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The demand for energy is increasing massively due to urbanization and industrialization. Due to the massive usage of diesel engines in the transportation sector, global warming is increasing rapidly. The purpose of this paper is to use hydrogen as the potential alternative for diesel engine.

A series of tests conducted in the twin cylinder four stroke diesel engine at various engine speeds. In addition to the hydrogen, the ultrasonication is applied to add the nanoparticles to the neat diesel. The role of nanoparticles on engine performance is effective owing to its physicochemical properties. Here, neat diesel mixed 30% of biodiesel along with the hydrogen at the concentration of 10%, 20% and 30% and 50 ppm of graphite oxide to form the blends DNH10, DNH20 and DNH30.

Inclusion of both hydrogen and nanoparticles increases the brake power and brake thermal efficiency (BTE) of the engine with relatively less fuel consumption. Compared to all blends, the maximum BTE of 33.3% has been reported by 30% hydrogen-based fuel. On the contrary, the production of the pollutants also reduces as the hydrogen concentration increases.

Majority of the pollutants such as carbon monoxide, carbon dioxide and hydrocarbon were dropped massively compared to diesel. On the contrary, there is no reduction in nitrogen of oxides (NOx). Highest production of NOx was witnessed for 30% hydrogen fuel due to the premixed combustion phase and cylinder temperatures.

This study aims to propose a novel viscoelastic–viscoplastic combined constitutive model for glassy amorphous polymers within the framework of thermodynamics at finite strain that is capable of capturing their rate-dependent inelastic mechanical behavior in wide ranges of deformation rate and amount.

The rheology model whose viscoelastic and viscoplastic elements are connected in series is set in accordance with the multi-mechanism theory. Then, the constitutive functions are formulated on the basis of the multiplicative decomposition of the deformation gradient implicated by the rheology model within the framework of thermodynamics. Dynamic mechanical analysis (DMA) and loading/unloading/no-load tests for polycarbonate (PC) are conducted to identify the material parameters and demonstrate the capability of the proposed model.

The performance was validated in comparison with the series of the test results with different rates and amounts of deformation before unloading together. It has been confirmed that the proposed model can accommodate various material behaviors empirically observed, such as rate-dependent elasticity, elastic hysteresis, strain softening, orientation hardening and strain recovery.

This paper presents a novel rheological constitutive model in which the viscoelastic element connected in series with the viscoplastic one exclusively represents the elastic behavior, and each material response is formulated according to the multiplicatively decomposed deformation gradients. In particular, the yield strength followed by the isotropic hardening reflects the relaxation characteristics in the viscoelastic constitutive functions so that the glass transition temperature could be variant within the wide range of deformation rate. Consequently, the model enables us to properly represent the loading process up to large deformation regime followed by unloading and no-load processes.

The purpose of this paper is to adopt the multi-objective optimization technique for identifying a set of optimum abrasive water jet machining (AWJM) parameters to achieve maximum material removal rate (MRR) and minimum surface roughness.

Data of a few experiments as per the Taguchi’s orthogonal array are considered for achieving maximum MRR and minimum surface roughness (Ra) of the Inconel718. Analysis of variance is performed to understand the statistical significance of AWJM input process parameters.

Empirical relations are developed for MRR and Ra in terms of the AWJM process parameters and demonstrated their adequacy through comparison of test results.

The signal-to-noise ratio transformation should be applied to take in to account the scatter in the repetition of tests in each test run. But, many researchers have adopted this transformation on a single output response of each test run, which has no added advantage other than additional computational task. This paper explains the impact of insignificant process parameter in selection of optimal process parameters. This paper demands drawbacks and complexity in existing theories prior to use new algorithms.

Taguchi approach is quite simple and easy to handle optimization problems, which has no practical implications (if it handles properly). There is no necessity to hunt for new algorithms for obtaining solution for multi-objective optimization AWJM process.

This paper deals with a case study, which demonstrates the simplicity of the Taguchi approach in solving multi-objective optimization problems with a few number of experiments.

The purpose of this paper is to identify personality clusters among consumers of Generation Y in India using the Big Five personality traits and profile these clusters on the basis of their levels of fashion consciousness, inclination toward status consumption and materialistic tendencies.

A self-completion questionnaire was administered to 751 respondents from Generation Y (born between 1980 and 2000) using mall-intercept approach. The questionnaire included demographic items and measures of the Big Five personality traits, fashion consciousness, status consumption and materialism. A two-step cluster analysis, using hierarchical and nonhierarchical clustering, was conducted on each respondent’s factor scores on the five dimensions of the Big Five. Later, multivariate analysis of variance (MANOVA) was applied to identify differences in the levels of fashion consciousness, inclination toward status consumption and materialistic tendencies of the clusters.

Four personality clusters were identified, i.e. Conventionalists (N = 95, 12.64 per cent), Anxious Achievers (N = 207, 27.56 per cent), Introverts (N = 204, 27.16 per cent) and Positivists (N = 245, 33.82 per cent). MANOVA revealed significant differences among clusters pertaining to their levels of fashion consciousness, status consumption and materialistic tendencies.

Results suggest that the personality clusters are not homogeneous, and fashion marketers must bear in mind the differences within the cohort of Generation Y while planning their promotion and communication strategies.

The value of this study lies in integrating the widely researched constructs of the Big Five personality traits, fashion consciousness, status consumption and materialism into one holistic study, thereby offering useful insights into the fashion shopping behavior of young Indian adults.

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming, powder metallurgy and composite material processing are briefly discussed. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for 1994‐1996, where 1,370 references are listed. This bibliography is an updating of the paper written by Brannberg and Mackerle which has been published in Engineering Computations, Vol. 11 No. 5, 1994, pp. 413‐55.

Using data from a top-five global executive placement firm, the authors explore how an organization's financial misconduct may affect pay for former employees not implicated in wrongdoing. Drawing on stigma theory, they hypothesize that although such alumni did not participate in the financial misconduct and they had left the organization years before the misconduct, these alumni experience a compensation penalty. The stigma effect increases in relation to the job function proximity to the misconduct, recency of the misconduct, and an employee's seniority. Collectively, results suggest that the stigma of financial misconduct could reach alumni employees and need not be confined to executives and directors that oversaw the organization during the misconduct.

The present study aims to understand small retailers' current use of various low-cost technologies and the factors responsible for small retailers' adoption. Furthermore, these factors of adoption were mapped back to beliefs within the theory of planned behaviour (TPB), and an attempt was made to understand if some of the beliefs dominated over the others and their implications.

The study takes a qualitative approach comprising in-depth semi-structured interviews and direct observation. The qualitative data were analysed through a thematic analysis to identify technology adoption factors.

Amongst the various technologies (mobile apps), payment and procurement apps were the most widely used. The authors identified eight factors influencing technology adoption: the top being customer demand for payment apps and convenience and cost-saving for procurement apps. The study also highlights the role of the dominant beliefs in technology adoption, which managers could use to improve adoption rates.

The current study is a cross-sectional study and the sample was predominantly of grocery retailers, limiting the generalisability of the results.

Small retailers face stiff competition from organised retail and e-commerce platforms which threatens small retailers' existence. Small retailers' survival is vital as many people depend on the small retail sector for livelihood. Increased use of technology seems the only way for them to stay competitive and increase profitability. The study's outcome could help increase technology adoption amongst small retailers and increase small retailers' competitiveness.

Despite the widespread presence of small retailers in emerging economies, few studies have examined technology adoption amongst them. This study is also the first to use the TPB theory in the small retailer technology adoption context.

Presents a review on implementing finite element methods on supercomputers, workstations and PCs and gives main trends in hardware and software developments. An appendix included at the end of the paper presents a bibliography on the subjects retrospectively to 1985 and approximately 1,100 references are listed.

The purpose of this paper is to design and manufacture an intelligent 3D printed sensor to monitor the re-occurrence of diaphragmatic hernia (DH; after surgery) in bovines as an Internet of Things (IOT)-based solution.

The approach used in this study is based on a bibliographic analysis for the re-occurrence of DH in the bovine after surgery. Using SolidWorks and ANSYS, the computer-aided design model of the implant was 3D printed based on literature and discussions on surgical techniques with a veterinarian. To ensure the error-proof design, load test and strain–stress rate analyses with boundary distortion have been carried out for the implant sub-assembly.

An innovative IOT-based additive manufacturing solution has been presented for the construction of a mesh-type sensor (for the health monitoring of bovine after surgery).

An innovative mesh-type sensor has been fabricated by integration of metal and polymer 3D printing (comprising 17–4 precipitate hardened stainless steel and polyvinylidene fluoride-hydroxyapatite-chitosan) without sacrificing strength and specific absorption ratio value.