Seawater uniaxial compression strength prediction method based on air temperature

Abstract

The invention belongs to the technical field of ice area environment science, and particularly relates to a seawater uniaxial compression strength prediction method based on air temperature, which comprises the following steps of: A1, starting to monitor ice temperature fit of each layer according to real-time air temperature data qt at the initial freezing stage of sea ice, and establishing a relationship between the air temperature and a sea ice temperature profile; a2, measuring a sea ice salinity profile Sit, and establishing a parameterized relationship between the sea ice temperature fit and the sea ice salinity Sit based on observation data; a3, calculating the porosity kit of each layer of sea ice, and then calculating the change rule of the porosity of each layer along with the temperature of the sea ice according to the porosity; a4, screening a sample of which the fracture mode is that ductility expansion is a main crack and is split, and establishing a relationship between the porosity kit and the sea ice uniaxial compression strength sigmait; through cooperation of the method, a uniaxial compression strength relation model based on air temperature is deduced, and a new technical means is provided for evaluation of mechanical properties of sea ice and disaster prevention and reduction of sea-related engineering in an ice area.

Description

Technical Field

[0001] The invention belongs to the field of ice zone environmental science and technology, and specifically is a method for predicting the uniaxial compression strength of seawater based on air temperature. Background Art

[0002] The temperature-based sea ice uniaxial compression strength prediction method is a method that uses temperature as the main variable to estimate or predict the uniaxial compression strength of sea ice. The compression strength of sea ice is its ability to resist compression deformation when subjected to external forces. It is crucial to the physical properties, stability assessment and related engineering of sea ice. Temperature plays a key role in the physical properties of sea ice, so the prediction method based on temperature has a wide range of applications.

[0003] Currently, the measurement of the mechanical properties of sea ice mainly relies on temperature-controlled pressure tests in the laboratory. This method collects sea ice samples and brings them back to the laboratory for temperature-controlled treatment, and then conducts pressure tests at specific temperatures to obtain the mechanical strength of the sea ice.

[0004] However, this method has significant flaws, because after the sea ice is separated from its natural environment, the interaction process between its internal temperature and salinity and the dynamic changes in its microstructure cannot be accurately reproduced, resulting in the inability to effectively establish the relationship between ice temperature and mechanical strength, and thus the inability to accurately predict the actual strength of the sea ice. This situation makes it impossible to establish a direct connection between sea ice temperature and sea ice salinity, resulting in the fact that although these two important factors have been included in the parameterization scheme of the mechanical properties of sea ice, it is still difficult to establish a clear relationship between air temperature, ice temperature and mechanical strength, which has become another major problem that hinders our further understanding.

[0005] To this end, the present invention provides a method for predicting the uniaxial compression strength of seawater based on air temperature. Summary of the invention

[0006] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0007] The technical solution adopted by the present invention to solve the technical problem is: a method for predicting the uniaxial compression strength of seawater based on air temperature according to the present invention comprises the following steps:

[0008] A1. At the beginning of sea ice freezing, real-time temperature data begins t Monitor the temperature of each layer of ice it , establish the relationship between air temperature and sea ice temperature profile;

[0009] A2. Measuring sea ice salinity profile Si t , and establish the sea ice temperature f based on observational data it and sea ice salinity Si tThe parameterized relationship of

[0010] A3. Calculate the porosity k of each layer of sea ice it , and then calculate the variation of porosity of each layer with sea ice temperature based on the porosity;

[0011] A4. Screen samples with fracture modes of ductile extension as main crack and splitting, and establish the porosity k it and the uniaxial compressive strength of sea ice σ it relationship;

[0012] A5. Establish a uniaxial compression strength relationship model based on temperature, and combine it with the real-time temperature observation data of nearby areas to predict the real-time uniaxial compression strength of sea ice;

[0013] Wherein, i=1, 2, 3, ..., n, i is the number of ice layers from top to bottom, and t is the corresponding collection time.

[0014] Preferably, in step A1, establishing the relationship between air temperature and sea ice temperature profile includes the following steps:

[0015] B1. Calculate the ratio of ice temperature data of each layer to air temperature data;

[0016] B2. Define the temperature of the sea ice layer in the next day based on the ratio of the ice temperature data of each layer to the air temperature data;

[0017] B3. By measuring the total thickness of sea ice and the thickness of each layer of sea ice, the standard thickness of each layer of sea ice can be calculated;

[0018] B4. Establish a coordinate system and substitute the temperature parameters at the same time and the standard thickness parameters of each layer of sea ice.

[0019] The ratio of ice temperature data of each layer to air temperature data,

[0020] Set the sliding window size and calculate the sliding average size ba based on the window period it , where the temperature of this layer of sea ice in the next day is ba it q t ;

[0021] The total thickness of sea ice is h t , the thickness of each layer of sea ice is h it The standard thickness of this layer of sea ice is

[0022] Preferably, the sliding average value ba it The calculation method is:

[0023]

[0024] The temperature of the i-th layer of sea ice in the next day is Ti The calculation method is:

[0025] Get the temperature of the next day through the weather forecast system, denoted as q f ;

[0026] T i =ba it ×q f .

[0027] Preferably, in step A2, establishing the relationship between sea ice temperature and sea ice salinity comprises the following steps:

[0028] C1. During the sea ice temperature observation period, collect sea ice samples from each layer and melt the collected samples;

[0029] C2. Calculate the sea ice salinity of each layer of sea ice and form a sea ice salinity profile;

[0030] C3. Establish ice temperature data for each layer it and sea ice salinity profile Si t model, and derived parameterized formulas for sea ice salinity profile and sea ice temperature.

[0031] Preferably, in step A4, the method for screening the sample with the fracture mode of ductile extension as main crack and splitting comprises the following steps:

[0032] D1. Obtain sea ice samples and record the initial crack length a on the sea ice surface of the sample;

[0033] D2. Set the acquisition time and simultaneously record the length of cracks on the sea ice surface;

[0034] D3. Record the expansion rate v of the sea ice cracks within each acquisition time period △t.

[0035] Preferably, the sea ice crack expansion rate v is calculated as follows:

[0036] Where △t=t n -t n-1 , △a=a n -a n-1 .

[0037] Preferably, the porosity and sea ice temperature data are fitted as follows:

[0038] Let the function equation be, k i (t) = [f i (t)] = af i (t)+b, where a and b are unknown coefficients;

[0039] Among them, n data observation points (f i1, p i1 ), (f i2 , p i2 ),…(f in , p in );

[0040] The error sum of squares S is:

[0041]

[0042] Based on the sum of squared errors, a and b are derived to form a function of the variation of porosity with sea ice temperature.

[0043] Preferably, the linear equations of a and b are derived based on the sum of squared errors:

[0044] Let S = S min When , the corresponding a and b;

[0045] Find the partial derivative with respect to a:

[0046]

[0047] Expand the partial derivative equation of a block:

[0048]

[0049] Find the partial derivative with respect to b:

[0050]

[0051] Expand the partial derivative equation of b:

[0052]

[0053] Then, the linear equations about a and b are:

[0054]

[0055] Preferably, the undetermined coefficients a and b are solved according to the linear equation system of a and b;

[0056] Solve for b,

[0057] Substitute b into the equation and solve for a:

[0058]

[0059] Preferably, in step A4, the porosity k is established it and the uniaxial compressive strength of sea ice σ it The relationship consists of the following steps:

[0060] E1. Collect ice samples directly on site and perform uniaxial compression strength measurements at different sea ice temperatures. The strain rate is 10 -3 ;

[0061] E2, only keep the samples with the fracture mode of ductile extension to main crack and splitting, and eliminate the samples with ductile or brittle fracture;

[0062] E3. Based on the screened sample library, establish the uniaxial compression strength of sea ice σ it The relationship between the change of sea ice temperature, namely σ it =qi(k it ).

[0063] The beneficial effects of the present invention are as follows:

[0064] 1. The present invention establishes the relationship between air temperature and sea ice temperature profile, sea ice temperature and sea ice salinity, sea ice temperature and sea ice porosity, and porosity and sea ice uniaxial compression strength, and finally derives the uniaxial compression strength relationship model based on air temperature. This method has the advantages of high accuracy, high evaluation efficiency, and strong real-time performance, and provides a new technical means for the evaluation of sea ice mechanical properties and disaster prevention and mitigation of marine engineering projects in ice areas;

[0065] 2. The present invention uses on-site ice samples to directly measure pressure, which can more accurately reflect the actual mechanical properties of sea ice, thereby establishing a more accurate relationship between porosity and uniaxial compression strength of sea ice. By proposing a single-factor parameterized formula based on sea ice temperature, the evaluation process of sea ice porosity is simplified, and the original two-factor evaluation is optimized to a single-factor evaluation. The present invention proposes a parameterized formula for sea ice salinity as a function of sea ice temperature, providing a new perspective and method for the study of sea ice salinity. By directly evaluating the sea ice temperature profile through air temperature and then predicting sea ice strength, it provides strong technical support for real-time evaluation of sea ice mechanical properties and disaster prevention and mitigation of marine engineering projects in ice areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The present invention will be further described below in conjunction with the accompanying drawings.

[0067] Figure 1 It is a framework diagram of the present invention as a whole;

[0068] Figure 2 is a flow chart of the method for predicting the uniaxial compression strength of seawater in the present invention;

[0069] Figure 3 is a flow chart for establishing the relationship between air temperature and sea ice temperature profile in the present invention;

[0070] Figure 4 is a flow chart for establishing the relationship between sea ice temperature and sea ice salinity in the present invention;

[0071] Figure 5is a flow chart of screening samples with fracture modes of ductile extension as main crack and splitting in the present invention;

[0072] Figure 6 It is a flow chart for establishing the relationship between porosity and uniaxial compression strength of sea ice in the present invention. DETAILED DESCRIPTION

[0073] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0074] like Figures 1 to 6 As shown, the method for predicting the uniaxial compressive strength of seawater based on air temperature of the present invention comprises the following steps:

[0075] A1. At the beginning of sea ice freezing, real-time temperature data begins t Monitor the temperature of each layer of ice it , establish the relationship between air temperature and sea ice temperature profile; where i = 1, 2, 3…, n, i is the number of ice layers from top to bottom, and t is the corresponding collection time.

[0076] Among them, the temperature of each layer of ice is the basis for subsequent data calculation and processing. The sea ice temperature is directly measured on-site in the detection area. The on-site measurement can obtain relevant data on sea ice in real time, thus avoiding the delays that may be caused by transporting samples back to the laboratory.

[0077] Through field measurements, data is obtained directly in a real natural environment, which helps to more accurately reflect the actual behavior of sea ice under specific environmental conditions. When sea ice samples are brought back to the laboratory for analysis, sample loss or contamination may occur due to storage, transportation and other factors. In particular, during the sampling process, the structure of the ice sample may change due to temperature fluctuations or improper handling. Field measurements avoid such problems and ensure the accuracy and reliability of the data. In addition, field measurements omit a series of tedious steps such as sample collection, transportation, storage, and processing, saving time and human resources, thereby improving the efficiency of large-scale ice and snow measurements.

[0078] In step A1, establishing the relationship between air temperature and sea ice temperature profile includes the following steps:

[0079] B1. Calculate the ratio of each layer's ice temperature data to the air temperature data.

[0080] B2. Define the temperature of the sea ice layer in the next day based on the ratio of the ice temperature data to the air temperature data of each layer, set the sliding window size, and obtain the sliding average size ba based on the window period it , where the temperature of this layer of sea ice in the next day is ba it qt .

[0081] In this embodiment, the sliding window size in the sliding average is 24 hours, which is used to eliminate the instantaneous impact of solar shortwave radiation on ice temperature. It should be noted that the size of the sliding window can be determined according to the length of daylight at the measurement site, and adjusted according to the length of daylight to improve the accuracy of data calculation (during polar day and polar night, the sliding window value needs to be extended to reduce invalid result data)

[0082] B3. By measuring the total thickness of sea ice and the thickness of each layer of sea ice, the standard thickness of each layer of sea ice is calculated. The total thickness of sea ice is h t , the thickness of each layer of sea ice is h it The standard thickness of this layer of sea ice is

[0083] During the growth of sea ice, different layers may grow at different rates. By calculating the standard thickness, we can more intuitively observe the relative contribution of each layer in the growth of sea ice. When a new ice layer forms on the surface of the sea ice, the standard thickness of the surface layer will increase, while the standard thickness of other layers may decrease accordingly or remain relatively stable, so as to understand whether the sea ice growth is mainly on the surface or whether each layer has uniform growth.

[0084] B4. Establish a coordinate system and substitute the temperature parameters and standard thickness parameters of each layer of sea ice at the same time to simulate the impact of future climate change on sea ice and predict the changing trend of sea ice. For the evaluation of sea ice temperature profiles at other locations in the sea area, the temperature of each layer of sea ice can be obtained by measuring the local temperature and sea ice thickness and based on this relationship model.

[0085] A2. Measuring sea ice salinity profile Si t , and establish the sea ice temperature f based on observational data it and sea ice salinity Si t The parameterized relationship of

[0086] Wherein, in step A2, establishing the relationship between sea ice temperature and sea ice salinity includes the following steps:

[0087] C1. During the sea ice temperature observation period, collect sea ice samples from each layer and melt the collected samples;

[0088] C2. Calculate the sea ice salinity of each layer of sea ice and form a sea ice salinity profile. By measuring the conductivity of the sea ice after it melts, measure the sea ice salinity based on the conductivity.

[0089] C3. Establish ice temperature data for each layer it and sea ice salinity profile Si t The model was used to derive the parameterization formulas of sea ice salinity profile and sea ice temperature.

[0090] A3. Calculate the porosity k of each layer of sea ice it , and then calculate the variation of porosity of each layer with sea ice temperature based on the porosity.

[0091] The porosity and sea ice temperature data are fitted as:

[0092] Let the function equation be, k i (t) = [f i (t)] = af i (t)+b, where a and b are unknown coefficients;

[0093] Among them, n data observation points (f i1 , p i1 ), (f i2 , p i2 ),…(f in , p in );

[0094] The error sum of squares S is:

[0095]

[0096] Based on the sum of squared errors, a and b are derived to form a function of the variation of porosity with sea ice temperature. The function fitted by sample data within a known temperature range can predict the porosity at an unknown temperature. At the same time, it can effectively reduce the impact of abnormal fluctuations or errors of a single data point on the overall trend, thereby improving the accuracy of the linear function.

[0097] The linear equations of a and b are derived from the sum of squared errors:

[0098] Let S = S min When , the corresponding a and b;

[0099] Find the partial derivative with respect to a:

[0100]

[0101] Expand the partial derivative equation of a block:

[0102]

[0103] Find the partial derivative with respect to b:

[0104]

[0105] Expand the partial derivative equation of b:

[0106]

[0107] Then, the linear equations about a and b are:

[0108]

[0109] According to the linear equation system of a and b, solve the unknown coefficients a and b;

[0110] Solve for b,

[0111] Substitute b into the equation and solve for a:

[0112]

[0113] After determining the unknown coefficients, equations for porosity and sea ice temperature data can be derived for data research. Moreover, since the data is collected on site, when the data collected on site changes, the function equation is iteratively updated to generate a dynamic function.

[0114] A4. Screen samples with fracture modes of ductile extension as main crack and splitting, and establish the porosity k it and the uniaxial compressive strength of sea ice σ it relationship;

[0115] In step A4, the method for screening the sample with the fracture mode of ductile extension as the main crack and splitting includes the following steps:

[0116] D1. Obtain sea ice samples and record the initial crack length a on the sea ice surface of the sample;

[0117] D2. Set the acquisition time and simultaneously record the length of cracks on the sea ice surface;

[0118] D3. Record the expansion rate v of the sea ice cracks within each acquisition period △t

[0119] Among them, the calculation method of sea ice crack expansion rate v is:

[0120] Where △t=t n -t n-1 , △a=a n -a n-1 .

[0121] By calculating the crack growth rate, we can have a deeper understanding of the crack growth mechanism of sea ice under different stress fields, temperature changes and external loads.

[0122] The fracture mode of ductile extension to the main crack and splitting indicates that when subjected to external force, the ice body first undergoes plastic deformation, then the main crack extends and leads to splitting under specific conditions. This mode provides profound insights into how sea ice responds to external loads, temperature changes and other environmental factors. Screening out samples that exhibit such fracture modes will help reveal the fracture mechanism of sea ice and its behavioral characteristics under different environmental conditions. By selecting samples with ductile extension and splitting characteristics, it can promote the establishment of numerical and mechanical models of sea ice.

[0123] A5. Establish a uniaxial compression strength relationship model based on temperature, and combine it with the real-time temperature observation data of nearby areas to predict the real-time uniaxial compression strength of sea ice.

[0124] In step A4, the porosity k is established it and the uniaxial compressive strength of sea ice σ it The relationship consists of the following steps:

[0125] E1. Collect ice samples directly on site and perform uniaxial compression strength measurements at different sea ice temperatures. The strain rate is 10 -3 , of which 10 -3 Based on the conservative principle, the ice strength in the ductile-brittle transition zone is the greatest.

[0126] E2. Only samples with ductile extension as main crack and splitting fracture mode are retained, and samples with ductile or brittle fracture are eliminated to achieve data cleaning, so as to identify and correct these problems, ensure the accuracy and consistency of the data, and provide a more reliable basis for analysis.

[0127] E3. Based on the screened sample library, establish the sea ice uniaxial compression strength σ it The relationship between the change of sea ice temperature, namely σ it =qi(k it ).

[0128] Among them, the uniaxial compressive strength of sea ice σ is derived it The relationship between the change of sea ice temperature and the least squares method is used to fit the data to generate the sea ice uniaxial compression strength σ it A linear function of the sea ice temperature relationship.

[0129] The above-mentioned front, back, left, right, top and bottom are all based on the figures in the specification. Figure 1 As a benchmark, according to the person's observation perspective, the side of the device facing the observer is defined as the front, the left side of the observer is defined as the left, and so on.

[0130] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the scope of protection of the present invention.

[0131] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for predicting the uniaxial compressive strength of seawater based on air temperature, characterized in that: The following steps are involved: A1. At the beginning of sea ice freezing, real-time temperature data begins t Monitor the temperature of each layer of ice it , establish the relationship between air temperature and sea ice temperature profile; A2. Measuring sea ice salinity profile Si t , and establish the sea ice temperature f based on observational data it and sea ice salinity Si t The parameterized relationship of A3. Calculate the porosity k of each layer of sea ice it , and then calculate the variation of porosity of each layer with sea ice temperature based on the porosity; A4. Screen samples with fracture modes of ductile extension as main crack and splitting, and establish the porosity k it and the uniaxial compressive strength of sea ice σ it relationship; A5. Establish a uniaxial compression strength relationship model based on temperature, and combine it with the real-time temperature observation data of nearby areas to predict the real-time uniaxial compression strength of sea ice; Wherein, i=1, 2, 3, ..., n, i is the number of ice layers from top to bottom, and t is the corresponding collection time.

2. The method for predicting the uniaxial compressive strength of seawater based on air temperature according to claim 1, characterized in that: In step A1, establishing the relationship between air temperature and sea ice temperature profile includes the following steps: B1. Calculate the ratio of ice temperature data of each layer to air temperature data; B2. Define the temperature of the sea ice layer in the next day based on the ratio of the ice temperature data of each layer to the air temperature data; B3. By measuring the total thickness of sea ice and the thickness of each layer of sea ice, the standard thickness of each layer of sea ice can be calculated; B4. Establish a coordinate system and substitute the temperature parameters at the same time and the standard thickness parameters of each layer of sea ice.

3. The method for predicting the uniaxial compressive strength of seawater based on air temperature according to claim 2, characterized in that: in, Sliding average valueba it The calculation method is: The temperature of the i-th layer of sea ice in the next day is T i The calculation method is: Get the temperature of the next day through the weather forecast system, denoted as q f ; T i =ba it ×q f 。 4. The method for predicting the uniaxial compressive strength of seawater based on air temperature according to claim 3, characterized in that: In step A2, the relationship between sea ice temperature and sea ice salinity is established, including the following steps: C1. During the sea ice temperature observation period, collect sea ice samples from each layer and melt the collected samples; C2. Calculate the sea ice salinity of each layer of sea ice and form a sea ice salinity profile; C3. Establish ice temperature data for each layer it and sea ice salinity profile Si t model, and derived parameterized formulas for sea ice salinity profile and sea ice temperature.

5. The method for predicting the uniaxial compressive strength of seawater based on air temperature according to claim 4, characterized in that: In step A4, the method for screening the sample with the fracture mode of ductile extension as the main crack and splitting includes the following steps: D1. Obtain sea ice samples and record the initial crack length a on the sea ice surface of the sample; D2. Set the acquisition time and simultaneously record the length of cracks on the sea ice surface; D3. Record the expansion rate v of the sea ice cracks within each acquisition time period △t.

6. The method for predicting the uniaxial compressive strength of seawater based on air temperature according to claim 5, characterized in that: The calculation method of sea ice crack expansion rate v is: Among them, △t=t n -t n-1 , △a=a n -a n-1 .

7. The method for predicting the uniaxial compressive strength of seawater based on air temperature according to claim 6, characterized in that: The porosity and sea ice temperature data are fitted as: Let the function equation be, k i (t) = [f i (t)] = af i (t)+b, where a and b are unknown coefficients; Among them, n data observation points (f i1 , p i1 ), (f i2 , p i2 ),…(f in , p in ); The error sum of squares S is: Based on the sum of squared errors, a and b are derived to form a function of the variation of porosity with sea ice temperature.

8. The method for predicting the uniaxial compressive strength of seawater based on air temperature according to claim 7, characterized in that: The linear equations of a and b are derived from the sum of squared errors: Let S = S min When , the corresponding a and b; Find the partial derivative with respect to a: Expand the partial derivative equation of a block: Find the partial derivative with respect to b: Expand the partial derivative equation of b: Then, the linear equations about a and b are:

9. The method for predicting the uniaxial compressive strength of seawater based on air temperature according to claim 8, characterized in that: According to the linear equation system of a and b, solve the unknown coefficients a and b; Solve for b, Substitute b into the equation and solve for a:

10. The method for predicting the uniaxial compressive strength of seawater based on air temperature according to claim 9, characterized in that: In step A4, the porosity k is established it and the uniaxial compressive strength of sea ice σ it The relationship consists of the following steps: E1. Collect ice samples directly on site and perform uniaxial compression strength measurements at different sea ice temperatures. The strain rate is 10 -3 ; E2, only keep the samples with the fracture mode of ductile extension to main crack and splitting, and eliminate the samples with ductile or brittle fracture; E3. Based on the screened sample library, establish the sea ice uniaxial compression strength σ it The relationship between the change of sea ice temperature, namely σ it =qi(k it ).

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