CN105427018A - Disease concrete bridge bearing capability evaluation method - Google Patents
Disease concrete bridge bearing capability evaluation method Download PDFInfo
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Abstract
The invention discloses a disease concrete bridge bearing capability evaluation method, which supposes various uncertainties influencing disease concrete bridge bearing capability evaluation to possess random variables of certain probability distribution characteristics, and defines disease index influence degrees to a bridge bearing capability as bearing capability partial checking computation coefficients according to a bearing capability calculation method. Based on an actual disease index detection result and mathematical statistics, the method employs monte carlo random simulation calculation and a fuzzy comprehensive evaluation principle to obtain a probability distribution characteristic approximating the disease concrete bridge bearing capability to be evaluated, an furthermore obtain a bearing capability evaluation result possessing a certain probability guarantee. The method overcomes the uncertainty influences caused by neglecting randomness of various factors and fuzzyness of evaluation grade division in a present highway bridge bearing capability evaluation standard, thereby realizing more scientific and rational evaluation results.
Description
Technical field
The present invention relates to technical field of bridge engineering, be specifically related to a kind of disease concrete-bridge Bearing Capacity Evaluation method.
Background technology
Highway in China bridge is in High Speed Construction period, and low by 2013, national highway bridge has 73.53 ten thousand, and wherein concrete-bridge accounts for 90% of sum, and builds with more than 20,000 seat speed every year.But based on China's fundamental realities of the country, the principal feature of disease concrete-bridge: the early stage bridge built, design load grade is low, construction quality is poor; Coastland bridge, chlorine salt corrosion effect causes steel bar corrosion, concrete cover leafing or a series of endurance issues such as to peel off serious; Overload and oversize operation phenomenon is given prominence to, even if make also to produce into a large amount of permanance and tired disease damage problem by the bridge of new standard design.In addition, the highway bridge detection maintenance technology strength put into effect and fund input are relatively lagged behind.These factors inevitably cause a lot of disease concrete-bridge " to be runed in spite of illness ", there is larger potential safety hazard, are necessary to formulate safety, reliable, rational Bearing Capacity Evaluation method to disease concrete-bridge.
At present, the domestic evaluation main technique methods to servicing bridges load-bearing capacity is according to " JTG/TJ21-2011. highway bridge load-bearing capacity detecting appraisal code [S] ", by testing result and the corresponding evaluation criteria of bridge the key technical indexes to be assessed, carry out bearing capacity evaluation.The subject matter that this assessment technology exists has: the method is a kind of based on servicing bridges situation detection result and in conjunction with the determinacy " definite value Evaluation Method " of ultimate limit states Computing Principle, have ignored the detection technique index that is reflected in service bridge structure damage status as concrete strength, the ambiguity that the randomness of the factors such as protective layer thickness, carbonation depth, chloride ion content and evaluation grade divide on the uncertainty impact of bringing to check and evaluation result, and then causes that bearing capacity evaluation result undulatory property is large, reliability is low, artificial subjective factor is strong; Simultaneously, also need in conjunction with Test on Bridge Loading, determine the structural response of bridge structure under trial load with this, there is the limitation that testing expenses are high, the cycle is long and task is loaded down with trivial details, even to carry out traffic control, bring adverse effect to daily traffic order.
Summary of the invention
For what exist the evaluation process of disease concrete-bridge load-bearing capacity in prior art, make a big impact to evaluation result because of the randomness change of various uncertain factor and the ambiguity of rating division, make the inaccurate technical matters of evaluation result, the invention provides a kind of disease concrete-bridge Bearing Capacity Evaluation method based on Probability Statistics Theory and Theory of Fuzzy Comprehensive.
The thought of technical solution of the present invention is: applied probability statistical theory and Theory of Fuzzy Comprehensive are also evaluated disease concrete-bridge load-bearing capacity in conjunction with conventional bridge defect detection technique, first, the disease index of disease concrete-bridge is defined as load-bearing capacity subitem checking computations coefficient to load-bearing capacity influence degree, load carrying capacity of bridge computing formula is revised, reflects from in-service disease concrete-bridge actual bearer ability with this; Next, the in-service disease concrete-bridge load-bearing capacity of setting impact examines the stochastic variable calculating the various uncertain factors in assessing (comprising: disease index, material property, cross section geometric parameter and load-bearing capacity subitem checking computations coefficient) equal Normal Distribution or lognormal distribution; Finally, based in the testing result of actual disease index and mathematical statistics basis, application montecarlo(Monte Carlo) random simulation calculate and Fuzzy Synthetic Evaluation principle, inspection is set up to disease concrete-bridge load-bearing capacity and calculates Evaluation model, simulation obtains the lognormal distribution rule approximate with load-bearing capacity, that is: R ~ LN (
μ σ), and evaluation result is calculated in the load-bearing capacity inspection calculating 95% fraction.
The technical solution used in the present invention is as follows:
Design a kind of disease concrete-bridge Bearing Capacity Evaluation method, comprise the following steps:
(1) adopt conventional bridge defect detection method to disease concrete-bridge typical disease index U={u to be detected
1, u
2, u
3u
10}={ fracture width u
1, fracture length and sectional dimension ratio u
2, component surface damage ratio u
3, concrete strength u
4, concrete carbonization coefficient u
5, protective layer thickness coefficient u
6, chloride ion content u
7, concrete resistivity u
8, steel bar corrosion current potential u
9, the concrete scaling degree of depth and damage location cross section minimum dimension ratio u
10detect, detect data according to actual, application parameter is estimated and K-S Testing Statistical Hypotheses, carries out normal distribution and lognormal distribution test of hypothesis, and calculates average μ corresponding to each typical disease index
iand variation factor δ
i, obtain corresponding probability distribution parameters (μ
i, δ
i);
(2) according to u
istatistical distribution parameter (μ
i, δ
i), calculate through n MonteCarlo random simulation, produce n between u
irandom number between the maximal value of actual detected value and minimum value;
(3) by based on the disease index bearing capacity test coefficient Z of probability randomness and Fuzzy comprehensive evaluation, the load-bearing capacity deterioration coefficient ξ based on probability randomness and Fuzzy comprehensive evaluation
e, based on the concrete section reduction coefficient ξ of probability randomness and Fuzzy comprehensive evaluation
c, based on the steel area reduction coefficient ξ of probability randomness
scomposition reflection disease index is to load-bearing capacity subitem checking computations coefficient { Z, the ξ of disease concrete-bridge load-bearing capacity influence degree
e, ξ
c, ξ
s, and (4) ~ (9) check coefficient { Z, ξ to subitem in the steps below
e, ξ
ccarry out randomness comprehensively fuzzy evaluation;
(4) by described disease index u
iaccording to the form below 1 forms evaluation object { Z, ξ in Fuzzy comprehensive evaluation index system
e, ξ
cset of factors U={U
1, U
2, U
3;
(5) by u in described set of factors U
ievaluation collection V be divided into 5 grades, that is: V={ v
1v
2v
3v
4v
5}={ I, II, III, IV, V }, correspond to good, better, poor, poor, serious five kinds of states respectively, and adopt trapezoidal profile membership function mui (u
i) according to the form below 2 carries out evaluation collection V fuzzy classification and divide, to u
in random number carry out the assessment fuzzy subset r of corresponding grade
i={ r
i1, r
i2..., r
i5calculate; Wherein trapezoidal profile membership function mui (u
i) be the function in fuzzy mathematics, carry out classification by the function parameter of table 2 during application herein,
u 1~
u 10corresponding fuzzy classification Membership Function Distribution figure is shown in accompanying drawing 1 ~ 10.
(6) by formula I to described evaluation object { Z, ξ
e, ξ
ccarry out n fuzzy overall evaluation collection B respectively and calculate:
---formula I
In formula:
B
ifor { Z, ξ
e, ξ
cthe i-th evaluation grade subjection degree, i=1,2,3,4,5;
R is evaluation object { Z, ξ
e, ξ
cfuzzy relation matrix;
W is weight sets corresponding to the set of factors of evaluation object;
(7) step (6) is calculated to the fuzzy overall evaluation collection B of gained, adopt second power method of weighted mean by formula II, to evaluation object { Z, ξ
e, ξ
ccarry out comprehensively calming down for n time value D calculating respectively, wherein D ∈ (0,5)
---formula II
In formula:
V
ifor element b in B
icorresponding rating, { v
1v
2v
3v
4v
5}={ 12345 };
(8) based on the comprehensive evaluation D that step (7) calculates, by bearing capacity test coefficient, load-bearing capacity deterioration coefficient, the concrete section reduction coefficient computation sheet of " JTG/TJ21-2011. highway bridge load-bearing capacity detecting appraisal code [S] ", interpolation calculation goes out { Z, the ξ of n corresponding comprehensive evaluation D
e, ξ
c;
(9) to { Z, ξ that step (8) calculates
e, ξ
cvalue, adopt normal distribution test of hypothesis and parameter estimation, calculate Z respectively, ξ
e, ξ
caverage μ and variation factor δ;
(10) described subitem checks in coefficient based on probability randomness steel area reduction coefficient ξ
sparameters of Normal Distribution average μ according to the form below 3 value, ξ
sthe value of variation factor δ be 0.05 ~ 0.15;
(11) using disease concrete-bridge material property, cross section geometric parameter as stochastic variable, wherein material property comprises concrete strength f
dwith reinforced steel bar strength f
s, cross section geometric parameter comprises cross section size
with cross section reinforcing bar area A
s;
F
d, f
s,
, A
sstatistical nature mean parameter μ and variation factor δ detect market demand parameter estimation and normal distribution is carried out in K-S test of hypothesis or lognormal distribution test of hypothesis calculates by actual, or by existing statistics value in " GB/T50283-1999. highway engineering structural reliability designs same standard [S] ";
(12) abovementioned steps is calculated load-bearing capacity subitem checking computations coefficient Z, ξ of gained
e, ξ
c, ξ
swith the probability model f of material property, cross section geometric parameter
d, f
s,
, A
sand (μ, δ), substitute into formula III and calculate through n MonteCarlo random simulation, obtain disease concrete-bridge crucial cross section actual bearer ability;
---formula III
In formula:
R is disease concrete-bridge crucial cross section actual bearer ability;
R() for function is calculated in the actual bearer ability inspection of disease concrete-bridge crucial cross section;
F
dfor based on probability randomness concrete strength statistical value;
F
sfor based on probability randomness steel bar stress strength statistics;
for based on randomness disease concrete-bridge cross section geometric parameter statistics;
A
sfor based on randomness disease concrete-bridge crucial cross section reinforcing bar area statistics value.
Wherein, in described step (12), for ordinary reinforced concrete disease bridge, its crucial cross section actual bearer ability inspection is calculated function and is corresponded to crucial cross section actual Bend load-bearing capacity function R() be:
1) when crucial cross section is square cross section, R() be
---formula III-1
Wherein,
xfor the actual depth of compressive zone in cross section is calculated in inspection:
, b is cross-sectional width;
2) when crucial cross section be T-shape or " I " type time, R() be
1. when
, R() be
---formula III-2
2. when
, R() be
---formula III-3
Wherein,
, b is " T " or " I " cross section web width, h
f for " T " or " I " top flange, cross section thickness, b
f for " T " or " I " top flange, cross section width.
for based on randomness disease concrete-bridge cross section geometric parameter statistics, it also contains crucial cross section b, b
f , h
f etc. relating to the parameter calculating all beam sections.
Further, the disease concrete-bridge load-bearing capacity R calculating gained in step (12) is carried out to the load-bearing capacity R of lognormal distribution hypothesis and 95% fraction
0inspection is calculated, and the approximate lognormal distribution of obeying R ~ LN (μ σ) of load-bearing capacity R, probability distribution function is formula IV, and carries out R by formula V
0inspection is calculated:
---formula IV
---formula V
In formula: μ, σ are lognormal distribution location parameter;
for standardized normal distribution inverse function.
Preferably, according to the load-bearing capacity loss percentage ρ calculated based on the calculating of montecarlo random simulation and Fuzzy Synthetic Evaluation, according to the form below 4 makes general technical status assessment to disease concrete-bridge to be detected, as final assessment result, wherein:
---formula VI
In formula: R
dfor crucial section capacity design load,
。
Wherein, evaluation object { Z, ξ in described step (6)
e, ξ
cfuzzy relationship matrix r, construct by formula VII:
---formula VII.
Weight sets W according to the form below 5 value that in described step (6), the set of factors of evaluation object is corresponding,
。
Preferably, method for parameter estimation used in above step is least square method.
Preferably, in same once estimated journey, the value correspondent equal of the n related in each step, the n value namely in step (2), (5) ~ (8), (12) is equal, and n >=8000, n value is more large more accurate, in the present invention general value 10000.
Above used the separate equations, if no special instructions, is conventionally calculation formula.
Advantageous Effects of the present invention is:
1. compared with existing disease bridge structure bearing capacity evaluation technology, the inventive method is applied probability statistical theory on the one hand, especially according to the actual testing result of disease index factor, be set the stochastic variable with certain Probability Characteristics, permanance and the damage status of disease concrete bridge structure can be objectively responded, thus overcome the discreteness of disease Indexs measure result, uncertainty impact that randomness is brought to assessment result; On the other hand by Theory of Fuzzy Comprehensive, the ambiguity of factors assessment grade classification each in this bearing capacity evaluation model can be quantized, reach the object of integrated application bridge situation fox message, fully can reflect bridge actual bearer ability level to be assessed.
2. the present invention also has the feature can carrying out bridge condition detection and the true load-bearing capacity of matching disease bridge structure without the need to carrying out loading test and large-scale traffic control; Its cost is low, cycle is short, to traffic impact little and load-bearing capacity inspection to calculate result reliability high, conveniently can reach the object to disease concrete-bridge " early detection, early assessment, early maintenance ", there is provided rational basis for bridge maintenance and strengthening decision-making and expense drop into, reduce the cost of bridge daily servicing to a certain extent.
Accompanying drawing explanation
Fig. 1 is fracture width
u 1fuzzy classification subordinate function
μ(
u 1) distribution plan;
Fig. 2 is fracture length and sectional dimension ratio
u 2fuzzy classification subordinate function
μ(
u 2) distribution plan;
Fig. 3 is component surface damage ratio
u 3fuzzy classification subordinate function
μ(
u 3) distribution plan;
Fig. 4 is concrete strength
u 4fuzzy classification subordinate function
μ(
u 4) distribution plan;
Fig. 5 is concrete carbonization coefficient
u 5fuzzy classification subordinate function
μ(
u 5) distribution plan;
Fig. 6 is protective layer thickness coefficient
u 6fuzzy classification subordinate function
μ(
u 6) distribution plan;
Fig. 7 is chloride ion content
u 7fuzzy classification subordinate function
μ(
u 7) distribution plan;
Fig. 8 is concrete resistivity
u 8fuzzy classification subordinate function
μ(
u 8) distribution plan;
Fig. 9 is steel bar corrosion current potential
u 9fuzzy classification subordinate function
μ(
u 9) distribution plan;
Figure 10 is the concrete scaling degree of depth and damage location cross section minimum dimension ratio
u 10fuzzy classification subordinate function
μ(
u 10) distribution plan;
Figure 11 Defect inspection index subordinate function
μ(
u i ) distribution schematic diagram;
Figure 12 is the schematic cross-sectional view (unit: cm) of disease bridge in embodiment 1;
Figure 13 be disease bridge in embodiment 1 cored slab spaning middle section size and and arrangement of reinforcement (unit: cm);
Figure 14 is the superstructure schematic cross section (unit: cm) of disease bridge in embodiment 2;
Figure 15 is the girder arrangement of reinforcement (unit: cm) of disease bridge in embodiment 2;
Figure 16 is the process flow diagram of disease concrete-bridge Bearing Capacity Evaluation method of the present invention.
Embodiment
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described, but following examples are only used to describe the present invention in detail, and limit the scope of the invention never in any form.Detection method involved by following embodiment, statistical method, function and calculating formula, if no special instructions, be then conventional detection method, statistical method, function and calculating formula.
Embodiment 1: by disease concrete-bridge Bearing Capacity Evaluation method of the present invention, is applied to the in-service load-bearing capacity inspection having a disease freely-supported blank board bridge and calculates in evaluation.This disease bridge overview is as follows: standard span 12m, cored slab total length 11.96m, its superstructure schematic cross-sectional view and cored slab spaning middle section size and arrangement of reinforcement, as shown in Figure 12 and Figure 13, concrete design strength C25, main muscle adopts II grade of reinforcing bar, through checking calculation design load-bearing capacity M
0=502.4kNm.
Content according to the present invention carries out Bearing Capacity Evaluation to this bridge, and detailed process is as follows:
(1) adopt conventional bridge defect detection method to disease concrete-bridge typical disease index U={u to be detected
1, u
2, u
3u
10}={ fracture width u
1, fracture length and sectional dimension ratio u
2, component surface damage ratio u
3, concrete strength u
4, concrete carbonization coefficient u
5, protective layer thickness coefficient u
6, chloride ion content u
7, concrete resistivity u
8, steel bar corrosion current potential u
9, the concrete scaling degree of depth and damage location cross section minimum dimension ratio u
10detect, detect data according to actual, application parameter estimates (least square method) and K-S Testing Statistical Hypotheses, carries out normal distribution and lognormal distribution test of hypothesis, and calculates average μ corresponding to each typical disease index
iand variation factor δ
i, obtain corresponding probability distribution parameters (μ
i, δ
i); Result is as shown in table 6 below:
。
(2) according in step (1)
u istatistic analysis result, calculates through 10000 MonteCarlo random simulations, produce 10000 between
u irandom number between the maximal value of actual detected value and minimum value.
(3) by based on the disease index bearing capacity test coefficient Z of probability randomness and Fuzzy comprehensive evaluation, the load-bearing capacity deterioration coefficient ξ based on probability randomness and Fuzzy comprehensive evaluation
e, based on the concrete section reduction coefficient ξ of probability randomness and Fuzzy comprehensive evaluation
c, based on the steel area reduction coefficient ξ of probability randomness
scomposition reflection disease index is to load-bearing capacity subitem checking computations coefficient { Z, the ξ of disease concrete-bridge load-bearing capacity influence degree
e, ξ
c, ξ
s, and to subitem checking computations coefficient { Z, ξ
e, ξ
ccarry out randomness comprehensively fuzzy evaluation.
(4) disease index u
ievaluation object { Z, ξ in Fuzzy comprehensive evaluation index system is formed by table 1
e, ξ
cset of factors U={U
1, U
2, U
3.
(5) by u in set of factors U
ievaluation collection V be divided into 5 grades, that is: V={ v
1v
2v
3v
4v
5}={ I, II, III, IV, V }, correspond to good, better, poor, poor, serious five kinds of states respectively, and adopt trapezoidal profile membership function mui (u
i) carry out the division of evaluation collection V fuzzy classification, to u by table 2
in random number carry out the assessment fuzzy subset r of corresponding grade
i={ r
i1, r
i2..., r
i5calculate.
(6) by formula I couple of evaluation object { Z, ξ
e, ξ
ccarry out 10000 fuzzy overall evaluation collection B respectively and calculate:
---formula I
In formula:
B
ifor { Z, ξ
e, ξ
cthe i-th evaluation grade subjection degree, i=1,2,3,4,5;
R is evaluation object { Z, ξ
e, ξ
cfuzzy relation matrix;
W is weight sets corresponding to the set of factors of evaluation object.
Wherein evaluation object { Z, ξ
e, ξ
cfuzzy relationship matrix r, construct by formula VII:
---formula VII.
The weight sets W that the set of factors of evaluation object is corresponding presses table 5 value.
(7) step (6) is calculated to the fuzzy overall evaluation collection B of gained, adopt second power method of weighted mean by formula II, to evaluation object { Z, ξ
e, ξ
ccarry out comprehensively calming down for 10000 times value D calculating respectively, wherein D ∈ (0,5)
---formula II
In formula:
V
ifor element b in B
icorresponding rating, { v
1v
2v
3v
4v
5}={ 12345 }.
(8) based on the comprehensive evaluation D that step (7) calculates, by bearing capacity test coefficient, load-bearing capacity deterioration coefficient, the concrete section reduction coefficient computation sheet of " JTG/TJ21-2011. highway bridge load-bearing capacity detecting appraisal code [S] ", interpolation calculation goes out { Z, the ξ of 10000 corresponding comprehensive evaluation D
e, ξ
c.
(9) to { Z, ξ that step (8) calculates
e, ξ
cvalue, adopt normal distribution test of hypothesis and parameter estimation, calculate Z respectively, ξ
e, ξ
caverage μ and variation factor δ.
(10) subitem checks in coefficient based on probability randomness steel area reduction coefficient ξ
sparameters of Normal Distribution average μ press table 3 value, ξ
sthe value of variation factor δ be 0.05 ~ 0.15.
The statistical parameter result of corresponding subitem checking computations coefficient is as shown in table 7 below:
。
(11) factual survey is adopted also to obtain the material property of this hollow slab bridge, the statistical nature parameter of cross section geometric parameter with reference to the method for " GB/T50283-1999. highway engineering structural reliability designs same standard [S] ", as shown in table 8 below:
。
(12) load-bearing capacity subitem checking computations coefficient Z, ξ of gained will be calculated
e, ξ
c, ξ
swith the probability model f of material property, cross section geometric parameter
d, f
s,
, A
sand (μ, δ), substitute into formula III and calculate through 10000 MonteCarlo random simulations, obtain disease concrete-bridge crucial cross section actual bearer ability;
---formula III
In formula:
R is disease concrete-bridge crucial cross section actual bearer ability;
R() for function is calculated in the actual bearer ability inspection of disease concrete-bridge crucial cross section;
F
dfor based on probability randomness concrete strength statistical value;
F
sfor based on probability randomness steel bar stress strength statistics;
for based on randomness disease concrete-bridge cross section geometric parameter statistics;
A
sfor based on randomness disease concrete-bridge crucial cross section reinforcing bar area statistics value.
In the present embodiment, R() III-2 and III-3 formula that specifies by formula III, and calculate cross section depth of compressive zone based on nonce count, can be substituted into by the computing machine judgement repeatedly automatically carried out between formula III-2 and III-3 repeatedly in computation process and calculate.
Result of calculation shows: the actual bending bearing capacity of this freely-supported hollow slab bridge spaning middle section obeys R ~ LN(6.1586,0.1665) lognormal distribution, its approximate probability distribution function is:
95% corresponding fraction load-bearing capacity
r 0=364.05kNm and loss percentage
ρ=27.5%.
By table 4, general technical status assessment is made to disease concrete-bridge to be detected, as final assessment result, this bridge general technical situation is rated as the 5th class, that is: in the hole, general using limit pole state can not be met, need to carry out keeping in repair, reinforce or adopt certain limit for tonnage measure with this to maintain this bridge normal operation security.
Simultaneously, for verifying feasibility of the present invention, again respectively by prior art, that is: " the definite value analytic approach " of " JTG/TJ21-2011. highway bridge load-bearing capacity detecting appraisal code [S] " is evaluated and loading test evaluation, evaluate this bridge load-bearing capacity, three's Comparative result is as shown in table 9 below:
。
" definite value analytic approach " assessment result of evaluation result in comparative example 1 and " JTG/TJ21-2011. highway bridge load-bearing capacity detecting appraisal code [S] ", the actual bearer ability applying evaluation result that disease concrete-bridge Bearing Capacity Evaluation method of the present invention draws and bridge to be measured is close, and has more rationality, reliability.
Embodiment 2: by disease concrete-bridge Bearing Capacity Evaluation method of the present invention, is applied to the in-service load-bearing capacity inspection having a T-shaped beam bridge of disease and calculates in evaluation.This is in-service the T-shaped beam bridge basic situation of disease: be 3 hole 20m assembled steel reinforced concrete Simple T-Girders, superstructure transverse section and girder arrangement of reinforcement are as shown in Figure 14 and Figure 15, concrete design strength C25, main muscle adopts with II grade of reinforcing bar, through checking former Cross section Design load-bearing capacity
m 0=2196.57kNm.
Carry out Bearing Capacity Evaluation according to content of the present invention to this bridge, detailed process is as follows:
(1) adopt conventional bridge defect detection method, statistical study obtains this in-service T-shaped beam bridge disease index
u i probability Distribution Model and statistical parameter (
μ i δ i ), result is as shown in table 10:
。
According to disease index U={
u 1 u 2 u 3 u 10detection statistics result, according to the evaluation process of step (2) ~ (10) in embodiment 1, by 10000 montecarlo simulation calculation, evaluation obtain this bridge load-bearing capacity subitem checking computations coefficient Parameters of Normal Distribution, result is as shown in table 11 below.
。
(11) adopt factual survey and obtain the statistical nature parameter of this T-shaped bridge material property, cross section geometric parameter with reference to the method for " GB/T50283-1999. highway engineering structural reliability designs same standard [S] ", as shown in table 12 below:
。
(12) comprehensive above result of calculation, substitute into formula III and calculate through 10000 MonteCarlo random simulations, result of calculation shows: the actual bending bearing capacity in this freely-supported T-shaped spanning middle section is obeyed
r~ LN(7.7645,0.2749) lognormal distribution, its approximate probability distribution function is:
95% corresponding fraction load-bearing capacity
r 0=1542.7kNm and loss percentage
ρ=29.68%.
By table 5 general technical condition evaluation standard, this bridge general technical situation is rated as the 5th class, that is: in the hole.
Equally, for verifying the feasibility inspection of this bridge load-bearing capacity being calculated to evaluation of the present invention, again respectively by prior art, that is: " the definite value analytic approach " of " JTG/TJ21-2011. highway bridge load-bearing capacity detecting appraisal code [S] " is assessed and loading test, assess this bridge load-bearing capacity, three's Comparative result is as shown in table 13 below:
。
Known by the contrast of three's evaluation result, apply disease concrete-bridge Bearing Capacity Evaluation method provided by the invention, the actual bearer ability load-bearing capacity inspection of this in-service simple supported T-beam being calculated to evaluation result and bridge to be measured is close, and has more rationality, reliability.
Instrument and equipment involved in the embodiment above if no special instructions, is routine instrument device; The involved raw material of industry if no special instructions, is commercially available regular industrial raw material.
In conjunction with the accompanying drawings and embodiments the present invention is described in detail above, but, person of ordinary skill in the field can understand, under the prerequisite not departing from present inventive concept, each design parameter in above-described embodiment can also be changed, form multiple specific embodiment, be common variation range of the present invention, describe in detail no longer one by one at this.
Claims (8)
1. a disease concrete-bridge Bearing Capacity Evaluation method, is characterized in that, comprise the following steps:
(1) adopt conventional bridge defect detection method to disease concrete-bridge typical disease index U={u to be detected
1, u
2, u
3u
10}={ fracture width u
1, fracture length and sectional dimension ratio u
2, component surface damage ratio u
3, concrete strength u
4, concrete carbonization coefficient u
5, protective layer thickness coefficient u
6, chloride ion content u
7, concrete resistivity u
8, steel bar corrosion current potential u
9, the concrete scaling degree of depth and damage location cross section minimum dimension ratio u
10detect, detect data according to actual, application parameter is estimated and K-S Testing Statistical Hypotheses, carries out normal distribution and lognormal distribution test of hypothesis, and calculate average μ corresponding to each typical disease index to described each typical disease index
iand variation factor δ
i, obtain corresponding probability distribution parameters (μ
i, δ
i);
(2) according to u
istatistical distribution parameter (μ
i, δ
i), calculate through n MonteCarlo random simulation, produce n between u
irandom number between the maximal value of actual detected value and minimum value;
(3) by based on the disease index bearing capacity test coefficient Z of probability randomness and Fuzzy comprehensive evaluation, the load-bearing capacity deterioration coefficient ξ based on probability randomness and Fuzzy comprehensive evaluation
e, based on the concrete section reduction coefficient ξ of probability randomness and Fuzzy comprehensive evaluation
c, based on the random property steel area reduction coefficient ξ of probability
scomposition reflection disease index is to load-bearing capacity subitem checking computations coefficient { Z, the ξ of disease concrete-bridge load-bearing capacity influence degree
e, ξ
c, ξ
s, and (5) ~ (9) check coefficient { Z, ξ to subitem in the steps below
e, ξ
ccarry out randomness comprehensively fuzzy evaluation;
(4) by described disease index u
iaccording to the form below 1 forms evaluation object { Z, ξ in Fuzzy comprehensive evaluation index system
e, ξ
cset of factors U={U
1, U
2, U
3;
(5) by u in described set of factors U
ievaluation collection V be divided into 5 grades, that is: V={ v
1v
2v
3v
4v
5}={ I, II, III, IV, V }, correspond to good, better, poor, poor, serious five kinds of states respectively, and adopt trapezoidal profile membership function mui (u
i) according to the form below 2 carries out evaluation collection V fuzzy classification and divide, to u
in random number carry out the assessment fuzzy subset r of corresponding grade
i={ r
i1, r
i2..., r
i5calculate;
(6) by formula I to described evaluation object { Z, ξ
e, ξ
ccarry out n fuzzy overall evaluation collection B respectively and calculate:
---formula I
In formula:
B
ifor { Z, ξ
e, ξ
cthe i-th evaluation grade subjection degree, i=1,2,3,4,5;
R is evaluation object { Z, ξ
e, ξ
cfuzzy relation matrix;
W is weight sets corresponding to the set of factors of evaluation object;
(7) step (6) is calculated to the fuzzy overall evaluation collection B of gained, adopt second power method of weighted mean by formula II, to evaluation object { Z, ξ
e, ξ
ccarry out comprehensively calming down for n time value D calculating respectively, wherein D ∈ (0,5)
---formula II
In formula:
V
ifor element b in B
icorresponding rating, { v
1v
2v
3v
4v
5}={ 12345 };
(8) based on the comprehensive evaluation D that step (7) calculates, by bearing capacity test coefficient, load-bearing capacity deterioration coefficient, the concrete section reduction coefficient computation sheet of " JTG/TJ21-2011. highway bridge load-bearing capacity detecting appraisal code [S] ", interpolation calculation goes out { Z, the ξ of n corresponding comprehensive evaluation D
e, ξ
c;
(9) to { Z, ξ that step (8) calculates
e, ξ
cvalue, adopt normal distribution test of hypothesis and parameter estimation, calculate Z respectively, ξ
e, ξ
caverage μ and variation factor δ;
(10) described subitem checks in coefficient based on probability randomness steel area reduction coefficient ξ
sparameters of Normal Distribution average μ according to the form below 3 value, ξ
sthe value of variation factor δ be 0.05 ~ 0.15;
(11) using disease concrete-bridge material property, cross section geometric parameter as stochastic variable, wherein material property comprises concrete strength f
dwith reinforced steel bar strength f
s, cross section geometric parameter comprises cross section size
with cross section reinforcing bar area A
s;
F
d, f
s,
, A
sstatistical nature mean parameter μ and variation factor δ detect market demand parameter estimation and normal distribution is carried out in K-S test of hypothesis or lognormal distribution test of hypothesis calculates by actual, or by existing statistics value in " GB/T50283-1999. highway engineering structural reliability designs same standard [S] ";
(12) abovementioned steps is calculated load-bearing capacity subitem checking computations coefficient Z, ξ of gained
e, ξ
c, ξ
swith the probability model f of material property, cross section geometric parameter
d, f
s,
, A
sand (μ, δ), substitute into formula III and calculate through n MonteCarlo random simulation, obtain disease concrete-bridge crucial cross section actual bearer ability;
---formula III
In formula:
R is disease concrete-bridge crucial cross section actual bearer ability;
R() for function is calculated in the actual bearer ability inspection of disease concrete-bridge crucial cross section;
F
dfor based on probability randomness concrete strength statistical value;
F
sfor based on probability randomness steel bar stress strength statistics;
for based on randomness disease concrete-bridge cross section geometric parameter statistics;
A
sfor based on randomness disease concrete-bridge crucial cross section reinforcing bar area statistics value.
2. disease concrete-bridge Bearing Capacity Evaluation method according to claim 1, is characterized in that, the disease concrete-bridge load-bearing capacity R calculating gained is carried out to the load-bearing capacity R of lognormal distribution hypothesis and 95% fraction in step (12)
0inspection is calculated, and the approximate lognormal distribution of obeying R ~ LN (μ σ) of load-bearing capacity R, probability distribution function is formula IV, and carries out R by formula V
0inspection is calculated:
---formula IV
---formula V
In formula: μ, σ are lognormal distribution location parameter;
for standardized normal distribution inverse function.
3. disease concrete-bridge Bearing Capacity Evaluation method according to claim 1, it is characterized in that, according to the load-bearing capacity loss percentage ρ calculated based on the calculating of montecarlo random simulation and Fuzzy Synthetic Evaluation, according to the form below 4 makes general technical status assessment to disease concrete-bridge to be detected, as final assessment result, wherein:
---formula VI
In formula: R
dfor crucial section capacity design load,
。
4. disease concrete-bridge Bearing Capacity Evaluation method according to claim 1, is characterized in that, evaluation object { Z, ξ in described step (6)
e, ξ
cfuzzy relationship matrix r, construct by formula VII:
---formula VII.
5. disease concrete-bridge Bearing Capacity Evaluation method according to claim 1, is characterized in that, weight sets W according to the form below 5 value that in described step (6), the set of factors of evaluation object is corresponding,
。
6. disease concrete-bridge Bearing Capacity Evaluation method according to claim 1, it is characterized in that, in described step (1), (9), (11), method for parameter estimation used is least square method.
7. disease concrete-bridge Bearing Capacity Evaluation method according to claim 1, is characterized in that, in described step (2), (5) ~ (8), (12), and the value correspondent equal of n, n >=8000.
8. disease concrete-bridge Bearing Capacity Evaluation method according to claim 1, it is characterized in that, in described step (12), for ordinary reinforced concrete disease bridge, its crucial cross section actual bearer ability inspection is calculated function and is corresponded to crucial cross section actual Bend load-bearing capacity function R():
1) when crucial cross section is square cross section, R() be
---formula III-1
Wherein,
xfor the actual depth of compressive zone in cross section is calculated in inspection:
, b is cross-sectional width;
2) when crucial cross section be T-shape or " I " type time, R() be
1. when
, R() be
---formula III-2
2. when
, R() be
---formula III-3
Wherein,
, b is " T " or " I " cross section web width, h
f for " T " or " I " top flange, cross section thickness, b
f for " T " or " I " top flange, cross section width.
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