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The purpose of this paper is to investigate computationally the hydrothermal characteristics for forced convective laminar flow of water through a channel with a top wavy wall and a flat bottom wall having metallic porous blocks.

The governing equations are solved computationally using a finite element method–based numerical solver COMSOL Multiphysics® for the following range of parameters: 10 ≤ Reynolds number (Re) ≤ 500 and 10^–4 ≤ Darcy number (Da) ≤ 10^–1.

The presence of porous blocks significantly influences the heat transfer rate, and the value of local Nusselt number increases with the increase in Da. The value of the average Nusselt number decreases with Da for the top wall and the same is enhanced for the bottom wall of the wavy channel with porous blocks (WCPB). The value of the average Nusselt number for WCPB is significantly higher than that of the wavy channel without porous block (WCWPB), plane channel without porous block (PCWPB) and plane channel with the porous block (PCPB) at higher Re. For PCPB, the performance factor (PF) is always higher than that of WCWPB and WCPB for Da = 10^–4 and Da = 10^–3. Also, PF for WCPB is higher than that of WCWPB for higher Re except for Da = 10^–4. Further, the value of for WCPB is higher than that of PCPB at Da = 10^–2 and 10^–1 at Re = 500.

The current study is useful in designing efficient heat exchangers for process plants, solar collectors and aerospace applications.

The analysis of thermo-hydraulic characteristics for laminar flow through a channel with a top wavy wall and a flat bottom wall having metallic porous blocks have been analyzed for the first time. Further, a comparative assessment of the performance has been performed with a wavy channel without a porous block, a plane channel without a porous block and a plane channel with porous blocks.

The purpose of this paper is to investigate the first three stochastic natural frequencies of skewed sandwich plates, considering uncertain system parameters. To conduct the sensitivity analysis for checking the criticality of input parameters.

The theoretical formulation is developed based on higher-order-zigzag theory in accordance with the radial basis function (RBF) and stochastic finite element (FE) model. A cubic function is considered for in-plane displacement over thickness while a quadratic function is considered for transverse displacement within the core and remains constant in the facesheet. RBF is used as a surrogate model to achieve computational efficiency and accuracy. In the present study, the individual and combined effect of ply-orientation angle, skew angle, number of lamina, core thickness and material properties are considered for natural frequency analysis of sandwich plates.

Results presented in this paper illustrates that the skewness in the sandwich plate significantly affects the global dynamic behaviour of the structure. RBF surrogate model coupled with stochastic FE approach significantly reduced the computational time (more than 1/18 times) compared to direct Monte Carlo simulation approach.

The stochastic results for dynamic stability of sandwich plates show that the inevitable source uncertainties present in the input parameters result in significant variation from the deterministic value demonstrates the need for inclusive design paradigm considering stochastic effects. The present paper comprehensively establishes a generalized new RBF-based FE approach for efficient stochastic analysis, which can be applicable to other complex structures too.

Introduction: Artificial intelligence (AI), the engineering of brilliant machinery, performs intelligent human intelligence tasks, such as learning and problem-solving. Insurance is a financial protection policy either for individuals or entities to reimburse losses from the insured company. The role of AI in insurance always helps enhance customer services and understand their behaviour.

Purpose: This chapter aims to determine the role of AI in the insurance industry in India. The insurance industry is expanding very fast, and to further increase its horizons, the part of the technology of AI is essential. However, this sector has initiated using AI technology and is expanding its scope to benefit the customers.

Methodology: The authors selected research papers of the last five years to review and determine how the technology changed during the period and how an increase in AI benefits the industry and facilitates delivering the best services, and understanding the customer’s needs and behaviour.

Findings: It has been found that the industry is moving very fast and adopting the AI technology methods to enhance customer services, betterment for growing India, and serve insurance services to the nation efficiently.

This paper aims to present a survey concerning the accuracy of thermoplastic polymeric parts fabricated by additive manufacturing (AM). Based on the scientific literature, the aim is to provide an updated map of trends and gaps in this relevant research field. Several technologies and investigation methods are examined, thus giving an overview and analysis of the growing body of research.

Permutations of keywords, which concern materials, technologies and the accuracy of thermoplastic polymeric parts fabricated by AM, are used for a systematic search in peer-review databases. The selected articles are screened and ranked to identify those that are more relevant. A bibliometric analysis is performed based on investigated materials and applied technologies of published papers. Finally, each paper is categorised and discussed by considering the implemented research methods.

The interest in the accuracy of additively manufactured thermoplastics is increasing. The principal sources of inaccuracies are those shrinkages occurring during part solidification. The analysis of the research methods shows a predominance of empirical approaches. Due to the experimental context, those achievements have consequently limited applicability. Analytical and numerical models, which generally require huge computational costs when applied to complex products, are also numerous and are investigated in detail. Several articles deal with artificial intelligence tools and are gaining more and more attention.

The cross-technology survey on the accuracy issue highlights the common critical aspects of thermoplastics transformed by AM. An updated map of the recent research literature is achieved. The analysis shows the advantages and limitations of different research methods in this field, providing an overview of research trends and gaps.

To improve the quality of the additive manufacturing (AM) products, it is necessary to estimate surface roughness distribution in advance. Although surface roughness estimation has been previously studied, factors leading to the creation of a rough surface and a comprehensive test for model validation have not been adequately investigated. Therefore, this paper aims to establish a robust model using empirical data based on optimized artificial neural networks (ANNs) to estimate the surface roughness distribution in fused deposition modelling parts. Accordingly, process parameters such as time, cost and quality should be optimized in the process planning stage.

Process parameters were selected via a literature review of surface roughness estimation modelling by analytical and empirical methods, and then a specific test part was fabricated to provide a complete evaluation of the proposed model. The ANN structure was optimized by trial and error method and evolutionary algorithms. A novel methodology based on the combination of the intelligent algorithms including the ANN, linked to the particle swarm optimization (PSO) and imperialist competitive algorithm (ICA), was developed. The PSOICA algorithm was implemented to increase the capability of the ANN to perform much faster and converge more precisely to favorable results. The performances of the ANN models were compared to the most well-known analytical models at build angle intervals of equal size. The most effective process variable was found by sensitivity analysis. The validity of proposed model was studied comprehensively where different truncheon parts and medical case studies including molar tooth, skull, femur and a custom-made hip stem were built.

This paper presents several improvements in surface roughness distribution modelling including a more suitable method for process parameter selection according to the design criteria and improvements in the overall surface roughness of parts as compared to analytical methods. The optimized ANN based on the proposed advanced algorithm (PSOICA) represents precise estimation and faster convergence. The validity assessment confirms that the proposed methodology performs better in varied conditions and complex shapes.

This research fills an important gap in surface roughness distribution estimation modelling by using a test part designed for that purpose and optimized ANN models which uses purely empirical data. The novel PSOICA combination enhances the ability of the ANN to perform more accurately and quickly. The advantage in using actual surface roughness values is that all factors resulting in the creation of a rough surface are included, which is impossible if other methods are used.

The purpose of this paper is to review the various pre-processing and post-processing approaches used to ameliorate the surface characteristics of fused deposition modelling (FDM)-based acrylonitrile butadiene styrene (ABS) prototypes. FDM being simple and versatile additive manufacturing technique has a calibre to comply with present need of tailor-made and cost-effective products with low cycle time. But the poor surface finish and dimensional accuracy are the primary hurdles ahead the implementation of FDM for rapid casting and tooling applications.

The consequences and scope of FDM pre-processing and post-processing parameters have been studied independently. The comprehensive study includes dominance, limitations, validity and reach of various techniques embraced to improve surface characteristics of ABS parts. The replicas of hip implant are fabricated by maintaining the optimum pre-processing parameters as reviewed, and a case study has been executed to evaluate the capability of vapour smoothing process to enhance surface finish.

The pre-processing techniques are quite deficient when different geometries are required to be manufactured within limited time and required range of surface finish and accuracy. The post-processing techniques of surface finishing, being effective disturbs the dimensional stability and mechanical strength of parts thus incapacitates them for specific applications. The major challenge for FDM is the development of precise, automatic and controlled mass finishing techniques with low cost and time.

The research assessed the feasibility of vapour smoothing technique for surface finishing which can make consistent castings of customized implants at low cost and shorter lead times.

The extensive research regarding surface finish and dimensional accuracy of FDM parts has been collected, and inferences made by study have been used to fabricate replicas to further examine advanced finishing technique of vapour smoothing.

Scaffolds are essentially required to have open porous structure for facilitating bone to grow. They are generally placed on those bone defective/fractured sites which are more prone to compressive loading. Open porous structure lacks in strength in comparison to solid. Selective laser sintering (SLS) process is prominently used for fabrication of polymer/composite scaffolds. So, this paper aims to study for fabrication of three-dimensional open porous scaffolds with enhanced strength, process parameters of SLS of a biocompatible material are required to be optimized.

Regular open porous structures with suitable pore size as per computer-aided design models were fabricated using SLS. Polyamide (PA-2200) was used to fabricate the specimen/scaffold. To optimize the strength of the designed structure, response surface methodology was used to design the experiments. Specimens as per ASTM D695 were fabricated using SLS and compressive testing was carried out. Analysis of variance was done for estimating contribution of individual process parameters. Optimized process parameters were obtained using a trust region algorithm and correlated with experimental results. Accuracy of the fabricated specimen/scaffold was also assessed in terms of IT grades. In vitro cell culture on the fabricated structures confirmed the biocompatibility of polyamide (PA-2200).

Optimized process parameters for open cell process structures were obtained and confirmed experimentally. Laser power, hatch spacing and layer thickness have contributed more in the porous part’s strength than scan speed. The accuracy of the order of IT16 has been found for all functional dimensions. Cell growth and proliferation confirmed biocompatibility of polyamide (PA-2200) for scaffold applications.

This paper demonstrates the biocompatibility of PA-2200 for scaffold applications. The optimized process parameters of SLS process for open cell structure having pore size 1.2 × 1.2 mm² with strut diameter of 1 mm have been obtained. The accuracy of the order of IT16 was obtained at the optimized process factors.

Condition monitoring (CM) has become significantly important, particularly in the context of ensuring safety, reliability and future usefulness of civil infrastructural systems. Most of the age old structures require immediate attention. Nondestructive tests and/or load tests along with routine maintenance inspections are common practice. However, most of the NDT techniques are location-dependent and are conducted in a piecewise manner. The paper aims to discuss these issues.

Numerical methods incorporating inverse techniques are a global approach to identify structural parameters using dynamic responses. However, measurement at all degrees of freedom does not seem to be feasible, due to practical constraints. Parameter identification of structures based on limited dynamic responses like modal slope and curvature mode shapes at the element level in a finite element platform is proposed in the present paper. The structural property for each element is derived adopting a two-phase analysis process, consisting modal extraction and structural parameter identification. It is important to study the accuracy of the predicted parameters with the number of measured modes. The structural property is identified using measured responses at those selected MDOF.

The proposed method is demonstrated in detail with a numerical example. The method seems to be an attractive proposition as the results obtained are very accurate even with noise-contaminated data.

However, for practical problems, the experimental validation is significantly important prior to its application in real-life problems.

The developed model seems to be feasible for practical applications after experimental validation, as it is able to identify the structural parameters from limited noisy dynamic responses in frequency domains measured for few modes.

Structural CM is the need of the hour, particularly for infrastructural systems including buildings and bridges, etc. System identification with a global dynamic response at few measurement locations may address the issue of health assessment of structures, which will have great social implications with respect to safety.

The proposed numerical model is originally developed by the authors with judicial modifications and combination of earlier research contributions to achieve greater accuracy. Limited measurement and the effect of random noise with numerical example are considered for the successful validation.

Adaptive slicing is a key step in three-dimensional (3D) printing as it is closely related to the building time and the surface quality. This study aims to develop a novel adaptive slicing method based on ameliorative area ratio and accurate cusp height for 3D printing using stereolithography (STL) models.

The proposed method consists of two stages. In the first stage, the STL model is sliced with constant layer thickness, where an improved algorithm for generating active triangular patches, the list is developed to preprocess the model faster. In the second stage, the model is first divided into several blocks according to the number of contours, then an axis-aligned bounding box-based contour matching algorithm and a polygons intersection algorithm are given to compare the geometric information between several successive layers, which will determine whether these layers can be merged to one.

Several benchmarks are applied to verify this new method. Developed method has also been compared with the uniform slicing method and two existing adaptive slicing methods to demonstrate its effectiveness in slicing.

Compared with other methods, the method leads to fewer layers whilst keeping the geometric error within a given threshold. It demonstrates that the proposed slicing method can reach a trade-off between the building time and the surface quality.