The Experts below are selected from a list of 96 Experts worldwide ranked by ideXlab platform

Prayogi Arie - One of the best experts on this subject based on the ideXlab platform.

  • Pengaruh Variasi Camber Terhadap Perilaku Jembatan Rangka Baja,
    2014
    Co-Authors: Prayogi Arie
    Abstract:

    Camber merupakan ruang kosong yang terdapat pada bawah jembatan yang memanfaatkan lengkungan lantai kendaraan jembatan. Camber biasa disebut dengan anti lendutan karena camber dibuat untuk melawan lendutan yang mungkin terjadi akibat beban yang bekerja. Jika terjadi lendutan maka tidak akan melebihi garis netral jembatan sehingga masih memungkinkan ruang kosong untuk kegiatan di bawah jembatan. Pada penelitian ini menggunakan analisis software analisa struktur dengan menggunakan 12 model jembatan yang terdiri dari empat variasi tipe rangka dan tiga variasi ketinggian camber. Empat variasi tipe rangka itu adalah Pratt Truss, Howe Truss, Warren Truss dan K-Truss dan tiga variasi camber itu adalah 0, 0,07 dan 0,14 meter atau 0%, 1,17% dan 2,33%. Analisa pembebanan menggunakan beban terpusat dengan penambahan beban setiap 200 kg sampai masing-masing model jembatan mengalami lendutan 1/800l atau 7,5 mm. Tujuannya untuk mengetahui tipe rangka manakah yang paling efektif ditinjau dari beban maksimum yang mampu ditahan, lendutan yang terjadi pada beban tertentu dan nilai gaya batangnya terhadap berat sendiri jembatannya. Hasil analisis menunjukan bahwa semua model jembatan cenderung mengalami penurunan efektifitas akibat perlakuan pemberian camber. Beban maksimum yang mampu ditahan terbesar yaitu pada model K-Truss camber 0% dengan beban 3010,79 kg sedangkan model yang terlemah yaitu Howe Truss camber 2,33% dengan beban 2163,12 kg. Lendutan struktur terkecil pada saat beban 2000 kg terjadi pada model K- Truss camber 0% sebesar 5,07 mm dan lendutan terbesar terjadi pada model Howe Truss camber 2,33% sebesar 6,96 mm. Jadi camber dipakai bukan untuk mengurangi lendutan melainkan untuk memberi ruang kosong di bawah jembata

  • PENGARUH VARIASI CAMBER TERHADAP PERILAKU JEMBATAN RANGKA BAJA
    Jurusan Teknik Sipil Fakultas Teknik Universitas Brawijaya, 2014
    Co-Authors: Prayogi Arie, Zacoeb Achfas, Wibowo Ari
    Abstract:

    Camber merupakan ruang terbuka  yang terdapat pada bawah jembatan yang memanfaatkan lengkungan lantai kendaraan jembatan. Camber biasa disebut dengan anti lendutan karena camber dibuat untuk melawan lendutan yang mungkin terjadi akibat beban yang bekerja. Jika terjadi lendutan maka tidak akan melebihi garis netral jembatan sehingga masih memungkinkan ruang kosong untuk kegiatan di bawah jembatan. Pada penelitian ini menggunakan analisis software analisa struktur dengan menggunakan 12 model jembatan yang terdiri dari empat variasi tipe rangka dan tiga variasi ketinggian camber. Empat variasi tipe rangka itu adalah Pratt Truss, Howe Truss, Warren Truss dan K-Truss dan tiga variasi camber itu adalah 0, 0,07 dan 0,14 meter atau 0%, 1,17% dan 2,33%. Analisa pembebanan menggunakan beban terpusat dengan penambahan beban setiap 200 kg sampai masing-masing model jembatan mengalami lendutan 1/800l atau 7,5 mm. Tujuannya untuk mengetahui tipe rangka manakah yang paling efektif ditinjau dari beban maksimum yang mampu ditahan, lendutan yang terjadi pada beban tertentu dan nilai gaya batangnya terhadap berat sendiri jembatannya. Hasil analisis menunjukan bahwa semua model jembatan cenderung mengalami penurunan efektifitas akibat perlakuan pemberian camber. Beban maksimum yang mampu ditahan terbesar yaitu pada model K-Truss camber 0% dengan beban 3010,79 kg sedangkan model yang terlemah yaitu Howe Truss camber 2,33% dengan beban 2163,12 kg. Lendutan struktur terkecil pada saat beban 2000 kg terjadi pada model K-Truss camber 0% sebesar 5,07 mm dan lendutan terbesar terjadi pada model Howe Truss camber 2,33% sebesar 6,96 mm. Jadi camber dipakai bukan untuk mengurangi lendutan melainkan untuk memberi ruang kosong di bawah jembatan. Kata kunci: beban maksimum, efektifitas, lendutan, tipe jembatan rangka, variasi cambe

Döhler Michael - One of the best experts on this subject based on the ideXlab platform.

  • Determination of structural and damage detection system influencing parameters on the value of information
    'SAGE Publications', 2020
    Co-Authors: Long Lijia, Döhler Michael, Thöns Sebastian
    Abstract:

    A method to determine the influencing parameters of a structural and damage detection system is proposed based on the value of information analysis. The value of information analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of damage detection system for the structural integrity management during service life. First, the influencing parameters of the structural system, such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the influencing parameters on the damage detection system performance, including number of sensors, sensor locations, measurement noise, and the Type-I error are investigated. The pre-posterior probabilistic model is computed utilizing the Bayes? theorem to update the prior system model with the damage indication information. Finally, the value of damage detection system is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences, as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt Truss bridge girder is carried out to validate the method. The analysis shows that the deterioration rate is the most sensitive parameter on the effect of relative value of information over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative value of information; only specific sensor locations near the highest utilized components lead to a high relative value of information; measurement noise and the Type-I error should be controlled and be as small as possible. An optimal sensor employment with highest relative value of information is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies?before implementation?for similar bridges and to optimize the damage detection system settings and sensor configuration for minimum expected costs and risks

  • Determination of structural and damage detection system influencing parameters on the value of information
    SAGE Publications (UK and US), 2020
    Co-Authors: Long Lijia, Döhler Michael, Thöns Sebastian
    Abstract:

    International audienceA method to determine the influencing parameters of a structural and Damage Detection System (DDS) is proposed based on the Value of Information (VoI) analysis. The VoI analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of DDS for the structural integrity management during service life. First the influencing parameters of the structural system, such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the influencing parameters on the DDS performance, including number of sensors, sensor locations, measurement noise and the Type I error are investigated. The pre-posterior probabilistic model is computed utilizing the Bayes' theorem to update the prior system model with the damage indication information. Finally, the value of DDS is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences, as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt Truss bridge girder is carried out to validate the method. The analysis shows that the deterioration rate is the most sensitive parameter on the effect of relative VoI over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative VoI; only specific sensor locations near the highest utilized components lead to a high relative VoI; measurement noise and the Type I error should be controlled and be as small as possible. An optimal sensor employment with highest relative VoI is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies-before implementation-for similar bridges and to optimize the DDS settings and sensor configuration for minimum expected costs and risks

  • The effects of deterioration models on the value of damage detection information
    HAL CCSD, 2018
    Co-Authors: Long Lijia, Thöns Sebastian, Döhler Michael
    Abstract:

    International audienceThis paper addresses the effects of the deterioration on the value of damage detection information. The quantification of the value of damage detection information for deteriorated structures is based on Bayesian pre-posterior decision analysis, comprising structural system performance models, consequence, benefit and costs models and damage detection information models throughout the service life of a structural system. The value of damage detection information accounts for the relevance and precision of the information to ensure the structural integrity and to reduce the potential structural system risks and expected costs throughout the ser-vice life before implementing damage detection system. With the developed approach, the value of damage detection information for a statically determinate Pratt Truss bridge girder subjected to different deterioration models is calculated. The analysis shows the impact of the deterioration model parameters on the value of damage detection information. The results can be used to develop optimal maintenance strategies before implementation of the damage detection system

  • The effects of SHM system parameters on the value of damage detection information
    HAL CCSD, 2018
    Co-Authors: Long Lijia, Thöns Sebastian, Döhler Michael
    Abstract:

    International audienceThis paper addresses how the value of damage detection information depends on key parameters of the Structural Health Monitoring (SHM) system including number of sensors and sensor locations. The Damage Detection System (DDS) provides the information by comparing ambient vibration measurements of a (healthy) reference state with measurements of the current structural system. The performance of DDS method depends on the physical measurement properties such as the number of sensors, sensor positions, measuring length and sensor type, measurement noise, ambient excitation and sampling frequency, as well as on the data processing algorithm including the chosen type I error for the indication threshold. The quantification of the value of information (VoI) is an expected utility based Bayesian decision analysis method for quantifying the difference of the expected economic benefits with and without information. The (pre-)posterior probability is computed utilizing the Bayesian updating theorem for all possible indications. If changing any key parameters of DDS, the updated probability of system failure given damage detection information will be varied due to different indication of probability of damage, which will result in changes of value of damage detection information. The DDS system is applied in a statically determinate Pratt Truss bridge girder. Through the analysis of the value of information with different SHM system characteristics, the settings of DDS can be optimized for minimum expected costs and risks before implementation

  • Damage Detection and Deteriorating Structural Systems
    HAL CCSD, 2017
    Co-Authors: Long Lijia, Thöns Sebastian, Döhler Michael
    Abstract:

    International audienceThis paper addresses the quantification of the value of damage detection system and algorithm information on the basis of Value of Information (VoI) analysis to enhance the benefit of damage detection information by providing the basis for its optimization before it is performed and implemented. The approach of the quantification the value of damage detection information builds upon the Bayesian decision theory facilitating the utilization of damage detection performance models, which describe the information and its precision on structural system level, facilitating actions to ensure the structural integrity and facilitating to describe the structural system performance and its function-ality throughout the service life. The structural system performance is described with its functionality, its deterioration and its behavior under extreme loading. The structural system reliability given the damage detection information is determined utilizing Bayesian updating. The damage detection performance is described with the probability of indication for different component and system damage states taking into account type 1 and type 2 errors. The value of damage detection information is then calculated as the difference between the expected benefits and risks utilizing the damage detection information or not. With an application example of the developed approach based on a deteriorating Pratt Truss system, the value of damage detection information is determined , demonstrating the potential of risk reduction and expected cost reduction

Long Lijia - One of the best experts on this subject based on the ideXlab platform.

  • Determination of structural and damage detection system influencing parameters on the value of information
    'SAGE Publications', 2020
    Co-Authors: Long Lijia, Döhler Michael, Thöns Sebastian
    Abstract:

    A method to determine the influencing parameters of a structural and damage detection system is proposed based on the value of information analysis. The value of information analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of damage detection system for the structural integrity management during service life. First, the influencing parameters of the structural system, such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the influencing parameters on the damage detection system performance, including number of sensors, sensor locations, measurement noise, and the Type-I error are investigated. The pre-posterior probabilistic model is computed utilizing the Bayes? theorem to update the prior system model with the damage indication information. Finally, the value of damage detection system is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences, as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt Truss bridge girder is carried out to validate the method. The analysis shows that the deterioration rate is the most sensitive parameter on the effect of relative value of information over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative value of information; only specific sensor locations near the highest utilized components lead to a high relative value of information; measurement noise and the Type-I error should be controlled and be as small as possible. An optimal sensor employment with highest relative value of information is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies?before implementation?for similar bridges and to optimize the damage detection system settings and sensor configuration for minimum expected costs and risks

  • Determination of structural and damage detection system influencing parameters on the value of information
    SAGE Publications (UK and US), 2020
    Co-Authors: Long Lijia, Döhler Michael, Thöns Sebastian
    Abstract:

    International audienceA method to determine the influencing parameters of a structural and Damage Detection System (DDS) is proposed based on the Value of Information (VoI) analysis. The VoI analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of DDS for the structural integrity management during service life. First the influencing parameters of the structural system, such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the influencing parameters on the DDS performance, including number of sensors, sensor locations, measurement noise and the Type I error are investigated. The pre-posterior probabilistic model is computed utilizing the Bayes' theorem to update the prior system model with the damage indication information. Finally, the value of DDS is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences, as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt Truss bridge girder is carried out to validate the method. The analysis shows that the deterioration rate is the most sensitive parameter on the effect of relative VoI over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative VoI; only specific sensor locations near the highest utilized components lead to a high relative VoI; measurement noise and the Type I error should be controlled and be as small as possible. An optimal sensor employment with highest relative VoI is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies-before implementation-for similar bridges and to optimize the DDS settings and sensor configuration for minimum expected costs and risks

  • The effects of deterioration models on the value of damage detection information
    HAL CCSD, 2018
    Co-Authors: Long Lijia, Thöns Sebastian, Döhler Michael
    Abstract:

    International audienceThis paper addresses the effects of the deterioration on the value of damage detection information. The quantification of the value of damage detection information for deteriorated structures is based on Bayesian pre-posterior decision analysis, comprising structural system performance models, consequence, benefit and costs models and damage detection information models throughout the service life of a structural system. The value of damage detection information accounts for the relevance and precision of the information to ensure the structural integrity and to reduce the potential structural system risks and expected costs throughout the ser-vice life before implementing damage detection system. With the developed approach, the value of damage detection information for a statically determinate Pratt Truss bridge girder subjected to different deterioration models is calculated. The analysis shows the impact of the deterioration model parameters on the value of damage detection information. The results can be used to develop optimal maintenance strategies before implementation of the damage detection system

  • The effects of SHM system parameters on the value of damage detection information
    HAL CCSD, 2018
    Co-Authors: Long Lijia, Thöns Sebastian, Döhler Michael
    Abstract:

    International audienceThis paper addresses how the value of damage detection information depends on key parameters of the Structural Health Monitoring (SHM) system including number of sensors and sensor locations. The Damage Detection System (DDS) provides the information by comparing ambient vibration measurements of a (healthy) reference state with measurements of the current structural system. The performance of DDS method depends on the physical measurement properties such as the number of sensors, sensor positions, measuring length and sensor type, measurement noise, ambient excitation and sampling frequency, as well as on the data processing algorithm including the chosen type I error for the indication threshold. The quantification of the value of information (VoI) is an expected utility based Bayesian decision analysis method for quantifying the difference of the expected economic benefits with and without information. The (pre-)posterior probability is computed utilizing the Bayesian updating theorem for all possible indications. If changing any key parameters of DDS, the updated probability of system failure given damage detection information will be varied due to different indication of probability of damage, which will result in changes of value of damage detection information. The DDS system is applied in a statically determinate Pratt Truss bridge girder. Through the analysis of the value of information with different SHM system characteristics, the settings of DDS can be optimized for minimum expected costs and risks before implementation

  • Damage Detection and Deteriorating Structural Systems
    HAL CCSD, 2017
    Co-Authors: Long Lijia, Thöns Sebastian, Döhler Michael
    Abstract:

    International audienceThis paper addresses the quantification of the value of damage detection system and algorithm information on the basis of Value of Information (VoI) analysis to enhance the benefit of damage detection information by providing the basis for its optimization before it is performed and implemented. The approach of the quantification the value of damage detection information builds upon the Bayesian decision theory facilitating the utilization of damage detection performance models, which describe the information and its precision on structural system level, facilitating actions to ensure the structural integrity and facilitating to describe the structural system performance and its function-ality throughout the service life. The structural system performance is described with its functionality, its deterioration and its behavior under extreme loading. The structural system reliability given the damage detection information is determined utilizing Bayesian updating. The damage detection performance is described with the probability of indication for different component and system damage states taking into account type 1 and type 2 errors. The value of damage detection information is then calculated as the difference between the expected benefits and risks utilizing the damage detection information or not. With an application example of the developed approach based on a deteriorating Pratt Truss system, the value of damage detection information is determined , demonstrating the potential of risk reduction and expected cost reduction

Thöns Sebastian - One of the best experts on this subject based on the ideXlab platform.

  • Determination of structural and damage detection system influencing parameters on the value of information
    'SAGE Publications', 2020
    Co-Authors: Long Lijia, Döhler Michael, Thöns Sebastian
    Abstract:

    A method to determine the influencing parameters of a structural and damage detection system is proposed based on the value of information analysis. The value of information analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of damage detection system for the structural integrity management during service life. First, the influencing parameters of the structural system, such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the influencing parameters on the damage detection system performance, including number of sensors, sensor locations, measurement noise, and the Type-I error are investigated. The pre-posterior probabilistic model is computed utilizing the Bayes? theorem to update the prior system model with the damage indication information. Finally, the value of damage detection system is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences, as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt Truss bridge girder is carried out to validate the method. The analysis shows that the deterioration rate is the most sensitive parameter on the effect of relative value of information over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative value of information; only specific sensor locations near the highest utilized components lead to a high relative value of information; measurement noise and the Type-I error should be controlled and be as small as possible. An optimal sensor employment with highest relative value of information is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies?before implementation?for similar bridges and to optimize the damage detection system settings and sensor configuration for minimum expected costs and risks

  • Determination of structural and damage detection system influencing parameters on the value of information
    SAGE Publications (UK and US), 2020
    Co-Authors: Long Lijia, Döhler Michael, Thöns Sebastian
    Abstract:

    International audienceA method to determine the influencing parameters of a structural and Damage Detection System (DDS) is proposed based on the Value of Information (VoI) analysis. The VoI analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of DDS for the structural integrity management during service life. First the influencing parameters of the structural system, such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the influencing parameters on the DDS performance, including number of sensors, sensor locations, measurement noise and the Type I error are investigated. The pre-posterior probabilistic model is computed utilizing the Bayes' theorem to update the prior system model with the damage indication information. Finally, the value of DDS is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences, as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt Truss bridge girder is carried out to validate the method. The analysis shows that the deterioration rate is the most sensitive parameter on the effect of relative VoI over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative VoI; only specific sensor locations near the highest utilized components lead to a high relative VoI; measurement noise and the Type I error should be controlled and be as small as possible. An optimal sensor employment with highest relative VoI is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies-before implementation-for similar bridges and to optimize the DDS settings and sensor configuration for minimum expected costs and risks

  • The effects of deterioration models on the value of damage detection information
    HAL CCSD, 2018
    Co-Authors: Long Lijia, Thöns Sebastian, Döhler Michael
    Abstract:

    International audienceThis paper addresses the effects of the deterioration on the value of damage detection information. The quantification of the value of damage detection information for deteriorated structures is based on Bayesian pre-posterior decision analysis, comprising structural system performance models, consequence, benefit and costs models and damage detection information models throughout the service life of a structural system. The value of damage detection information accounts for the relevance and precision of the information to ensure the structural integrity and to reduce the potential structural system risks and expected costs throughout the ser-vice life before implementing damage detection system. With the developed approach, the value of damage detection information for a statically determinate Pratt Truss bridge girder subjected to different deterioration models is calculated. The analysis shows the impact of the deterioration model parameters on the value of damage detection information. The results can be used to develop optimal maintenance strategies before implementation of the damage detection system

  • The effects of SHM system parameters on the value of damage detection information
    HAL CCSD, 2018
    Co-Authors: Long Lijia, Thöns Sebastian, Döhler Michael
    Abstract:

    International audienceThis paper addresses how the value of damage detection information depends on key parameters of the Structural Health Monitoring (SHM) system including number of sensors and sensor locations. The Damage Detection System (DDS) provides the information by comparing ambient vibration measurements of a (healthy) reference state with measurements of the current structural system. The performance of DDS method depends on the physical measurement properties such as the number of sensors, sensor positions, measuring length and sensor type, measurement noise, ambient excitation and sampling frequency, as well as on the data processing algorithm including the chosen type I error for the indication threshold. The quantification of the value of information (VoI) is an expected utility based Bayesian decision analysis method for quantifying the difference of the expected economic benefits with and without information. The (pre-)posterior probability is computed utilizing the Bayesian updating theorem for all possible indications. If changing any key parameters of DDS, the updated probability of system failure given damage detection information will be varied due to different indication of probability of damage, which will result in changes of value of damage detection information. The DDS system is applied in a statically determinate Pratt Truss bridge girder. Through the analysis of the value of information with different SHM system characteristics, the settings of DDS can be optimized for minimum expected costs and risks before implementation

  • Damage Detection and Deteriorating Structural Systems
    HAL CCSD, 2017
    Co-Authors: Long Lijia, Thöns Sebastian, Döhler Michael
    Abstract:

    International audienceThis paper addresses the quantification of the value of damage detection system and algorithm information on the basis of Value of Information (VoI) analysis to enhance the benefit of damage detection information by providing the basis for its optimization before it is performed and implemented. The approach of the quantification the value of damage detection information builds upon the Bayesian decision theory facilitating the utilization of damage detection performance models, which describe the information and its precision on structural system level, facilitating actions to ensure the structural integrity and facilitating to describe the structural system performance and its function-ality throughout the service life. The structural system performance is described with its functionality, its deterioration and its behavior under extreme loading. The structural system reliability given the damage detection information is determined utilizing Bayesian updating. The damage detection performance is described with the probability of indication for different component and system damage states taking into account type 1 and type 2 errors. The value of damage detection information is then calculated as the difference between the expected benefits and risks utilizing the damage detection information or not. With an application example of the developed approach based on a deteriorating Pratt Truss system, the value of damage detection information is determined , demonstrating the potential of risk reduction and expected cost reduction

Wibowo Ari - One of the best experts on this subject based on the ideXlab platform.

  • PENGARUH VARIASI CAMBER TERHADAP PERILAKU JEMBATAN RANGKA BAJA
    Jurusan Teknik Sipil Fakultas Teknik Universitas Brawijaya, 2014
    Co-Authors: Prayogi Arie, Zacoeb Achfas, Wibowo Ari
    Abstract:

    Camber merupakan ruang terbuka  yang terdapat pada bawah jembatan yang memanfaatkan lengkungan lantai kendaraan jembatan. Camber biasa disebut dengan anti lendutan karena camber dibuat untuk melawan lendutan yang mungkin terjadi akibat beban yang bekerja. Jika terjadi lendutan maka tidak akan melebihi garis netral jembatan sehingga masih memungkinkan ruang kosong untuk kegiatan di bawah jembatan. Pada penelitian ini menggunakan analisis software analisa struktur dengan menggunakan 12 model jembatan yang terdiri dari empat variasi tipe rangka dan tiga variasi ketinggian camber. Empat variasi tipe rangka itu adalah Pratt Truss, Howe Truss, Warren Truss dan K-Truss dan tiga variasi camber itu adalah 0, 0,07 dan 0,14 meter atau 0%, 1,17% dan 2,33%. Analisa pembebanan menggunakan beban terpusat dengan penambahan beban setiap 200 kg sampai masing-masing model jembatan mengalami lendutan 1/800l atau 7,5 mm. Tujuannya untuk mengetahui tipe rangka manakah yang paling efektif ditinjau dari beban maksimum yang mampu ditahan, lendutan yang terjadi pada beban tertentu dan nilai gaya batangnya terhadap berat sendiri jembatannya. Hasil analisis menunjukan bahwa semua model jembatan cenderung mengalami penurunan efektifitas akibat perlakuan pemberian camber. Beban maksimum yang mampu ditahan terbesar yaitu pada model K-Truss camber 0% dengan beban 3010,79 kg sedangkan model yang terlemah yaitu Howe Truss camber 2,33% dengan beban 2163,12 kg. Lendutan struktur terkecil pada saat beban 2000 kg terjadi pada model K-Truss camber 0% sebesar 5,07 mm dan lendutan terbesar terjadi pada model Howe Truss camber 2,33% sebesar 6,96 mm. Jadi camber dipakai bukan untuk mengurangi lendutan melainkan untuk memberi ruang kosong di bawah jembatan. Kata kunci: beban maksimum, efektifitas, lendutan, tipe jembatan rangka, variasi cambe