A method for determining the size effect of compressive strength of restructured composite structural wood

Abstract

The embodiment of the present invention discloses a method for determining the size effect of the compressive strength of reconstructed composite structural timber, which relates to the technical field of green wood building materials. The method for determining the size effect of the compressive strength of the reconstructed composite structural timber comprises: obtaining the strength distribution characteristics of a reference compressive specimen; evaluating the compressive strength of specimens of different sizes; and determining a relationship between the size effect of the compressive strength of the reconstructed composite structural timber. The method for determining the size effect of the compressive strength of the reconstructed composite structural timber of the present invention can accurately and quantitatively evaluate the influence of the size of a component on its compressive strength, and promote the transformation of the reconstructed composite structural timber from non-structural application fields such as plank roads and furniture to building structure application fields.

Description

Technical Field

[0001] The invention relates to the technical field of green wooden building materials, in particular to a method for determining the compressive strength size effect of reconstituted composite structural wood. Background Art

[0002] Recombinant composite structural timber is a new type of wood composite material formed by rolling, debonding, drying, impregnation, cold pressing and thermal curing of peeled veneer. It has good dimensional stability and mechanical strength and has broad application prospects in the field of green building materials. As a biomass material, recombinant composite structural timber naturally has various inherent defects, such as microcracks and pores. As the volume of the component increases, the possibility of defects in the component also increases, and the probability of failure under load increases, resulting in a decrease in strength with the increase in the volume of the component, that is, there is a size effect in its strength. Determining the size effect of recombinant composite structural timber is a prerequisite for determining the design indicators of components of different sizes and applying them to the field of building structures. However, there is currently a lack of a method for determining the size effect of recombinant composite structural timber, and it is impossible to calculate and evaluate the strength of recombinant composite structural timber components of different sizes, resulting in its current main application in non-structural fields such as plank roads and furniture, with low added value. Proposing a method for determining the size effect of recombinant composite structural timber is of great significance for accurately and quantitatively evaluating the strength of recombinant composite structural timber and promoting the application of recombinant composite structural timber in the field of building structures.

[0003] After searching relevant literature and materials, there is currently no method to determine the size effect of reconstructed composite structural wood. In the approximate field, the Weibull weakest chain theory is generally used to determine the size effect of wood and bamboo structural materials. This theory holds that a component can be regarded as a chain composed of links of different strengths. When the load applied to the chain exceeds the bearing capacity of the weakest link, the chain will break, that is, the strength of the component is equal to the strength of the weakest unit. According to this theory, the logarithm of the strength of wood and bamboo components of different sizes is linearly related to the logarithm of the volume. Therefore, by testing the compressive strength of specimens of different sizes, taking the logarithm of the strength and volume respectively, and then performing linear fitting, the relationship between strength and specimen size can be established to describe the size effect of wood column components.

[0004] The shortcomings of the above technologies are mainly manifested in:

[0005] (1) One of the premises for the Weibull weakest link theory is that the material strength obeys the Weibull distribution. However, actual test results show that the material strength does not necessarily conform to this distribution.

[0006] (2) Weibull's weakest chain theory is only applicable to brittle fracture modes, that is, the failure of the weakest link in the chain will lead to the failure of the chain. However, this assumption is not applicable to the compression of reconstructed composite structural timber. When under compression, after the unit with the lowest strength on the cross section reaches the ultimate strength, the unit yields under compression and can still bear the load. Therefore, the cross section will not fail immediately, and the load on the adjacent units can continue to increase. Only when the number of units in the cross section that reach the ultimate strength exceeds a certain number will the component fail. In other words, the Weibull weakest chain theory cannot consider the situation where the number of units that reach the ultimate strength inside the component accumulates to a certain extent before the component is compressed and damaged. Therefore, it is not applicable to determine the size effect of the compressive strength of reconstructed composite structural timber.

[0007] (3) It is necessary to test specimens of different sizes, and the test volume is large. Summary of the invention

[0008] In view of this, an embodiment of the present invention provides a method for determining the size effect of the compressive strength of reconstructed composite structural timber, so as to accurately and quantitatively evaluate the influence of the component size on its compressive strength, and promote the transformation of reconstructed composite structural timber from non-structural application fields such as plank roads and furniture to building structure application fields.

[0009] A method for determining the size effect of compressive strength of reconstructed composite structural wood, comprising:

[0010] Step 1: Obtain the strength distribution characteristics of the benchmark compression specimen;

[0011] Step 2: Evaluate the compressive strength of specimens of different sizes;

[0012] Step 3: Determine the size effect relationship of the compressive strength of reconstructed composite structural timber.

[0013] Furthermore, the step 1 comprises:

[0014] Step 11: Processing the reconstructed composite structural timber into no less than 40 benchmark compression test pieces;

[0015] Step 12: Determine the compressive strength characteristics of the reconstructed composite structural timber benchmark compressive specimens through mechanical property tests.

[0016] Further, the step 12 includes:

[0017] Step 121: Performing compressive strength tests on the reference compression test pieces respectively, applying a compressive load in the height direction, causing the reference compression test pieces to fail within 3-5 minutes, recording the failure load of the reference compression test pieces, and calculating the compressive strength of each reference compression test piece according to the failure load;

[0018] Step 122: Record the average compressive strength of all reference compressive test pieces as fr;

[0019] Step 123: draw a cumulative frequency distribution diagram of the compressive strength of all benchmark compressive specimens, and fit the compressive strength test results with normal distribution, lognormal distribution and Weibull distribution to obtain fitting parameters; wherein, for normal distribution, the fitting parameters are the mean and standard deviation, for lognormal distribution, the fitting parameters are the logarithmic mean and logarithmic standard deviation, and for Weibull distribution, the fitting parameters are the shape parameter and size parameter;

[0020] Step 124: Compare the single point errors and the sum of squared errors of the three distribution prediction values ​​and the measured values, and select the best fitting distribution.

[0021] Furthermore, the step 2 comprises:

[0022] Step 21: Generate virtual compression specimens of different sizes;

[0023] Step 22: Generate a number of groups of virtual compression test pieces of different sizes from small to large in volume, with n pieces in each group;

[0024] Step 23: Determine the compressive strength of each virtual compressive specimen;

[0025] Step 24: For each group of n virtual compression specimens, after determining the strength of each virtual compression specimen according to step 23, calculate the average compressive strength of the group of virtual compression specimens.

[0026] Furthermore, the step 21 includes:

[0027] Step 211: combining the reference compression test piece as a basic unit in the width direction and the height direction to form a large-sized virtual compression test piece;

[0028] Step 212: In the large-size virtual compressive specimen, the compressive strength of each basic unit is randomly selected according to the optimal fitting distribution of the compressive strength of the benchmark compressive specimen determined in step 124.

[0029] Further, the step 23 includes:

[0030] Step 231: gradually increase the compressive load applied to the virtual compression test piece from 0, evaluate the compressive stress of each basic unit in each section of the virtual compression test piece, when the weakest unit in the section reaches its ultimate strength, the stress of the weakest unit remains unchanged, while the stress of other units continues to increase; repeat this process, when the number of units that reach the ultimate strength in a certain section reaches a certain proportion, determine that the section has failed, and determine the ultimate load of the section at this time;

[0031] Step 232: comparing the ultimate loads of each section in the height direction, and the minimum value is the ultimate load of the virtual compression test piece;

[0032] Step 233: The ultimate load of the virtual compression specimen is divided by the cross-sectional area of ​​the virtual compression specimen to obtain the compressive strength of the virtual compression specimen.

[0033] Furthermore, the step 3 comprises:

[0034] Step 31: taking the natural logarithm of the average compressive strength of each group of virtual compression specimens divided by the average compressive strength of the reference compression specimens, taking the natural logarithm of the average volume of each group of virtual compression specimens divided by the volume of the reference compression specimens, and drawing a relationship diagram between the two;

[0035] Step 32: A quadratic function is used to fit the relationship between the two in step 31, so as to establish a size effect relationship of the reconstructed composite structural wood.

[0036] The method for determining the size effect of the compressive strength of reconstructed composite structural timber provided in an embodiment of the present invention first obtains the strength distribution characteristics of a reference compressive specimen; secondly, evaluates the compressive strength of specimens of different sizes; and finally determines the size effect relationship of the compressive strength of the reconstructed composite structural timber. Compared with the prior art, the method can accurately and quantitatively evaluate the influence of the component size on its compressive strength, and promote the transformation of the reconstructed composite structural timber from non-structural application fields such as plank roads and furniture to building structure application fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 It is a schematic flow chart of a method for determining the size effect of the compressive strength of reconstructed composite structural wood according to the present invention;

[0039] Figure 2 It is a schematic diagram comparing the cumulative failure frequency of the compressive strength of the reconstructed composite structural wood in the method of the present invention and the fitting curves of three different distributions;

[0040] Figure 3 Schematic diagram of the structure of the compression test piece in the method of the present invention, wherein (a) is a structural diagram of a reference compression test piece, and (b) is a structural diagram of a virtual compression test piece composed of 3×3×5 reference compression test pieces shown in (a);

[0041] Figure 4 The figure is a comparison diagram of the size effect of reconstructed composite structural wood determined according to the present invention and Weibull's weakest chain theory. DETAILED DESCRIPTION

[0042] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0043] It should be clear that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] The embodiment of the present invention provides a method for determining the size effect of the compressive strength of a reconstructed composite structural wood. Figure 1 As shown, including:

[0045] Step 1: Obtain the strength distribution characteristics of the benchmark compression specimen;

[0046] As a preferred embodiment, the step 1 includes:

[0047] Step 11: Processing the reconstructed composite structural timber into no less than 40 benchmark compression test pieces;

[0048] In specific implementation, each specimen can be in the shape of a cuboid with a size of 20 mm × 20 mm × 30 mm. The volume V of the reference compressive specimen is r is the reference volume, the average strength f of the benchmark compressive specimen r is the reference intensity.

[0049] Step 12: Determine the compressive strength characteristics of the reconstructed composite structural timber benchmark compressive specimens through mechanical property tests.

[0050] As a preferred embodiment, the step 12 includes:

[0051] Step 121: Performing compressive strength tests on the reference compression test pieces respectively, applying a compressive load along the height (30 mm) direction, causing the reference compression test pieces to fail within 3-5 minutes, recording the failure load of the reference compression test pieces, and calculating the compressive strength of each reference compression test piece according to the failure load;

[0052] Step 122: The average value of the strength of all the reference compressive specimens is recorded as f r ;

[0053] Step 123: draw a cumulative frequency distribution diagram of the compressive strength of all benchmark compressive specimens, and fit the compressive strength test results with normal distribution, lognormal distribution and Weibull distribution to obtain fitting parameters; wherein, for normal distribution, the fitting parameters are the mean and standard deviation, for lognormal distribution, the fitting parameters are the logarithmic mean and logarithmic standard deviation, and for Weibull distribution, the fitting parameters are the shape parameter and size parameter;

[0054] Step 124: Compare the single point errors and the sum of squared errors of the three distribution prediction values ​​and the measured values, and select the best fitting distribution.

[0055] Step 2: Evaluate the compressive strength of specimens of different sizes;

[0056] As a preferred embodiment, the step 2 includes:

[0057] Step 21: Generate virtual compression specimens of different sizes;

[0058] As a preferred embodiment, the step 21 includes:

[0059] Step 211: combining the reference compression test piece as a basic unit in the width direction and the height direction to form a large-sized virtual compression test piece;

[0060] Step 212: In the large-size virtual compressive specimen, the compressive strength of each basic unit is randomly selected according to the optimal fitting distribution of the compressive strength of the benchmark compressive specimen determined in step 124.

[0061] Step 22: Generate a number of groups of virtual compression test pieces of different sizes from small to large in volume, with n pieces in each group;

[0062] In this step, n is an integer. Since several groups of virtual compression specimens of different sizes are generated, and each group of specimens contains a sufficient number of specimens, random sampling errors can be eliminated.

[0063] Step 23: Determine the compressive strength of each virtual compressive specimen;

[0064] For each virtual compressive test piece, the compressive strength thereof is determined according to the following method, that is, as a preferred embodiment, the step 23 includes:

[0065] Step 231: gradually increase the compressive load applied to the virtual compression test piece from 0, evaluate the compressive stress of each basic unit in each section of the virtual compression test piece, when the weakest unit in the section reaches its ultimate strength, the stress of the weakest unit remains unchanged, while the stress of other units continues to increase; repeat this process, when the number of units that reach the ultimate strength in a certain section reaches a certain proportion, determine that the section has failed, and determine the ultimate load of the section at this time;

[0066] Step 232: comparing the ultimate loads of each section in the height direction, and the minimum value is the ultimate load of the virtual compression test piece;

[0067] Step 233: The ultimate load of the virtual compression specimen is divided by the cross-sectional area of ​​the virtual compression specimen to obtain the compressive strength of the virtual compression specimen.

[0068] Step 24: For each group of n virtual compression specimens, after determining the strength of each virtual compression specimen according to step 23, calculate the average compressive strength of the group of virtual compression specimens.

[0069] Step 3: Determine the size effect relationship of the compressive strength of reconstructed composite structural timber.

[0070] As a preferred embodiment, step 3 includes:

[0071] Step 31: taking the natural logarithm of the average compressive strength of each group of virtual compression specimens divided by the average compressive strength of the reference compression specimens, taking the natural logarithm of the average volume of each group of virtual compression specimens divided by the volume of the reference compression specimens, and drawing a relationship diagram between the two;

[0072] Step 32: A quadratic function is used to fit the relationship between the two in step 31, so as to establish a size effect relationship of the reconstructed composite structural wood.

[0073] The method for determining the size effect of the compressive strength of reconstructed composite structural timber provided by an embodiment of the present invention first obtains the strength distribution characteristics of a benchmark compressive specimen; secondly, evaluates the compressive strength of specimens of different sizes; and finally determines the size effect relationship of the compressive strength of the reconstructed composite structural timber. Compared with the prior art, the present invention only performs compressive strength tests on a number of benchmark compressive specimens of smaller sizes to obtain the compressive strength, and uses different distributions to fit the test results of the benchmark compressive specimens to obtain the optimal compressive strength distribution. There is no need to perform compressive strength tests on specimens of different sizes, and the influence of the component size on its compressive strength can be accurately and quantitatively evaluated, thereby promoting the transformation of reconstructed composite structural timber from non-structural application fields such as plank roads and furniture to building structure application fields.

[0074] The technical solution of the present invention is described in detail below with reference to specific examples.

[0075] Step 1: Obtain the strength distribution characteristics of the benchmark compression specimen

[0076] (1) The reconstructed composite structural timber was processed into 42 benchmark compressive test specimens (see Figure 3 ), each benchmark compressive test piece is in the shape of a cuboid with dimensions of 20 mm × 20 mm × 30 mm. The volume of the benchmark compressive test piece is V r =12000mm 3 is the reference volume, the average strength f of the benchmark compressive specimen r is the reference intensity.

[0077] (2) The compressive strength characteristics of the reconstructed composite structural wood benchmark compressive specimens were determined through mechanical property tests. The benchmark compressive strength tests were conducted on the benchmark compressive specimens. A compressive load was applied along the height (30 mm) direction to cause the specimens to fail within 3-5 minutes. The load at which the benchmark compressive specimen failed was recorded. Based on the load at failure, the compressive strength of each benchmark compressive specimen was calculated. The average compressive strength of all benchmark compressive specimens was calculated to be 90.30 MPa, denoted as f r , draw the cumulative frequency distribution of the compressive strength of all benchmark compressive specimens, and fit the compressive strength test results with normal distribution, lognormal distribution and Weibull distribution (see Figure 2 ), and get the fitting parameters. For normal distribution, the fitting parameters are mean and standard deviation, for lognormal distribution, the fitting parameters are log mean and log standard deviation, and for Weibull distribution, the fitting parameters are shape parameter and size parameter. Comparing the single point error and error sum of the three distribution prediction values ​​and the measured values, it can be found that the lognormal distribution has the smallest error and the best fit, see Table 1 below:

[0078] Table 1 Fitting parameters and errors of strength distribution of benchmark compressive specimens

[0079]

[0080] Step 2: Evaluate the compressive strength of specimens of different sizes

[0081] (1) Generate virtual compressive specimens of different sizes. The benchmark compressive specimens are combined as basic units in the width and height directions to form large-sized virtual compressive specimens. In the large-sized virtual compressive specimens, the compressive strength of each basic unit is randomly selected according to the log-normal distribution.

[0082] (2) Generate several groups of virtual compressive specimens of different sizes from small to large, with each group containing 1000 specimens. Table 2 below lists the specific sizes of the virtual compressive specimens. The sizes of the first group of virtual compressive specimens are the same as those of the reference compressive specimens. The volume of the twelfth group of virtual compressive specimens is 13,600 times that of the first group of virtual compressive specimens, and the size range is relatively large. Take the fourth group of specimens as an example (see Figure 3 ), its size is 60mm×60mm×150mm, each section includes 9 basic units, there are 5 layers of basic units in the height direction, and a total of 45 basic units.

[0083] Table 2 Parameters of generated specimens

[0084]

[0085] Note: nA is the number of basic units in each cross section, nh is the number of basic units along the length direction, and nt is the total number of basic units in each specimen.

[0086] (3) Determine the compressive strength of each virtual compressive specimen. For each virtual compressive specimen, determine its compressive strength according to the following method:

[0087] The compressive load applied to the virtual compressive specimen is gradually increased from 0 to evaluate the compressive stress of each basic unit in each section of the virtual compressive specimen. When the weakest unit in the section reaches its ultimate strength, the stress of the weakest unit remains unchanged, while the stress of other units continues to increase. Repeat this process. When the number of units that reach the ultimate strength in a certain section reaches 40% of the square root of the number of basic units in the section, the section is judged to be failed and the ultimate load of the section at this time is determined. Compare the ultimate loads of each section in the height direction, and the minimum value is the ultimate load of the virtual compressive specimen. The ultimate load of the virtual compressive specimen divided by the cross-sectional area of ​​the virtual compressive specimen is the compressive strength of the virtual compressive specimen.

[0088] (4) For each group of 1000 virtual compressive specimens, after determining the strength of each virtual compressive specimen according to step 23, calculate the average compressive strength of the specimens in the group.

[0089] Step 3: Determine the size effect relationship of the compressive strength of reconstructed composite structural wood

[0090] The average compressive strength of each group of virtual compressive specimens is divided by the average compressive strength of the reference compressive specimens and the natural logarithm is taken. The average volume of each group of virtual compressive specimens is divided by the volume of the reference compressive specimens and the natural logarithm is taken. The relationship between the two is plotted (see Figure 4 );according to Figure 4 It is found that as the volume of the virtual compressive specimen increases, the strength gradually decreases, but after taking the logarithm of the two, they do not satisfy a linear relationship; therefore, a quadratic function is used to fit the relationship between the two in step 31 to establish the size effect relationship of the reconstructed composite structural wood:

[0091]

[0092] According to the existing technical solution, as the volume of the virtual compressive test piece increases, the logarithm of the strength and the logarithm of the volume are linearly related. After fitting, the following relationship can be obtained:

[0093]

[0094] According to the above two formulas, it can be found that the predicted strength value of the Weibull weakest chain theory using the existing technology is too small when the component size is large.

[0095] The method for determining the size effect of the compressive strength of reconstructed composite structural wood provided by the embodiment of the present invention has the following advantages:

[0096] (1) Significantly reduce the number of tests. The traditional technical solution requires carrying out compression tests on reconstructed composite structural wood of different sizes, and then establishing the relationship between the compressive strength and the specimen size after obtaining the test results. However, the present invention only requires testing the benchmark compression specimen, which reduces the number of tests, reduces the specimen size, saves time, and is economical.

[0097] (2) The established size effect relationship is more accurate. The traditional Weibull weakest chain theory assumes that the specimen fails after the weakest unit in the specimen reaches the ultimate bearing capacity, which is inconsistent with the failure mechanism of reconstructed composite structural timber under compression. When under compression, when the weakest unit in the specimen reaches its ultimate bearing capacity, the unit yields under compression, which does not lead to the destruction of the entire specimen. The specimen will fail only when the number or proportion of units that reach the ultimate bearing capacity in a certain section reaches a certain level. With the traditional technical solution, the compressive bearing capacity of the specimen will be underestimated as the size of the specimen increases. The present invention takes into account the stress mechanism of multiple units yielding one after another, so the established size effect relationship is more accurate.

[0098] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for determining the size effect of compressive strength of reconstructed composite structural wood, characterized in that: include: Step 1: Obtain the strength distribution characteristics of the benchmark compression specimen; Step 2: Evaluate the compressive strength of specimens of different sizes; Step 3: Determine the size effect relationship of the compressive strength of the reconstructed composite structural wood; Wherein, the step 1 comprises: Step 11: Processing the reconstructed composite structural timber into no less than 40 benchmark compression test pieces; Step 12: Determine the compressive strength characteristics of the reconstructed composite structural wood benchmark compressive test piece through a mechanical property test; The step 12 comprises: Step 121: Performing compressive strength tests on the reference compression test pieces respectively, applying a compressive load in the height direction, causing the reference compression test pieces to fail within 3-5 minutes, recording the failure load of the reference compression test pieces, and calculating the compressive strength of each reference compression test piece according to the failure load; Step 122: Record the average compressive strength of all reference compressive test pieces as fr; Step 123: draw a cumulative frequency distribution diagram of the compressive strength of all benchmark compressive specimens, and fit the compressive strength test results with normal distribution, lognormal distribution and Weibull distribution to obtain fitting parameters; wherein, for normal distribution, the fitting parameters are the mean and standard deviation, for lognormal distribution, the fitting parameters are the logarithmic mean and logarithmic standard deviation, and for Weibull distribution, the fitting parameters are the shape parameter and size parameter; Step 124: Compare the single point errors and the sum of square errors of the three distribution prediction values ​​and the measured values, and select the best fitting distribution; The step 2 comprises: Step 21: Generate virtual compression specimens of different sizes; Step 22: Generate a number of groups of virtual compression test pieces of different sizes from small to large in volume, with n pieces in each group; Step 23: Determine the compressive strength of each virtual compressive specimen; Step 24: for each group of n virtual compression test pieces, after determining the strength of each virtual compression test piece according to step 23, calculate the average compressive strength of the group of virtual compression test pieces; The step 21 comprises: Step 211: combining the reference compression test piece as a basic unit in the width direction and the height direction to form a large-sized virtual compression test piece; Step 212: In the large-size virtual compression test piece, the compressive strength of each basic unit is randomly selected according to the optimal fitting distribution of the compressive strength of the benchmark compression test piece determined in step 124; The step 23 comprises: Step 231: gradually increase the compressive load applied to the virtual compression test piece from 0, evaluate the compressive stress of each basic unit in each section of the virtual compression test piece, when the weakest unit in the section reaches its ultimate strength, the stress of the weakest unit remains unchanged, while the stress of other units continues to increase; repeat this process, when the number of units that reach the ultimate strength in a certain section reaches a certain proportion, determine that the section has failed, and determine the ultimate load of the section at this time; Step 232: comparing the ultimate loads of each section in the height direction, and the minimum value is the ultimate load of the virtual compression test piece; Step 233: The ultimate load of the virtual compression specimen is divided by the cross-sectional area of ​​the virtual compression specimen to obtain the compressive strength of the virtual compression specimen.

2. The method according to claim 1, characterized in that The step 3 comprises: Step 31: taking the natural logarithm of the average compressive strength of each group of virtual compression specimens divided by the average compressive strength of the reference compression specimens, taking the natural logarithm of the average volume of each group of virtual compression specimens divided by the volume of the reference compression specimens, and drawing a relationship diagram between the two; Step 32: A quadratic function is used to fit the relationship between the two in step 31, so as to establish a size effect relationship of the reconstructed composite structural wood.

Images