acquiring a digital image of the surface to be acquired of the cemented hardened body over time (b) Strain is calculated using the digital image correlation method based on the digital image, and the maximum main component is based on the strain. Maximum principal strain distribution acquisition process to obtain strain distribution

The method for predicting the crack occurrence time of the present invention can easily predict the crack occurrence time with high accuracy. Further, the method for early detection of the alkali-silica reaction of the present invention can detect the alkali-silica reaction at an early stage.

It is a figure which shows the block-shaped test body and the test body (gray part) of the plate cut out from there to the thickness 50 mm. However, the unit of the numerical value in FIG. 1 is mm. It is a photograph which shows the scanner for digital image acquisition used in an Example. It is a figure which shows the measurement range of the test piece by the digital image correlation method, and the sticking position of the contact gauge tip. However, the unit of the numerical value in FIG. 3 is mm. It is a figure which shows the distribution of the maximum main strain at the accelerated curing period of 13, 28 days, and 56 days. However, the numerical values in FIG. 4 are abbreviated as ^{× 10-6.} It is a figure which shows the time-dependent change of strain measured using the contact gauge. It is a figure which shows the basis for setting the maximum principal strain value (numerical value × ^{10-6) at the time of crack occurrence.} It is a figure which showed three places to acquire a digital image by coordinates. It is a graph which shows the time-dependent change of the maximum principal strain at the coordinates (2600, 12350) and the coordinates (6100, 4700). It is a graph which shows the time-dependent change of the maximum principal strain at the position of coordinates (3600, 7850).

As described above, the method for predicting the crack occurrence time of the present invention is a prediction formula derived through at least (A) an image acquisition step, (B) a time-dependent change calculation step of the maximum principal strain, and (C) a prediction formula derivation step. (D) This is a method of calculating and predicting the time when cracks occur by using the maximum principal strain value set in the maximum principal strain value setting step. Further, in the method for early detection of the alkali-silica reaction of the present invention, at least, the turtle-shaped strain in the image of the distribution of the maximum principal strain obtained through the (a) image acquisition step and (b) the maximum principal strain distribution acquisition step It is a method to detect the alkali-silica reaction at an early stage by its appearance.
Hereinafter, the method for predicting the crack occurrence time and the method for early detection of the alkali-silica reaction will be described in detail.

1. 1. Method for Predicting Crack Occurrence Time (A) Image Acquisition Step This step is a step of acquiring a digital image of the surface to be acquired of the cementum hardened body (test body) over time.
Here, the cementified hardened concrete is not particularly limited, and is ordinary concrete, watertight concrete, hot concrete, cold concrete, mass concrete, fluidized concrete, high fluid concrete, high strength concrete, low heat generation concrete, expanded concrete, prestressed. Examples include concrete, low shrinkage concrete, fibrous reinforced concrete, lightweight concrete, polymer concrete, and mortar.
In order to acquire a good digital image, it is preferable to polish the surface to be acquired of the cementum cured product.
In addition, before and after the cementum hardened body is deformed, a digital image of the surface to be acquired is acquired. Since the accumulated strain is released when cracks occur, the image is acquired after the cementum hardened body has hardened, at least before the cracks occur. The deformation includes expansion due to an alkali-silica reaction. Here, when the image of the hardened cementum before deformation is acquired, if moisture adheres to the image acquisition surface, the color contrast becomes small and color unevenness occurs, which correlates with the image acquired after drying. The sex may be significantly reduced. In order to avoid this decrease in correlation, before acquiring the image, compressed air or the like is sprayed onto the imaged surface of the hardened cementum before drying to remove the moisture on the imaged surface, or it is static until the imaged surface is depleted of water. Perform pretreatment such as placing and air-drying. The pretreatment is an arbitrary treatment performed when moisture is attached to the image acquisition surface.

ただし、実際は、矩形に設定した変形前のサブセットに対し、変形後のデジタル画像そのものが変形しているため、サブセットが矩形にならない場合がある。この場合、これを補正するため、サブセット内部において変位勾配が一定と仮定して、変形前後の座標(x,y)および(x^*,y^*)には下記（２）式を用いる。

以上の計算は、市販の画像解析用ソフトウエア（例えば、digital：Correlated solutions社製）を用いて行なうことができる。 (B) Time-dependent change calculation step of the maximum principal strain The step is a step of calculating the strain using the digital image correlation method based on the digital image and calculating the time-dependent change of the maximum principal strain based on the strain. The digital image is a digital image before and after the deformation of the hardened cementum, and the maximum principal strain after the deformation is calculated by using the digital image correlation method.
The digital image correlation method is a method of calculating the amount of movement on a cementum hardened body and converting it into the maximum principal strain based on the distribution of the brightness values of the digital images acquired before and after the deformation due to the strain.
Specifically, the strain is calculated through the following calculation process.
(I) Find the brightness value distribution within a subset centered on an arbitrary position in the digital image before deformation.
(Ii) Search for a subset of the digital image before deformation, which has the brightness value distribution with the highest correlation with the brightness value distribution of the digital image after deformation, and regard the center point as the position after the point of interest is displaced. , The amount displaced from the point of interest to the center point is calculated, and the displaced amount is further converted into the maximum principal strain. The correlation of the subset before and after the deformation is expressed using the correlation coefficient R of the following equation (1).

However, in reality, the subset may not be rectangular because the digital image itself after transformation is deformed with respect to the subset before transformation set to be rectangular. In this case, in order to correct this, the following equation (2) is used for ^{the coordinates (x, y) and (x *} , y ^* ) before and after the deformation, assuming that the displacement gradient is constant inside the subset.

The above calculation can be performed using commercially available image analysis software (for example, digital: manufactured by Correlated solutions).

(C) Prediction Formula Derivation Step This step is a step of deriving a prediction formula including the maximum principal strain value and time as variables by fitting based on the change with time of the maximum principal strain. The fitting can be performed using commercially available application software (for example, Microsoft Excel, manufactured by Microsoft Corporation). As an example of the prediction formula, the following formula (i) can be mentioned.
Y = ae ^bX ... (i)
However, in Eq. (1), Y represents the maximum principal strain value, X represents the time (day), and a and b represent the constants obtained by fitting.

(D) Maximum principal strain value setting process This process is a process of presetting the maximum principal strain value at the time of crack occurrence, and is based on the experience (rule of thumb) so far regarding the time when cracks occur and the strain value at that time. Set the maximum principal strain value when cracks occur. From experience, the maximum principal strain value at the time of cracking differs slightly depending on the cause of cracking, the material constituting the cementum hardened material, the surface condition of the cementum hardened material, etc., but the maximum calculated by the digital image correlation method. As shown in FIG. 6, the main strain may be set to ^{approximately 7000 × 10-6.} Further, when the occurrence of initial cracks can be confirmed in the plane of the hardened cementum, the accuracy is improved by using the maximum principal strain value at that time.
Then, the time when the crack occurs is calculated by substituting the set maximum principal strain value into the prediction formula including the maximum principal strain value and the time as variables.
As shown in Examples described later, the method for predicting the crack occurrence time of the present invention can easily predict the crack occurrence time of the cementum hardened material with high accuracy.

Further, as described in paragraph 0003, when the conventional method is used for predicting the crack occurrence time due to the alkali-silica reaction, there is the above-mentioned problem, but the crack occurrence time prediction method of the present invention can solve the above-mentioned problem. The hardened cementaceous material to be predicted by the present invention preferably contains a reactive aggregate, and the cracks to be predicted are preferably cracks generated by an alkali-silica reaction that continues to progress.

2. Early Detection Method of Alkali-Silica Reaction This method detects the alkali-silica reaction at an early stage by the appearance of hexagonal strain in the image of the distribution of the maximum principal strain obtained through the steps (a) and (b). How to do it. The step (a) is the same as the step (A), and the step (b) is described only in the difference between obtaining the distribution of the maximum principal strain and calculating the change with time of the maximum principal strain. (B) It is substantially the same as the step.
If the occurrence of the alkali-silica reaction is detected early by the method for early detection of the alkali-silica reaction of the present invention, countermeasures can be promptly implemented, and if the crack occurrence time is predicted by the method for predicting the crack occurrence time of the present invention. , Measures can be taken by the time cracks occur.
Therefore, in the present invention, another aspect of the method for predicting the crack occurrence time is the prediction formula derived through the step (C) when the alkali silica reaction is detected by the method for early detection of the alkali silica reaction. This is a method of calculating and predicting the time when cracks occur by using the maximum principal strain value set in the step (D).

Hereinafter, the present invention will be described with reference to Examples, but the present invention is not limited to these Examples.
1. 1. Formulation of materials used and concrete (test piece) Table 1 shows the materials used, and Table 2 shows the composition of concrete, fresh properties, and compressive strength. Here, the strain caused by the alkali-silica reaction was used as the measurement target.

2. Preparation of test piece According to the formulation shown in Table 2, a block-shaped test piece having a length of 400 mm, a width of 400 mm, and a thickness of 300 mm was prepared, and a plate (test piece) cut out to a thickness of 50 mm was measured. The surface was polished and used for the test. The block-shaped test piece was cured under the conditions shown in Table 3.
For reference, in order to grasp the change in the length of the entire test piece, a contact gauge is used in accordance with the contact gauge method, and as shown in FIG. 3, the lengths of the remaining three sides of the test piece excluding the driving surface. The change was also measured and the average value was calculated. The result is shown in FIG.

3. 3. Acquisition of digital image of the test piece and distribution of maximum principal strain The digital image of the test piece is based on the end of the pre-curing 2 (age 28 days), and at the time of the base length, the accelerated curing periods 13, 28 and On the 56th day, the range shown in FIG. 3 was scanned and acquired using a line sensor type digital image acquisition scanner (total field distortion measuring device) shown in FIG. In order to avoid a change in strain due to temperature and a change in brightness value due to the influence of moisture, the test piece was stored for 20 hours or more in an environment of 20 ° C. and 60% relative humidity before acquiring an image.
Next, the calculation of the distribution of the maximum principal strain is analyzed by the digital image correlation method using the acquired digital image, and the maximum principal strain on the surface of the test piece is subjected to the following calculation processes (i) and (ii). Distribution was calculated. The distribution of the maximum principal strain calculated here was (i) the brightness value distribution within the subset centered on an arbitrary position on the digital image of the test piece at the time of basal length and after accelerated curing.
(Ii) Search for a subset of the digital image of the test piece before drying, which has the brightness value distribution with the highest correlation with the brightness value distribution of the digital image of the test piece after accelerated curing, and focus on the center point. The distance (displacement amount) moved from the point of interest to the center point was calculated by regarding the position after the movement (displacement), and the moved distance was further converted into the maximum principal strain.
FIG. 4 shows the distribution of the maximum principal strain. For reference, FIG. 5 shows a change in the length of the entire test piece measured by a contact gauge. In addition, FIGS. 8 and 9 show changes over time in the maximum principal strain.
Since the hexagonal silica reaction causes hexagonal strain, as shown in the right figure of FIG. 4, even before cracks occur, the appearance of hexagonal strain in the image of the distribution of the maximum principal strain causes alkaline silica. You can know the occurrence of the reaction.

4. Prediction of crack occurrence time (1) Setting of strain at which cracks occur In the example, cracks occur when the maximum principal strain calculated by the digital image correlation method is ^{about 7000 × 10-6} or more, and about 6000 × ^10-6. Since the occurrence of cracks could not be confirmed below, the maximum principal strain value at which cracks occur was set to 7000 × ^10-6 as shown in FIG. The width of the target crack was 0.06 mm or more.
(2) Derivation of a prediction formula based on the change over time of the maximum principal strain The accelerated curing period is 13 at the measurement points of the coordinates (2600,12350), coordinates (3600,7850), and coordinates (6100,4700) shown in FIG. The maximum principal strain values for days, 28 days, and 56 days are shown in Table 4.

The relational expressions obtained by fitting using the accelerated curing period and the maximum principal strain value shown in Table 4 are the following equation (ii) at the coordinates (2600, 12350) and the following equation (iii) at the coordinates (3600, 7850). At the coordinates (6100, 4700), it is the following equation (vi). The crack did not occur at the coordinates (2600, 12350) and the coordinates (6100, 4700), but occurred at the coordinates (3600, 7850).
Y = 14.659e ^0.0937X ... (ii)
Y = 603.19e ^0.0744X ... (iii)
Y = 44.544e ^0.0805X ... (vi)
However, in the formula, Y represents the maximum main strain value and X represents the accelerated curing period (days).

(3) Prediction of crack occurrence time Then, when Y = 7000 × ^10-6 , which is the maximum principal strain value at which cracks occur, is substituted into the above equations (ii) to (vi), cracks occur at the coordinates (2600, 12350). The predicted occurrence time X is 65.8 days, the crack occurrence time X is 32.9 days at the coordinates (3600, 7850), and the crack occurrence time X is 62.8 days at the coordinates (6100, 4700).
Incidentally, the crack occurrence time at the coordinates (3600, 7850) is between 28 and 56 days from the captured digital image, which is close to the crack occurrence prediction time of 32.9 days, and thus the present invention. It can be said that the prediction method of the crack occurrence time is highly accurate.

Claims (4)

At least, cracks occur using the prediction formula that includes the maximum principal strain value and time as variables, which are derived through the following steps (A) to (C), and the maximum principal strain value set in the following steps (D). A method for predicting the time when cracks occur, which calculates and predicts the time.
(A) Image acquisition step of acquiring a digital image of the surface to be acquired of the cemented hardened body over time (B) Strain is calculated using the digital image correlation method based on the digital image, and the maximum main strain is calculated based on the strain. Time-dependent change calculation step of maximum principal strain to calculate the time-dependent change of strain (C) Based on the time-dependent change of the maximum principal strain, a prediction formula including the maximum main strain value and time as variables is derived by fitting. Derivation process (D) Maximum principal strain value setting process that presets the maximum principal strain value when cracks occur. The method for predicting the time of occurrence of cracks according to claim 1, wherein the hardened cementum contains a reactive aggregate. The method for predicting a crack occurrence time according to claim 1 or 2, wherein the crack is a crack generated by an alkali-silica reaction. At least, an alkali with the advent of tortoise-shell strain in the following step (a) and (b) the maximum step obtained through the principal strain distribution image of an early stage to detect the alkali silica reaction, the early detection methods alkali silica reaction When a silica reaction is detected, the prediction formula derived through the step (C) and the maximum principal strain value set in the step (D) are used to calculate and predict the time when cracks occur. Item 3. The method for predicting a crack occurrence time according to any one of Items 1 to 3.
(A) Image acquisition step of acquiring a digital image of the surface to be acquired of the cemented hardened body over time (b) Strain is calculated using the digital image correlation method based on the digital image, and the maximum main component is based on the strain. Maximum principal strain distribution acquisition process to obtain strain distribution

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