Relevant bibliographies by topics / Structural

Academic literature on the topic 'Structural'

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Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Structural"

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Yamasaki, Satoshi, and Kazuhiko Fukui. "2P266 Tertiary structure prediction of RNA-RNA complex structures using secondary structure information(22A. Bioinformatics: Structural genomics,Poster)." Seibutsu Butsuri 53, supplement1-2 (2013): S203. http://dx.doi.org/10.2142/biophys.53.s203_1.

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Aftandiliants, Ye G. "Modelling of structure forming in structural steels." Naukovij žurnal «Tehnìka ta energetika» 11, no. 4 (September 10, 2020): 13–22. http://dx.doi.org/10.31548/machenergy2020.04.013.

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The study showed that the influence of alloying elements on the secondary structure formation of the steels containing from 0.19 to 0.37 wt. % carbon; 0.82-1.82 silicon; 0.63-3.03 manganese; 1.01-3.09 chromium; 0.005-0.031 nitrogen; up to 0.25 wt.% vanadium and austenite grain size is determined by their change in the content of vanadium nitride phase in austenite, its alloying and overheating above tac3, and the dispersion of ferrite-pearlite, martensitic and bainitic structures is determined by austenite grain size and thermal kinetic parameters of phase transformations. Analytical dependencies are defined that describe the experimental data with a probability of 95% and an error of 10% to 18%. An analysis results of studying the structure formation of structural steel during tempering after quenching show that the dispersion and uniformity of the distribution of carbide and nitride phases in ferrite is controlled at complete austenite homogenization by diffusion mobility and the solubility limit of carbon and nitrogen in ferrite, and secondary phase quantity in case of the secondary phase presence in austenite more than 0.04 wt. %. Equations was obtained which, with a probability of 95% and an error of 0.7 to 2.6%, describe the real process.
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Elyiğit, Belkıs, and Cevdet Emin Ekinci. "A RESEARCH ON STRUCTURAL AND NON-STRUCTURAL DAMAGES AND DAMAGE ASSESSMENT IN REINFORCED CONCRETE STRUCTURES." NWSA Academic Journals 18, no. 2 (April 25, 2023): 19–42. http://dx.doi.org/10.12739/nwsa.2023.18.2.1a0485.

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HORNUNG, Martin, Takahisa DOBA, Rajat AGARWAL, Mark BUTLER, and Olaf LAMMERSCHOP. "Structural Adhesives for Energy Management and Reinforcement of Body Structures." Journal of The Adhesion Society of Japan 44, no. 7 (2008): 258–63. http://dx.doi.org/10.11618/adhesion.44.258.

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Tamura, Shohei, Yaemi Teramoto, Jiro Katto, and Hiroshi Wako. "1P041 Structural alignment with Delaunay codes characterizing local structures and structural motifs identified by the alignment(1. Protein structure and dynamics (I),Poster Session,Abstract,Meeting Program of EABS & BSJ 2006)." Seibutsu Butsuri 46, supplement2 (2006): S157. http://dx.doi.org/10.2142/biophys.46.s157_1.

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Hafiz, Hiba. "Structural Labor Rights." Michigan Law Review, no. 119.4 (2021): 651. http://dx.doi.org/10.36644/mlr.119.4.structural.

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American labor law was designed to ensure equal bargaining power between workers and employers. But workers’ collective power against increasingly dominant employers has disintegrated. With union density at an abysmal 6.2 percent in the private sector—a level unequaled since the Great Depression— the vast majority of workers depend only on individual negotiations with employers to lift stagnant wages and ensure upward economic mobility. But decentralized, individual bargaining is not enough. Economists and legal scholars increasingly agree that, absent regulation to protect workers’ collective rights, labor markets naturally strengthen employers’ bargaining power over workers. Existing labor and antitrust law have failed to step in, leaving employers free to coordinate and consolidate labor-market power while constraining workers’ ability to do the same. The dissolution of workers’ collective rights has resulted in spiking income inequality: workers have suffered economy-wide wage stagnation and a declining share of the national income for decades. To resolve this crisis, some scholars have advocated for ambitious labor law reforms, like sector-wide bargaining, while others have turned to antitrust law to tackle employer power. While these proposals are vital, they overlook an existing opportunity already contained in the labor law that would avoid the political and doctrinal obstacles to such large-scale reforms. This Article argues for a “structural” approach to the labor law that revives and modernizes its equal bargaining power purpose through deploying innovative social scientific analysis. A “structural” approach is one that takes into account workers’ bargaining power relative to employers in determining the scope of substantive labor rights and in resolving disputes. Because employers’ current buyer power strengthens their ability to indefinitely hold out on worker demands in the employment bargain, the “structural” approach seeks to deploy social scientific tools to tailor the labor law’s provisions so that they resituate workers to a bargaining position from which they could equally hold out. This Article makes three key contributions. First, it documents the dispersion and misalignment of workers’ collective rights under current labor law, detailing the historical narrowing of workers’ collective rights to limited tactics by a small set of workers against highly protected individual enterprises and the concomitant rise of employer power (Part I). Second, it introduces and schematizes the wealth of social scientific literature relevant for evaluating the relative bargaining power of employers and employees (Part II). And finally, it offers concrete proposals for how to apply these social scientific tools and insights to three areas of the National Labor Relation Board’s adjudication and regulatory authority: the determination of “employer”/”employee” status, the determination of employees’ substantive rights under section 7 of the National Labor Relations Act (NLRA), and the determination of what counts as sanctionable unfair labor practices under section 8 of the NLRA (Part III).
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Bhak, Jong. "S3c2-2 Structural Interactomics : Omics approach in protein structural bioinformatics(S3-c2: "Structural Bioinformatics: Molecular structures as the basis of understanding protein network systems",Symposia,Abstract,Meeting Program of EABS & BSJ 2006)." Seibutsu Butsuri 46, supplement2 (2006): S141. http://dx.doi.org/10.2142/biophys.46.s141_1.

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Grigorenko, G. M., V. D. Poznyakov, T. A. Zuber, and V. A. Kostin. "Peculiarities of formation of structure in welded joints of microalloyed structural steel S460M." Paton Welding Journal 2017, no. 10 (October 28, 2017): 2–8. http://dx.doi.org/10.15407/tpwj2017.10.01.

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Vinay, Potharaboyena, and Kurimilla Srilaxmi. "Structural Analysis and Design of Structural Elements of A Building." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 1132–51. http://dx.doi.org/10.31142/ijtsrd11237.

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Ghodake, Prasad, and S. R. Suryawanshi. "Structural Health Monitoring." Journal of Advances and Scholarly Researches in Allied Education 15, no. 2 (April 1, 2018): 360–63. http://dx.doi.org/10.29070/15/56847.

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Dissertations / Theses on the topic "Structural"

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Carpentier, Mathilde. "Méthodes de détection des similarités structurales : caractérisation des motifs conservés dans les familles de structures pour l' annotation des génomes." Paris 6, 2005. http://www.theses.fr/2005PA066571.

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Mahajan, Swapnil. "Applications d'un alphabet structural pour l'analyse, la prédiction et la reconnaissance des repliements des protéines." Thesis, La Réunion, 2013. http://www.theses.fr/2013LARE0032.

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Les blocs protéiques (BP) constituent un alphabet structural qui permettent une bonne approximation du squelette carbonnée des protéines et la compression de l'information 3D en 1D. Leur utilisation a permis d'appréhender sous un nouvel angle la structure des protéines. Cette thèse explore de nouvelles applications des BP pour l'analyse des structures des protéines, leur prédiction et la reconnaissance de leurs repliements. Dans un premier temps, nous utilisons les BP pour une caractérisation fine des régions variables dans les alignements structuraux de protéines homologues. Ces régions peuvent néanmoins présenter des similarités importantes en terme de conformation. Leur caractérisation a permis de les distinguer des régions dont les conformations sont différentes. Nous montrons aussi que les variations intrinsèques de certaines régions comme les boucles au sein d’une protéine ne sont pas corrélées aux différences de conformation observées dans les régions équivalentes entre protéines homologues. Dans une deuxième partie, nous analysons la relation séquence-structure à l'aide de BP par le biais d'une base de données de pentapeptides issus des structures des protéines. Celle-ci a servi de base pour la mise en place d'outils pour la prédiction du squelette carbonnée des protéines (PB-kPRED) et de sa plasticité (PB-SVindex). Nous exposons comment ces prédictions permettent la reconnaissance du repliement des protéines avec un certain succès et l'identification de probables points chauds structuraux et fonctionnels. En dernière partie, nous présentons un nouvel algorithme (FoRSA) pour la reconnaissance du repliement des protéines à l'aide des BP. Cet algorithme s'appuie sur le calcul de la probabilité conditionnelle qu'une séquence adopte un repliement donné et a été testé avec succès sur des protéines tirées de CASP10. Nous montrons que FoRSA peut être utilisé pour l'annotation structurale rapide de génomes entiers
Analysis of protein structures using structural alphabets has provided new insights into protein function and evolution. We have used a structural alphabet called proteins blocks (PBs) which efficiently approximates protein backbone and allows abstraction of 3D protein structures into 1D PB sequences. This thesis describes applications of PBs for protein structure analysis, prediction and fold recognition. First, PBs were used to provide a refined view of structurally variable regions (SVRs) in homologous proteins in terms of conformationally similar and dissimilar SVRs in which were compiled a database of structural alignments (DoSA). We also show that the inherent conformational variations in loop regions are not correlated to corresponding conformational differences in their homologues. Second, to further analyze sequence-structure relationships in terms of PBs and other structural features, we have set up a database of pentapeptides derived from protein structures. This served as a basis for the knowledge-based prediction of local protein structure in terms of PB sequences (PB-kPRED) and of local structure plasticity (PB-SVindex). We demonstrate the successful applications of PB-kPRED for fold recognition and explored possible identification of structural and functional hotspots in proteins using PB-SVindex. Finally, an algorithm for fold recognition using a structural alphabet (FoRSA) based on calculation of conditional probability of sequence-structure compatibility was developed. This new threading method has been successfully benchmarked on a test dataset from CASP10 targets. We further demonstrate the application of FoRSA for fast structural annotations of genomes
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Keyhani, Ali. "A Study On The Predictive Optimal Active Control Of Civil Engineering Structures." Thesis, Indian Institute of Science, 2000. https://etd.iisc.ac.in/handle/2005/223.

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Uncertainty involved in the safe and comfort design of the structures is a major concern of civil engineers. Traditionally, the uncertainty has been overcome by utilizing various and relatively large safety factors for loads and structural properties. As a result in conventional design of for example tall buildings, the designed structural elements have unnecessary dimensions that sometimes are more than double of the ones needed to resist normal loads. On the other hand the requirements for strength and safety and comfort can be conflicting. Consequently, an alternative approach for design of the structures may be of great interest in design of safe and comfort structures that also offers economical advantages. Recently, there has been growing interest among the researchers in the concept of structural control as an alternative or complementary approach to the existing approaches of structural design. A few buildings have been designed and built based on this concept. The concept is to utilize a device for applying a force (known as control force) to encounter the effects of disturbing forces like earthquake force. However, the concept still has not found its rightful place among the practical engineers and more research is needed on the subject. One of the main problems in structural control is to find a proper algorithm for determining the optimum control force that should be applied to the structure. The investigation reported in this thesis is concerned with the application of active control to civil engineering structures. From the literature on control theory. (Particularly literature on the control of civil engineering structures) problems faced in application of control theory were identified and classified into two categories: 1) problems common to control of all dynamical systems, and 2) problems which are specially important in control of civil engineering structures. It was concluded that while many control algorithms are suitable for control of dynamical systems, considering the special problems in controlling civil structures and considering the unique future of structural control, many otherwise useful control algorithms face practical problems in application to civil structures. Consequently a set of criteria were set for judging the suitability of the control algorithms for use in control of civil engineering structures. Various types of existing control algorithms were investigated and finally it was concluded that predictive optimal control algorithms possess good characteristics for purpose of control of civil engineering structures. Among predictive control algorithms, those that use ARMA stochastic models for predicting the ground acceleration are better fitted to the structural control environment because all the past measured excitation is used to estimate the trends of the excitation for making qualified guesses about its coming values. However, existing ARMA based predictive algorithms are devised specially for earthquake and require on-line measurement of the external disturbing load which is not possible for dynamic loads like wind or blast. So, the algorithms are not suitable for tall buildings that experience both earthquake and wind loads during their life. Consequently, it was decided to establish a new closed loop predictive optimal control based on ARMA models as the first phase of the study. In this phase it was initially established that ARMA models are capable of predicting response of a linear SDOF system to the earthquake excitation a few steps ahead. The results of the predictions encouraged a search for finding a new closed loop optimal predictive control algorithm for linear SDOF structures based on prediction of the response by ARMA models. The second part of phase I, was devoted to developing and testing the proposed algorithm The new developed algorithm is different from other ARMA based optimal controls since it uses ARMA models for prediction of the structure response while existing algorithms predict the input excitation. Modeling the structure response as an AR or ARMA stochastic process is an effective mean for prediction of the structure response while avoiding measurement of the input excitation. ARMA models used in the algorithm enables it to avoid or reduce the time delay effect by predicting the structure response a few steps ahead. Being a closed loop control, the algorithm is suitable for all structural control conditions and can be used in a single control mechanism for vibration control of tall buildings against wind, earthquake or other random dynamic loads. Consequently the standby time is less than that for existing ARMA based algorithms devised only for earthquakes. This makes the control mechanism more reliable. The proposed algorithm utilizes and combines two different mathematical models. First model is an ARMA model representing the environment and the structure as a single system subjected to the unknown random excitation and the second model is a linear SDOF system which represents the structure subjected to a known past history of the applied control force only. The principle of superposition is then used to combine the results of these two models to predict the total response of the structure as a function of the control force. By using the predicted responses, the minimization of the performance index with respect to the control force is carried out for finding the optimal control force. As phase II, the proposed predictive control algorithm was extended to structures that are more complicated than linear SDOF structures. Initially, the algorithm was extended to linear MDOF structures. Although, the development of the algorithm for MDOF structures was relatively straightforward, during testing of the algorithm, it was found that prediction of the response by ARMA models can not be done as was done for SDOF case. In the SDOF case each of the two components of the state vector (i.e. displacement and velocity) was treated separately as an ARMA stochastic process. However, applying the same approach to each component of the state vector of a MDOF structure did not yield satisfactory results in prediction of the response. Considering the whole state vector as a multi-variable ARMA stochastic vector process yielded the desired results in predicting the response a few steps ahead. In the second part of this phase, the algorithm was extended to non-linear MDOF structures. Since the algorithm had been developed based on the principle of superposition, it was not possible to directly extend the algorithm to non-linear systems. Instead, some generalized response was defined. Then credibility of the ARMA models in predicting the generalized response was verified. Based on this credibility, the algorithm was extended for non-linear MDOF structures. Also in phase II, the stability of a controlled MDOF structure was proved. Both internal and external stability of the system were described and verified. In phase III, some problems of special interest, i.e. soil-structure interaction and control time delay, were investigated and compensated for in the framework of the developed predictive optimal control. In first part of phase III soil-structure interaction was studied. The half-space solution of the SSI effect leads to a frequency dependent representation of the structure-footing system, which is not fit for control purpose. Consequently an equivalent frequency independent system was proposed and defined as a system whose frequency response is equal to the original structure -footing system in the mean squares sense. This equivalent frequency independent system then was used in the control algorithm. In the second part of this phase, an analytical approach was used to tackle the time delay phenomenon in the context of the predictive algorithm described in previous chapters. A generalized performance index was defined considering time delay. Minimization of the generalized performance index resulted into a modified version of the algorithm in which time delay is compensated explicitly. Unlike the time delay compensation technique used in the previous phases of this investigation, which restricts time delay to be an integer multiplier of the sampling period, the modified algorithm allows time delay to be any non-negative number. However, the two approaches produce the same results if time delay is an integer multiplier of the sampling period. For evaluating the proposed algorithm and comparing it with other algorithms, several numerical simulations were carried during the research by using MATLAB and its toolboxes. A few interesting results of these simulations are enumerated below: ARM A models are able to predict the response of both linear and non-linear structures to random inputs such as earthquakes. The proposed predictive optimal control based on ARMA models has produced better results in the context of reducing velocity, displacement, total energy and operational cost compared to classic optimal control. Proposed active control algorithm is very effective in increasing safety and comfort. Its performance is not affected much by errors in the estimation of system parameters (e.g. damping). The effect of soil-structure interaction on the response to control force is considerable. Ignoring SSI will cause a significant change in the magnitude of the frequency response and a shift in the frequencies of the maximum response (resonant frequencies). Compensating the time delay effect by the modified version of the proposed algorithm will improve the performance of the control system in achieving the control goal and reduction of the structural response.
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4

Keyhani, Ali. "A Study On The Predictive Optimal Active Control Of Civil Engineering Structures." Thesis, Indian Institute of Science, 2000. http://hdl.handle.net/2005/223.

Full text
Abstract:
Uncertainty involved in the safe and comfort design of the structures is a major concern of civil engineers. Traditionally, the uncertainty has been overcome by utilizing various and relatively large safety factors for loads and structural properties. As a result in conventional design of for example tall buildings, the designed structural elements have unnecessary dimensions that sometimes are more than double of the ones needed to resist normal loads. On the other hand the requirements for strength and safety and comfort can be conflicting. Consequently, an alternative approach for design of the structures may be of great interest in design of safe and comfort structures that also offers economical advantages. Recently, there has been growing interest among the researchers in the concept of structural control as an alternative or complementary approach to the existing approaches of structural design. A few buildings have been designed and built based on this concept. The concept is to utilize a device for applying a force (known as control force) to encounter the effects of disturbing forces like earthquake force. However, the concept still has not found its rightful place among the practical engineers and more research is needed on the subject. One of the main problems in structural control is to find a proper algorithm for determining the optimum control force that should be applied to the structure. The investigation reported in this thesis is concerned with the application of active control to civil engineering structures. From the literature on control theory. (Particularly literature on the control of civil engineering structures) problems faced in application of control theory were identified and classified into two categories: 1) problems common to control of all dynamical systems, and 2) problems which are specially important in control of civil engineering structures. It was concluded that while many control algorithms are suitable for control of dynamical systems, considering the special problems in controlling civil structures and considering the unique future of structural control, many otherwise useful control algorithms face practical problems in application to civil structures. Consequently a set of criteria were set for judging the suitability of the control algorithms for use in control of civil engineering structures. Various types of existing control algorithms were investigated and finally it was concluded that predictive optimal control algorithms possess good characteristics for purpose of control of civil engineering structures. Among predictive control algorithms, those that use ARMA stochastic models for predicting the ground acceleration are better fitted to the structural control environment because all the past measured excitation is used to estimate the trends of the excitation for making qualified guesses about its coming values. However, existing ARMA based predictive algorithms are devised specially for earthquake and require on-line measurement of the external disturbing load which is not possible for dynamic loads like wind or blast. So, the algorithms are not suitable for tall buildings that experience both earthquake and wind loads during their life. Consequently, it was decided to establish a new closed loop predictive optimal control based on ARMA models as the first phase of the study. In this phase it was initially established that ARMA models are capable of predicting response of a linear SDOF system to the earthquake excitation a few steps ahead. The results of the predictions encouraged a search for finding a new closed loop optimal predictive control algorithm for linear SDOF structures based on prediction of the response by ARMA models. The second part of phase I, was devoted to developing and testing the proposed algorithm The new developed algorithm is different from other ARMA based optimal controls since it uses ARMA models for prediction of the structure response while existing algorithms predict the input excitation. Modeling the structure response as an AR or ARMA stochastic process is an effective mean for prediction of the structure response while avoiding measurement of the input excitation. ARMA models used in the algorithm enables it to avoid or reduce the time delay effect by predicting the structure response a few steps ahead. Being a closed loop control, the algorithm is suitable for all structural control conditions and can be used in a single control mechanism for vibration control of tall buildings against wind, earthquake or other random dynamic loads. Consequently the standby time is less than that for existing ARMA based algorithms devised only for earthquakes. This makes the control mechanism more reliable. The proposed algorithm utilizes and combines two different mathematical models. First model is an ARMA model representing the environment and the structure as a single system subjected to the unknown random excitation and the second model is a linear SDOF system which represents the structure subjected to a known past history of the applied control force only. The principle of superposition is then used to combine the results of these two models to predict the total response of the structure as a function of the control force. By using the predicted responses, the minimization of the performance index with respect to the control force is carried out for finding the optimal control force. As phase II, the proposed predictive control algorithm was extended to structures that are more complicated than linear SDOF structures. Initially, the algorithm was extended to linear MDOF structures. Although, the development of the algorithm for MDOF structures was relatively straightforward, during testing of the algorithm, it was found that prediction of the response by ARMA models can not be done as was done for SDOF case. In the SDOF case each of the two components of the state vector (i.e. displacement and velocity) was treated separately as an ARMA stochastic process. However, applying the same approach to each component of the state vector of a MDOF structure did not yield satisfactory results in prediction of the response. Considering the whole state vector as a multi-variable ARMA stochastic vector process yielded the desired results in predicting the response a few steps ahead. In the second part of this phase, the algorithm was extended to non-linear MDOF structures. Since the algorithm had been developed based on the principle of superposition, it was not possible to directly extend the algorithm to non-linear systems. Instead, some generalized response was defined. Then credibility of the ARMA models in predicting the generalized response was verified. Based on this credibility, the algorithm was extended for non-linear MDOF structures. Also in phase II, the stability of a controlled MDOF structure was proved. Both internal and external stability of the system were described and verified. In phase III, some problems of special interest, i.e. soil-structure interaction and control time delay, were investigated and compensated for in the framework of the developed predictive optimal control. In first part of phase III soil-structure interaction was studied. The half-space solution of the SSI effect leads to a frequency dependent representation of the structure-footing system, which is not fit for control purpose. Consequently an equivalent frequency independent system was proposed and defined as a system whose frequency response is equal to the original structure -footing system in the mean squares sense. This equivalent frequency independent system then was used in the control algorithm. In the second part of this phase, an analytical approach was used to tackle the time delay phenomenon in the context of the predictive algorithm described in previous chapters. A generalized performance index was defined considering time delay. Minimization of the generalized performance index resulted into a modified version of the algorithm in which time delay is compensated explicitly. Unlike the time delay compensation technique used in the previous phases of this investigation, which restricts time delay to be an integer multiplier of the sampling period, the modified algorithm allows time delay to be any non-negative number. However, the two approaches produce the same results if time delay is an integer multiplier of the sampling period. For evaluating the proposed algorithm and comparing it with other algorithms, several numerical simulations were carried during the research by using MATLAB and its toolboxes. A few interesting results of these simulations are enumerated below: ARM A models are able to predict the response of both linear and non-linear structures to random inputs such as earthquakes. The proposed predictive optimal control based on ARMA models has produced better results in the context of reducing velocity, displacement, total energy and operational cost compared to classic optimal control. Proposed active control algorithm is very effective in increasing safety and comfort. Its performance is not affected much by errors in the estimation of system parameters (e.g. damping). The effect of soil-structure interaction on the response to control force is considerable. Ignoring SSI will cause a significant change in the magnitude of the frequency response and a shift in the frequencies of the maximum response (resonant frequencies). Compensating the time delay effect by the modified version of the proposed algorithm will improve the performance of the control system in achieving the control goal and reduction of the structural response.
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5

Peters, David W. "Design of diffractive optical elements through low-dimensional optimization." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/54614.

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The simulation of diffractive optical structures allows for the efficient testing of a large number of structures without having to actually fabricate these devices. Various forms of analysis of these structures have been done through computer programs in the past. However, programs that can actually design a structure to perform a given task are very limited in scope. Optimization of a structure can be a task that is very processor time intensive, particularly if the optimization space has many dimensions. This thesis describes the creation of a computer program that is able to find an optimal structure while maintaining a low-dimensional search space, thus greatly reducing the processor time required to find the solution. The program can design the optimal structure for a wide variety of planar optical devices that conform to the weakly-guiding approximation with an efficient code that incorporates the low-dimensional search space concept. This work is the first use of an electromagnetic field solver inside of an optimization loop for the design of an optimized diffractive-optic structure.
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Edrees, Tarek. "Structural Identification of Civil Engineering Structures." Licentiate thesis, Luleå tekniska universitet, Byggkonstruktion och -produktion, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-26719.

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The assumptions encountered during the analysis and design of civil engineering structures lead to a difference in the structural behavior between calculations based models and real structures. Moreover, the recent approach in civil engineering nowadays is to rely on the performance-based design approaches, which give more importance for durability, serviceability limit states, and maintenance.Structural identification (St-Id) approach was utilized to bridge the gap between the real structure and the model. The St-Id procedure can be utilized to evaluate the structures health, damage detection, and efficiency. Despite the enormous developments in parametric time-domain identification methods, their relative merits and performance as correlated to the vibrating structures are still incomplete due to the lack of comparative studies under various test conditions and the lack of extended applications and verification of these methods with real-life data.This licentiate thesis focuses on the applications of the parametric models and non-parametric models of the System Identification approach to assist in a better understanding of their potentials, while proposing a novel strategy by combining this approach with the utilization of the Singular Value Decomposition (SVD) and the Complex Mode Indicator Function (CMIF) curves based techniques in the damage detection of structures.In this work, the problems of identification of the vertical frequencies of the top storey in a multi-storey¸ building prefabricated from reinforced concrete in Stockholm, and the existence of damage and damage locations for a bench mark steel frame are investigated. Moreover, the non-parametric structural identification approach to investigate the amount of variations in the modal characteristics (frequency, damping, and modes shapes) for a railway steel bridge will be presented.
Godkänd; 2014; 20141023 (taredr); Nedanstående person kommer att hålla licentiatseminarium för avläggande av teknologie licentiatexamen. Namn: Tarek Edrees Saaed Ämne: Konstruktionsteknik/Structural Engineering Uppsats: Structural Identification of Civil Engineering Structures Examinator: Professor Jan-Erik Jonasson, Institutionen för samhällsbyggnad och naturresurser, Luleå tekniska universitet Diskutant: Forskare Andreas Andersson, Brobyggnad inklusive Stålbyggnad, Kungliga Tekniska Högskolan Tid: Torsdag den 20 november 2014 kl 10:00 Plats: F1031, Luleå tekniska universitet
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BABAEI, IMAN. "Structural Testing of Composite Crash Structures." Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2910072.

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Rasmussen, Kim J. R. "Stability of thin-walled structural members and systems." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/18194.

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This DEng thesis consists of 83 articles containing research material on the stability of thin-walled structural members and systems with emphasis on metal structures. Metal structures are used widely in the construction industry. They include structural members and frames made from rolled and fabricated steel, cold-formed steel, stainless steel and aluminium. Common to these products is the desire to minimise the cross-sectional area to reduce weight and cost. Structural cross-sections are therefore thin-walled and prone to buckling, and an overriding consideration in the design of metal structures is to account for buckling in determining the strength of sections, members and frames. Specifically, the thesis is concerned with determining the reduction in buckling capacity and strength of structural members and frames caused by cross-sectional buckling and material softening. The thesis presents research under the headings Stainless Steel Structures - Hollow Sections, covering tubular columns, beams and welded connections; Stainless Steel Structures - Open Sections, addressing the effect of distortional buckling and interaction buckling on the design of stainless steel columns and beams; Analysis of Locally Buckled Members and Frames, describing a theory to determine the buckling loads of locally and/or distortionally buckled members and frames; Behaviour and Design of Members and Sections Composed Solely or Predominantly from Unstiffened Elements, outlining analytical, numerical and experimental research to advance the understanding of the behaviour and design of singly symmetric cross-sections made up entirely or predominantly from plate elements, including angle sections, T-sections and plain channel sections; Cold-formed Steel Structural Systems, describing numerical and experimental investigations of steel storage racks including selective and drive-in racking systems; and System-based Design of Steel Structures, developing a general framework for designing steel structural framing systems by advanced analysis, termed the Direct Design Method. The thesis also highlights the implementation of the research outcomes in national and international specifications for the design of steel, cold-formed steel and stainless steel structures.
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9

Irakarama, Modeste. "Towards Reducing Structural Interpretation Uncertainties Using Seismic Data." Electronic Thesis or Diss., Université de Lorraine, 2019. http://www.theses.fr/2019LORR0060.

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Les modèles géologiques sont couramment utilisés pour estimer les ressources souterraines, pour faire des simulations numériques, et pour évaluer les risques naturels ; il est donc important que les modèles géologiques représentent la géométrie des objets géologiques de façon précise. La première étape pour construire un modèle géologique consiste souvent à interpréter des surfaces structurales, telles que les failles et horizons, à partir d'une image sismique ; les objets géologiques identifiés sont ensuite utilisés pour construire le modèle géologique par des méthodes d'interpolation. Les modèles géologiques construits de cette façon héritent donc les incertitudes d'interprétation car une image sismique peut souvent supporter plusieurs interprétations structurales. Dans ce manuscrit, j'étudie le problème de réduire les incertitudes d'interprétation à l'aide des données sismiques. Particulièrement, j'étudie le problème de déterminer, à l'aide des données sismiques, quels modèles sont plus probables que d'autres dans un ensemble des modèles géologiques cohérents. Ce problème sera connu par la suite comme "le problème d'évaluation des modèles géologiques par données sismiques". J'introduis et formalise ce problème. Je propose de le résoudre par génération des données sismiques synthétiques pour chaque interprétation structurale dans un premier temps, ensuite d'utiliser ces données synthétiques pour calculer la fonction-objectif pour chaque interprétation ; cela permet de classer les différentes interprétations structurales. La difficulté majeure d'évaluer les modèles structuraux à l'aide des données sismiques consiste à proposer des fonctions-objectifs adéquates. Je propose un ensemble de conditions qui doivent être satisfaites par la fonction-objectif pour une évaluation réussie des modèles structuraux à l'aide des données sismiques. Ces conditions imposées à la fonction-objectif peuvent, en principe, être satisfaites en utilisant les données sismiques de surface (« surface seismic data »). Cependant, en pratique il reste tout de même difficile de proposer et de calculer des fonctions-objectifs qui satisfassent ces conditions. Je termine le manuscrit en illustrant les difficultés rencontrées en pratique lorsque nous cherchons à évaluer les interprétations structurales à l'aide des données sismiques de surface. Je propose une fonction-objectif générale faite de deux composants principaux : (1) un opérateur de résidus qui calcule les résidus des données, et (2) un opérateur de projection qui projette les résidus de données depuis l'espace de données vers l'espace physique (le sous-sol). Cette fonction-objectif est donc localisée dans l'espace car elle génère des valeurs en fonction de l'espace. Cependant, je ne suis toujours pas en mesure de proposer une implémentation pratique de cette fonction-objectif qui satisfasse les conditions imposées pour une évaluation réussie des interprétations structurales ; cela reste un sujet de recherche
Subsurface structural models are routinely used for resource estimation, numerical simulations, and risk management; it is therefore important that subsurface models represent the geometry of geological objects accurately. The first step in building a subsurface model is usually to interpret structural features, such as faults and horizons, from a seismic image; the identified structural features are then used to build a subsurface model using interpolation methods. Subsurface models built this way therefore inherit interpretation uncertainties since a single seismic image often supports multiple structural interpretations. In this manuscript, I study the problem of reducing interpretation uncertainties using seismic data. In particular, I study the problem of using seismic data to determine which structural models are more likely than others in an ensemble of geologically plausible structural models. I refer to this problem as "appraising structural models using seismic data". I introduce and formalize the problem of appraising structural interpretations using seismic data. I propose to solve the problem by generating synthetic data for each structural interpretation and then to compute misfit values for each interpretation; this allows us to rank the different structural interpretations. The main challenge of appraising structural models using seismic data is to propose appropriate data misfit functions. I derive a set of conditions that have to be satisfied by the data misfit function for a successful appraisal of structural models. I argue that since it is not possible to satisfy these conditions using vertical seismic profile (VSP) data, it is not possible to appraise structural interpretations using VSP data in the most general case. The conditions imposed on the data misfit function can in principle be satisfied for surface seismic data. In practice, however, it remains a challenge to propose and compute data misfit functions that satisfy those conditions. I conclude the manuscript by highlighting practical issues of appraising structural interpretations using surface seismic data. I propose a general data misfit function that is made of two main components: (1) a residual operator that computes data residuals, and (2) a projection operator that projects the data residuals from the data-space into the image-domain. This misfit function is therefore localized in space, as it outputs data misfit values in the image-domain. However, I am still unable to propose a practical implementation of this misfit function that satisfies the conditions imposed for a successful appraisal of structural interpretations; this is a subject for further research
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10

Irakarama, Modeste. "Towards Reducing Structural Interpretation Uncertainties Using Seismic Data." Thesis, Université de Lorraine, 2019. http://www.theses.fr/2019LORR0060/document.

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Les modèles géologiques sont couramment utilisés pour estimer les ressources souterraines, pour faire des simulations numériques, et pour évaluer les risques naturels ; il est donc important que les modèles géologiques représentent la géométrie des objets géologiques de façon précise. La première étape pour construire un modèle géologique consiste souvent à interpréter des surfaces structurales, telles que les failles et horizons, à partir d'une image sismique ; les objets géologiques identifiés sont ensuite utilisés pour construire le modèle géologique par des méthodes d'interpolation. Les modèles géologiques construits de cette façon héritent donc les incertitudes d'interprétation car une image sismique peut souvent supporter plusieurs interprétations structurales. Dans ce manuscrit, j'étudie le problème de réduire les incertitudes d'interprétation à l'aide des données sismiques. Particulièrement, j'étudie le problème de déterminer, à l'aide des données sismiques, quels modèles sont plus probables que d'autres dans un ensemble des modèles géologiques cohérents. Ce problème sera connu par la suite comme "le problème d'évaluation des modèles géologiques par données sismiques". J'introduis et formalise ce problème. Je propose de le résoudre par génération des données sismiques synthétiques pour chaque interprétation structurale dans un premier temps, ensuite d'utiliser ces données synthétiques pour calculer la fonction-objectif pour chaque interprétation ; cela permet de classer les différentes interprétations structurales. La difficulté majeure d'évaluer les modèles structuraux à l'aide des données sismiques consiste à proposer des fonctions-objectifs adéquates. Je propose un ensemble de conditions qui doivent être satisfaites par la fonction-objectif pour une évaluation réussie des modèles structuraux à l'aide des données sismiques. Ces conditions imposées à la fonction-objectif peuvent, en principe, être satisfaites en utilisant les données sismiques de surface (« surface seismic data »). Cependant, en pratique il reste tout de même difficile de proposer et de calculer des fonctions-objectifs qui satisfassent ces conditions. Je termine le manuscrit en illustrant les difficultés rencontrées en pratique lorsque nous cherchons à évaluer les interprétations structurales à l'aide des données sismiques de surface. Je propose une fonction-objectif générale faite de deux composants principaux : (1) un opérateur de résidus qui calcule les résidus des données, et (2) un opérateur de projection qui projette les résidus de données depuis l'espace de données vers l'espace physique (le sous-sol). Cette fonction-objectif est donc localisée dans l'espace car elle génère des valeurs en fonction de l'espace. Cependant, je ne suis toujours pas en mesure de proposer une implémentation pratique de cette fonction-objectif qui satisfasse les conditions imposées pour une évaluation réussie des interprétations structurales ; cela reste un sujet de recherche
Subsurface structural models are routinely used for resource estimation, numerical simulations, and risk management; it is therefore important that subsurface models represent the geometry of geological objects accurately. The first step in building a subsurface model is usually to interpret structural features, such as faults and horizons, from a seismic image; the identified structural features are then used to build a subsurface model using interpolation methods. Subsurface models built this way therefore inherit interpretation uncertainties since a single seismic image often supports multiple structural interpretations. In this manuscript, I study the problem of reducing interpretation uncertainties using seismic data. In particular, I study the problem of using seismic data to determine which structural models are more likely than others in an ensemble of geologically plausible structural models. I refer to this problem as "appraising structural models using seismic data". I introduce and formalize the problem of appraising structural interpretations using seismic data. I propose to solve the problem by generating synthetic data for each structural interpretation and then to compute misfit values for each interpretation; this allows us to rank the different structural interpretations. The main challenge of appraising structural models using seismic data is to propose appropriate data misfit functions. I derive a set of conditions that have to be satisfied by the data misfit function for a successful appraisal of structural models. I argue that since it is not possible to satisfy these conditions using vertical seismic profile (VSP) data, it is not possible to appraise structural interpretations using VSP data in the most general case. The conditions imposed on the data misfit function can in principle be satisfied for surface seismic data. In practice, however, it remains a challenge to propose and compute data misfit functions that satisfy those conditions. I conclude the manuscript by highlighting practical issues of appraising structural interpretations using surface seismic data. I propose a general data misfit function that is made of two main components: (1) a residual operator that computes data residuals, and (2) a projection operator that projects the data residuals from the data-space into the image-domain. This misfit function is therefore localized in space, as it outputs data misfit values in the image-domain. However, I am still unable to propose a practical implementation of this misfit function that satisfies the conditions imposed for a successful appraisal of structural interpretations; this is a subject for further research
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Books on the topic "Structural"

1

American Institute of Aeronautics and Astronautics., ed. Standard space systems: Structures, structural components, and structural assemblies. Reston, VA: American Institute of Aeronautics and Astronautics, 2005.

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Bui, Tinh Quoc, Le Thanh Cuong, and Samir Khatir, eds. Structural Health Monitoring and Engineering Structures. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0945-9.

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Moreira, Pedro M. G. P., Lucas F. M. da Silva, and Paulo M. S. T. de Castro, eds. Structural Connections for Lightweight Metallic Structures. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-18187-0.

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Chamis, C. C. Computational structural mechanics for engine structures. [Washington, DC]: National Aeronautics and Space Administration, 1989.

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M, Silva Lucas F., Castro, Paulo M.S.T., and SpringerLink (Online service), eds. Structural Connections for Lightweight Metallic Structures. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Moore, Fuller. Understanding structures = Introduction to structural systems. Taipei: McGraw Hill, 2000.

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International Association for Shell and Spatial Structures, ed. Structural design of retractable roof structures. Southampton: WIT, 2000.

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Fernández-Villaverde, Jesús. How structural are structural parameters? Cambridge, Mass: National Bureau of Economic Research, 2007.

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Wong, Kevin Kai Fai, 1969-, ed. Structural dynamics for structural engineers. New York: Wiley, 2000.

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Eschenauer, Hans. Applied structural mechanics: Fundamentals of elasticity, load-bearing structures, structural optimization : including exercises. Berlin: Springer, 1997.

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Book chapters on the topic "Structural"

1

Stimpfle, Bernd. "Structural Air — Pneumatic Structures." In Textile Composites and Inflatable Structures II, 233–52. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6856-0_13.

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Bates, Frederick L. "Structure and Structural Analysis." In Sociopolitical Ecology, 49–67. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4899-0251-1_3.

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Lyre, Holger. "Structural Invariants, Structural Kinds, Structural Laws." In Probabilities, Laws, and Structures, 169–81. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-3030-4_12.

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Colciago, Andrea. "Structural Reforms and Endogenous Market Structures." In Structural Reforms, 199–219. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74400-1_9.

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Pedersen, P. Terndrup, and N.-J. Rishøj Nielsen. "Structural Optimization of Ship Structures." In Computer Aided Optimal Design: Structural and Mechanical Systems, 921–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-83051-8_27.

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Oakley, D. J. "Musical structures as structural pedagogy." In Structures and Architecture A Viable Urban Perspective?, 997–1004. London: CRC Press, 2022. http://dx.doi.org/10.1201/9781003023555-119.

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Peou, Sorpong. "Institutional Structure and Structural Challenges." In International Democracy Assistance for Peacebuilding, 21–32. London: Palgrave Macmillan UK, 2007. http://dx.doi.org/10.1057/9780230590809_3.

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Tonkinwise, Cameron. "The Structure of Structural Change." In Routledge Handbook of Sustainable Design, 433–45. Abingdon, Oxon ; New York, NY : Routledge, 2017.: Routledge, 2017. http://dx.doi.org/10.4324/9781315625508-37.

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Quintino, L., R. Miranda, U. Dilthey, D. Iordachescu, M. Banasik, and S. Stano. "Laser Welding of Structural Aluminium." In Structural Connections for Lightweight Metallic Structures, 33–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/8611_2010_46.

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Kanda, Jun. "Safety and Sustainability—the Structural Engineer's Role." In Sustainable Structural Engineering, 1–8. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2015. http://dx.doi.org/10.2749/sed014.001.

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<p>The mission of structural engineering is to design and construct safe structures by making appropriate decisions. At the same time, society also has a strong demand for sustainability, to which structural engineers can contribute through their decisions. Such decisions are necessary at every step of the design, construction, maintenance, and demolition process. The appropriateness depends on people’s expectancy for a structure, which varies according to their cultural background and economic well-being, as well as technological development. Historically, when quantitative information of a design variable was not available, the structural safety was deter-mined by engineers, based mainly on their own experiences. Materials and construction systems simply followed what had been successful in the past.</p>
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Conference papers on the topic "Structural"

1

Downen, Paul, Philip Johnson-Freyd, and Zena M. Ariola. "Structures for structural recursion." In ICFP'15: 20th ACM SIGPLAN International Conference on Functional Programming. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2784731.2784762.

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Khalessi, M. "Design of structural tests for verification of structural reliability." In 35th Structures, Structural Dynamics, and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-1384.

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Yu, Xiaoye, and Tianjian Ji. "Searching Efficient Structural Forms: Evolutionary Structural Optimization Vs Structural Concepts." In The Seventh International Structural Engineering and Construction Conference. Singapore: Research Publishing Services, 2013. http://dx.doi.org/10.3850/978-981-07-5354-2_st-163-487.

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Reich, Gregory, and K. Park. "Structural health monitoring via structural localization." In 39th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1998. http://dx.doi.org/10.2514/6.1998-1892.

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"Structural Health Monitoring (SHM) of Space Structures." In Structural Health Monitoring. Materials Research Forum LLC, 2021. http://dx.doi.org/10.21741/9781644901311-42.

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Abstract. Recent years have seen an increased interest in exploring outer space for space tourism or for unmanned or manned planetary explorations. The captivated interests among various stakeholders to employ advanced technologies to meet the requirements of these missions have necessitated the use of newly developed asset monitoring systems to ensure robustness and mission reliability. Although, Non-Destructive Testing (NDT) methods provide sufficient information about the state of the structure at the time of inspection, the need for continuously monitoring the health of the structure throughout the mission has asserted the use of Structure Health Monitoring (SHM) technologies to increase the levels of safety and thereby, reducing the overall mission costs. However, since the implementation of SHM technologies for space missions can be affected by several factors including, environmental conditions, measurement reliability and unavailability of adequate standards, additional considerations on its employability must be reconsidered. This article demonstrates a structured approach to compare the capabilities of some of the most promising SHM technologies in consideration of these influential factors. Additionally, remarks on the feasibility of employing these SHM technologies and the role they could play in such critical missions would be elaborated.
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Leutenegger, Tobias, Dirk H. Schlums, and Jurg Dual. "Structural testing of fatigued structures." In 1999 Symposium on Smart Structures and Materials, edited by Norman M. Wereley. SPIE, 1999. http://dx.doi.org/10.1117/12.350775.

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PAEZ, THOMAS. "Nonlinear structural system modelling." In 28th Structures, Structural Dynamics and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1987. http://dx.doi.org/10.2514/6.1987-860.

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Gawronski, W., and W. Gawronski. "Almost-balanced structural dynamics." In 38th Structures, Structural Dynamics, and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1997. http://dx.doi.org/10.2514/6.1997-1028.

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LIBRESCU, L., L. MEIROVITCH, and O. SONG. "Integrated Structural Tailoring and Adaptive Control of Advanced Flight Vehicle Structural Vibration." In 34th Structures, Structural Dynamics and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1993. http://dx.doi.org/10.2514/6.1993-1697.

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CRUSE, T., O. BURNSIDE, Y. T. WU, E. POLCH, and P. FINK. "Probabilistic structural analysis methods for select space propulsion system structural components (PSAM)." In 28th Structures, Structural Dynamics and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1987. http://dx.doi.org/10.2514/6.1987-763.

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Reports on the topic "Structural"

1

Sullivan, Brian J., and Kent W. Buesking. Structural Integrity of Intelligent Materials and Structures. Fort Belvoir, VA: Defense Technical Information Center, February 1994. http://dx.doi.org/10.21236/ada280941.

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Fuller, Chris R. Active Structural Acoustic Control and Smart Structures. Fort Belvoir, VA: Defense Technical Information Center, September 1991. http://dx.doi.org/10.21236/ada248341.

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Inman, Daniel J., Armaghan Salhian, and Pablo Tarazaga. Structural Dynamics of Cable Harnessed Spacecraft Structures. Fort Belvoir, VA: Defense Technical Information Center, July 2013. http://dx.doi.org/10.21236/ada588127.

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Fernández-Villaverde, Jesús, and Juan Rubio-Ramírez. How Structural Are Structural Parameters? Cambridge, MA: National Bureau of Economic Research, June 2007. http://dx.doi.org/10.3386/w13166.

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Heymsfield, Ernie, and Jeb Tingle. State of the practice in pavement structural design/analysis codes relevant to airfield pavement design. Engineer Research and Development Center (U.S.), May 2021. http://dx.doi.org/10.21079/11681/40542.

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An airfield pavement structure is designed to support aircraft live loads for a specified pavement design life. Computer codes are available to assist the engineer in designing an airfield pavement structure. Pavement structural design is generally a function of five criteria: the pavement structural configuration, materials, the applied loading, ambient conditions, and how pavement failure is defined. The two typical types of pavement structures, rigid and flexible, provide load support in fundamentally different ways and develop different stress distributions at the pavement – base interface. Airfield pavement structural design is unique due to the large concentrated dynamic loads that a pavement structure endures to support aircraft movements. Aircraft live loads that accompany aircraft movements are characterized in terms of the load magnitude, load area (tire-pavement contact surface), aircraft speed, movement frequency, landing gear configuration, and wheel coverage. The typical methods used for pavement structural design can be categorized into three approaches: empirical methods, analytical (closed-form) solutions, and numerical (finite element analysis) approaches. This article examines computational approaches used for airfield pavement structural design to summarize the state-of-the-practice and to identify opportunities for future advancements. United States and non-U.S. airfield pavement structural codes are reviewed in this article considering their computational methodology and intrinsic qualities.
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Ebeling, Robert, and Barry White. Load and resistance factors for earth retaining, reinforced concrete hydraulic structures based on a reliability index (β) derived from the Probability of Unsatisfactory Performance (PUP) : phase 2 study. Engineer Research and Development Center (U.S.), March 2021. http://dx.doi.org/10.21079/11681/39881.

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This technical report documents the second of a two-phase research and development (R&D) study in support of the development of a combined Load and Resistance Factor Design (LRFD) methodology that accommodates geotechnical as well as structural design limit states for design of the U.S. Army Corps of Engineers (USACE) reinforced concrete, hydraulic navigation structures. To this end, this R&D effort extends reliability procedures that have been developed for other non-USACE structural systems to encompass USACE hydraulic structures. Many of these reinforced concrete, hydraulic structures are founded on and/or retain earth or are buttressed by an earthen feature. Consequently, the design of many of these hydraulic structures involves significant soil structure interaction. Development of the required reliability and corresponding LRFD procedures has been lagging in the geotechnical topic area as compared to those for structural limit state considerations and have therefore been the focus of this second-phase R&D effort. Design of an example T-Wall hydraulic structure involves consideration of five geotechnical and structural limit states. New numerical procedures have been developed for precise multiple limit state reliability calculations and for complete LRFD analysis of this example T-Wall reinforced concrete, hydraulic structure.
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Issa, Mohsen A. Structural Evaluation Procedures for Heavy Wood Truss Structures. Fort Belvoir, VA: Defense Technical Information Center, July 1998. http://dx.doi.org/10.21236/ada362404.

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Allen, J., and J. Lauffer. Integrated structural control design of large space structures. Office of Scientific and Technical Information (OSTI), January 1995. http://dx.doi.org/10.2172/10115453.

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9

Red-Horse, J. R. Structural system identification: Structural dynamics model validation. Office of Scientific and Technical Information (OSTI), April 1997. http://dx.doi.org/10.2172/469145.

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Eisbacher, G. H. Structural geology. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1998. http://dx.doi.org/10.4095/209775.

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