Mohit Verma

Fuzzy Similarity Approach for Ranking and Health Assessment of Towers Based on Visual Inspection

The most common way for the health assessment of existing telecommunication towers is through visual inspection. However, the results of the visual inspection are highly subjective and are merely based on perception which may differ grossly from one expert to another. One of the best ways to normalize human perception and reasoning in decision making is through fuzzy logic. This paper presents a fuzzy approach towards health assessment and ranking of telecommunication towers based on visual inspection. The health assessment of tower is treated as a group multicriteria decision making (MCDM) problem in which the towers are rated by expert group based on different criteria. The model used in the paper is a modified version of fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The modified version rank the towers based on similarity with fuzzy positive ideal solution (FPIS) rather than the distance from fuzzy positive and negative ideal solutions. The model also provides critical information about the issues which need to be addressed to maintain the health of the towers and thereby enables efficient management and allocation of the limited resources. An illustrative example is included to clearly describe the steps involved in the process. Finally, sensitivity analysis for the model is carried out. The results of the sensitivity analysis demonstrate the tolerance of the model for slight variation in the input parameters, which typically reflect the doubt or confusion in the mind of expert while rating. The method is also compared with the closeness coefficient method and is found to be more appropriate for the ranking of towers. The model attempts to bring some rationality to the vagueness involved in visual inspection. The model is an effective tool for health assessment and ranking of towers based on visual inspection.

Kernel-based models for prediction of cement compressive strength

Abstract This paper employs three different kernel-based models—support vector regression (SVR), relevance vector machine (RVM) and Gaussian process regression (GPR)—for the prediction of cement compressive strength. The input variables for the model are taken as C3S (%), SO3 (%), Alkali (%) and Blaine (cm2/g), while the output is 28-day cement compressive strength (N/mm2) of the cement. The hyperparameters of the SVR are obtained using two different metaheuristic optimization algorithms—particle swarm optimization (PSO) and symbiotic organism search (SOS). Trial-and-error-based approach is used for arriving at the hyperparameters of RVM and GPR. The compressive strength predicted using different kernel-based models is also compared with that obtained from ANN and fuzzy logic models reported in the literature. The performance of the different kernel-based models is benchmarked using six different error indices and residual analysis. The performance of the kernel-based models is found to be at par with ANN. The better generalization capability and excellent empirical performance of the kernel-based models overcome the disadvantages associated with ANN and provide a good tool for the prediction of the cement compressive strength.

A thermodynamical approach towards group multi-criteria decision making (GMCDM) and its application to human resource selection

Graphical abstractDisplay Omitted HighlightsA new model for group multi-criteria decision making (GMCDM) using thermodynamical indicators.TOPSIS used an indicator similar to energy while the current model uses exergy indicator for ranking of alternatives.The model incorporates a factor accounting for the quality of the ratings.The model is formulated for both crisp and fuzzy environment.Two case studies are carried out in human resource selection to demonstrate the application and the effectiveness of the proposed model. In group multi-criteria decision making (GMCDM) problems, ratings are assigned to the alternatives on different criteria by an expert group. In this paper, we propose a thermodynamically consistent model for GMCDM using the analogies for thermodynamical indicators energy, exergy and entropy. The most commonly used method for analysing GMCDM problem is technique for order of preference by similarity to ideal solution (TOPSIS). The conventional TOPSIS method uses a measure similar to energy for the ranking of alternatives. We demonstrate that the ranking of the alternatives is more meaningful if we use exergy in place of energy. The use of exergy is superior due to the inclusion of a factor accounting for the quality of the ratings by the expert group. The unevenness in the ratings by the experts is measured by entropy. The procedure for the calculation of the thermodynamical indicators is explained in both crisp and fuzzy environments. Finally, the effectiveness of the proposed method is demonstrated by applying to human resource selection problem.

Fuzzy logic controller for real-time substructuring applications

Real-time substructuring is a hybrid technique in which the critical component of the structure is tested, while the remainder is numerically analyzed based on a suitable model. The synchronization between the testing and the analysis is maintained by a controller. This paper proposes a new controller based on fuzzy logic for real-time substructuring applications. The advantage of a fuzzy-logic-based controller is that it is rule based and involves far less computations. The performance of the proposed controller is verified through numerical simulations of a substructured linear and nonlinear single-degree-of-freedom system for two different damping ratios. The performance of the controller is compared with that of conventional controllers which are used in real-time substructuring on the basis of a nondimensional error index. The fuzzy logic controller is found to have the least error index for the chosen nonlinear system and performs satisfactorily for a linear system. Furthermore, the effectiveness of the proposed fuzzy logic controller is demonstrated by numerically evaluating the response of a portal frame pinned at one of the beam column joints for the El-Centro earthquake. The displacement time history response was found to closely match that of the emulated system.

Real-time Hybrid Simulation Using an Electromagnetic Shaker

This paper discusses a controller design strategy for the real-time hybrid simulation using an electromagnetic shaker. A two-storey shear building is adopted as the system whose response is emulated using hybrid simulation. The bottom storey is taken as the physical subsystem while the top storey is taken as the virtual subsystem. A control law is derived such that the mechanical impedance of the electromagnetic shaker matches to that of the virtual subsystem. The control law is validated by comparing the frequency responses of the virtual subsystem and the electromagnetic shaker from the physical subsystem acceleration to the force transferred. Finally, the experimental validation of the controller design strategy is carried out by the hybrid simulation of the two-storey structure. The frequency response obtained from the experiment and emulated system is found to be in good agreement with each other.

Numerical Investigation on the Flexural Performance of Laced Steel–Concrete Composite (LSCC) One-Way Slab System

In this paper, numerical investigations are carried out to assess the flexural performance of laced steel–concrete composite (LSCC) one-way slab system subjected to monotonic loading. The individual LSCC units are modelled as L-shaped beams. Flanges of two LSCC units are then connected using high strength steel bolts. Finite element analysis of the LSCC slab system is carried out in ABAQUS. Concrete damaged plasticity (CDP) model is used for concrete in both tension and compression including damage characteristics. Nonlinear behaviour of steel is modelled using plasticity model available in the software. The LSCC slab system is then subjected to two-point loading under displacement control mode. The LSCC slab system is found to take the load up to 333 kN for 200-mm deflection. The composite action of the two LSCC units is evident from the deformed shape. Therefore, the proposed integration scheme for LSCC one-way slab system using bolts is found to be effective. An analytical procedure is also described to estimate the strength of the LSCC one-way slab system based on the different failure criteria. The strength obtained from the analytical model is found to be in close agreement with those obtained from ABAQUS.

A Convex Optimization Framework for Hybrid Simulation

Hybrid simulation is a dynamic response evaluation technique which involves the partitioning of the structure into parts—physical and numerical subsystems. The interaction between the two subsystems is realized with the help of a transfer system (an actuator or a shake table). The objective of the hybrid simulation is to find control input to the transfer system such that the impedance of the transfer system is close to the numerical subsystem. The physical limitations of the system needs to be accounted while designing controller for hybrid simulation. This paper presents a framework which enables to pose controller synthesis for hybrid simulation as a multi-objective convex optimization problem using linear matrix inequalities (LMIs). Different control system tools based on LMIs which can be used for abstract formulation are described. A mathematical model based on the linear control theory is presented for the hybrid simulation of a three degrees of freedom system using shake table. The controller obtained from the solution of optimization is used to evaluate the frequency response of the closed loop hybrid system. It is observed that the accuracy of the hybrid simulation decreases with the decrease in the control effort.