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This paper presents a review concerning the analytical and inverse methods of small punch creep test (SPCT) in order to evaluate the mechanical property of component material at elevated temperature.

In this work, the effects of temperature, specimen size and shape on material properties are mainly discussed using the finite element (FE) method. The analytical approaches including membrane stretching, empirical or semi-empirical solutions that are currently used for data interpretation have been presented.

The state-of-the-art research progress on the inverse method, such as non-linear optimization program and neutral network, is critically reviewed. The capabilities of the inverse technique, the uniqueness of the solution and future development are discussed.

The state-of-the-art research progress on the inverse method such as non-linear optimization program and neutral network is critically reviewed. The capabilities of the inverse technique, the uniqueness of the solution and future development are discussed.

A new class of approximate inverse banded matrix techniques based on the concept of LU‐type factorization procedures is introduced for computing explicitly approximate inverses without inverting the decomposition factors. Explicit preconditioned iterative schemes in conjunction with approximate inverse matrix techniques are presented for the efficient solution of banded linear systems. Applications of the method on a linear system are discussed and numerical results are given.

With the advent of technology, a huge amount of data is being transmitted and received through the internet. Large bandwidth and storage are required for the exchange of data and storage, respectively. Hence, compression of the data which is to be transmitted over the channel is unavoidable. The main purpose of the proposed system is to use the bandwidth effectively. The videos are compressed at the transmitter’s end and reconstructed at the receiver’s end. Compression techniques even help for smaller storage requirements.

The paper proposes a novel compression technique for three-dimensional (3D) videos using a zig-zag 3D discrete cosine transform. The method operates a 3D discrete cosine transform on the videos, followed by a zig-zag scanning process. Finally, to convert the data into a single bit stream for transmission, a run-length encoding technique is used. The videos are reconstructed by using the inverse 3D discrete cosine transform, inverse zig-zag scanning (quantization) and inverse run length coding techniques. The proposed method is simple and reduces the complexity of the convolutional techniques.

Coding reduction, code word reduction, peak signal to noise ratio (PSNR), mean square error, compression percent and compression ratio values are calculated, and the dominance of the proposed method over the convolutional methods is seen.

With zig-zag quantization and run length encoding using 3D discrete cosine transform for 3D video compression, gives compression up to 90% with a PSNR of 41.98 dB. The proposed method can be used in multimedia applications where bandwidth, storage and data expenses are the major issues.

The purpose of this paper is to investigate strategies for expedited dimension scaling of electromagnetic (EM)-simulated microwave and antenna structures, exploiting the concept of variable-fidelity inverse surrogate modeling.

A fast inverse surrogate modeling technique is described for dimension scaling of microwave and antenna structures. The model is established using reference designs obtained for cheap underlying low-fidelity model and corrected to allow structure scaling at high accuracy level. Numerical and experimental case studies are provided demonstrating feasibility of the proposed approach.

It is possible, by appropriate combination of surrogate modeling techniques, to establish an inverse model for explicit determination of geometry dimensions of the structure at hand so as to re-design it for various operating frequencies. The scaling process can be concluded at a low computational cost corresponding to just a few evaluations of the high-fidelity computational model of the structure.

The present study is a step toward development of procedures for rapid dimension scaling of microwave and antenna structures at high-fidelity EM-simulation accuracy.

The proposed modeling framework proved useful for fast geometry scaling of microwave and antenna structures, which is very laborious when using conventional methods. To the authors’ knowledge, this is one of the first attempts to surrogate-assisted dimension scaling of microwave components at the EM-simulation level.

Large structural objects, primarily concrete bridges, can be reinforced by gluing to their stretched surface tapes of fiber-reinforced polymer (FRP). The condition for this technology to work requires the quality of the bonding of FRP and the concrete to be perfect. Possible defects may arise in the phase of construction but also as a result of long-term fatigue loads. These defects having different forms of voids and discontinuities in the bonding layer are difficult to detect by optical inspection. This paper aims to describe the development of a rapid and nondestructive method for quantitative assessment of the debonding between materials.

The applied technique belongs to the wide class of active infrared (IR) thermography, the principle of which is to heat (or cool) the investigated object, and determine the properties of interest from the recorded, by an IR camera, temperature field. The methodology implemented in this work is to uniformly heat for a few seconds, using a set of halogen lamps, the FRP surface attached to the concrete. The parameter of interest is the thermal resistance of the layer separating the polymer tape and the concrete. The presence of voids and debonding will result in large values of this resistance. Its value is retrieved by solving an inverse transient heat conduction problem. This is accomplished by minimizing, in the sense of least squares, the difference between the recorded and simulated temperatures. The latter is defined as a solution of a 1D transient heat conduction problem with the already mentioned thermal resistance treated as the only decision variable.

A general method has been developed, which detects debonding of the FRP tapes from the concrete. The method is rapid and nondestructive. Owing to a special selection of the compared dimensionless measured and simulated temperatures, the method is not sensitive to the surface quality (roughness and emissivity). Measurements and calculation may be executed within seconds. The efficiency of the technique has been shown at a sample, where the defects have been artificially introduced in a controlled manner.

A quantitative assessment procedure which can be used to determine the extent of the debonding has been developed. The procedure uses inverse technique whose result is the unknown thermal resistance between the member and the FRP strip.

Condition monitoring (CM) of structures is important from safety consideration. Damage detection techniques, using inverse dynamic approaches, are important tools to improve the mathematical models for monitoring the condition of structure. Uncertainties in the measured data might lead to unreliable identification of damage in structural system. Experimental validation is crucial for establishing its practical applicability. The measurement of dynamic responses at all degrees of freedom (DOFs) of a structure is also not feasible in practice. In addition the effect of these uncertainties and constraint of limited measurement are required to be studied based on experimental validation. This paper aims to discuss these issues.

Proposed numerical model based on measured natural frequencies and mode shapes is found suitable for CM of framed structures in the framework of finite element model with limited dynamic responses. The structural properties, namely, axial rigidity and bending rigidity are identified at the element level in the updated models of the system. Damage at the element level is identified by comparing the identified structural parameters of the updated model of the system with those of the undamaged state. Proposed numerical model is suitable for practical problem, as it is able to identify the structural parameters with limited modal data of first few modes, measured at selected DOFs.

The model is able to identify the structural damage with greater accuracy from the noisy dynamic responses even if the extent of damage is small. Experimental studies, on simple cantilever beams, establish the potential of the proposed methods for its practical implementation.

The greater random noise will lead to unreliable identification of structural parameters as observed. Thus, filtering of noise technique may be required to be adopted prior to consideration of the measured data in the proposed identification approach.

Requirement of higher modal data seems to be difficult in case of real life practical problem. Thus, simulation technique like condensation or SEREP technique may be adopted.

Structural health monitoring of infrastructural system is significantly important. CM of those structures from global response with limited measured data seems to be an effective tool to ensure safety and durability of structures.

The modal testing and subsequent extraction of modal data have been carried out at the authors’ laboratory. The numerical code based on inverse dynamic approach has been developed independently with original contribution.

Many a times, the information about the boundary heat flux is obtained only through inverse approach by locating the thermocouple or temperature sensor in accessible boundary. Most of the work reported in literature for the estimation of unknown parameters is based on heat conduction model. Inverse approach using conjugate heat transfer is found inadequate in literature. Therefore, the purpose of the paper is to develop a 3D conjugate heat transfer model without model reduction for the estimation of heat flux and heat transfer coefficient from the measured temperatures.

A 3 D conjugate fin heat transfer model is solved using commercial software for the known boundary conditions. Navier–Stokes equation is solved to obtain the necessary temperature distribution of the fin. Later, the complete model is replaced with neural network to expedite the computations of the forward problem. For the inverse approach, genetic algorithm (GA) and particle swarm optimization (PSO) are applied to estimate the unknown parameters. Eventually, a hybrid algorithm is proposed by combining PSO with Broyden–Fletcher–Goldfarb–Shanno (BFGS) method that outperforms GA and PSO.

The authors demonstrate that the evolutionary algorithms can be used to obtain accurate results from simulated measurements. Efficacy of the hybrid algorithm is established using real time measurements. The hybrid algorithm (PSO-BFGS) is more efficient in the estimation of unknown parameters for experimentally measured temperature data compared to GA and PSO algorithms.

Surrogate model using ANN based on computational fluid dynamics simulations and in-house steady state fin experiments to estimate the heat flux and heat transfer coefficient separately using GA, PSO and PSO-BFGS.

As compared with the maneuvering flight studies for single main rotor helicopters, the corresponding studies for coaxial rotor helicopters are relatively poor. In this paper, the maneuvering flight governing equations for coaxial rotor helicopters is established. By introducing induced velocity interference factor analysis, the coaxial rotor aerodynamic interference can be taken into account. With the combination of coaxial rotor helicopter control features and nonlinear inverse simulation technique, the governing equations for maneuvering flight can be solved so as to determine helicopter control input, control force and moment, and helicopter body attitudes which are needed for performing a specified maneuver. Good results of the sample calculations of level turn and lateral jink maneuvers are obtained and simply analyzed.

This paper aims to present a new discrete method to predict average excess pore pressure and degree of consolidation for soft ground using prefabricated vertical drains under time-dependent surcharge and/or vacuum loading and multi-soil layers.

The drain is discretized into a number of mesh points at which the average excess pore pressure is estimated. The conventional Laplace technique is used to solve the analytical equations. The proposed method is validated with previous findings reported in the literature. Moreover, field measurements are used to verify the accuracy of the proposed method with a case history of ground improvement by prefabricated vertical drains using the vacuum consolidation technique.

In comparison to past studies, this new discrete method is simpler to be implemented in a spreadsheet calculation to achieve a rational solution with less computational time for similar consolidation problems. Moreover, the current approach also incorporates a solution for multi-soil layers, which can hardly be derived by analytical solutions.

According to authors’ knowledge, this is the first-time discrete method by Laplace transform technique is applied for the vertical drain.

This purpose of this paper is to provide an overview of the theoretical background and applications of inverse reinforcement learning (IRL).

Reinforcement learning (RL) techniques provide a powerful solution for sequential decision making problems under uncertainty. RL uses an agent equipped with a reward function to find a policy through interactions with a dynamic environment. However, one major assumption of existing RL algorithms is that reward function, the most succinct representation of the designer's intention, needs to be provided beforehand. In practice, the reward function can be very hard to specify and exhaustive to tune for large and complex problems, and this inspires the development of IRL, an extension of RL, which directly tackles this problem by learning the reward function through expert demonstrations. In this paper, the original IRL algorithms and its close variants, as well as their recent advances are reviewed and compared.

This paper can serve as an introduction guide of fundamental theory and developments, as well as the applications of IRL.

This paper surveys the theories and applications of IRL, which is the latest development of RL and has not been done so far.