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This paper aims to study the influences of hydrogen jet pressure on flow features of a strut-based injector in a scramjet combustor under-reacting cases are numerically investigated in this study.

The numerical analysis is carried out using Reynolds Averaged Navier Stokes (RANS) equations with the Shear Stress Transport k-ω turbulence model in contention to comprehend the flow physics during scramjet combustion. The three major parameters such as the shock wave pattern, wall pressures and static temperature across the combustor are validated with the reported experiments. The results comply with the range, indicating the adopted simulation method can be extended for other investigations as well. The supersonic flow characteristics are determined based on the flow properties, combustion efficiency and total pressure loss.

The results revealed that the augmentation of hydrogen jet pressure via variation in flame features increases the static pressure in the vicinity of the strut and destabilize the normal shock wave position. Indeed, the pressure of the mainstream flow drives the shock wave toward the upstream direction. The study perceived that once the hydrogen jet pressure is reached 4 bar, the incoming flow attains a subsonic state due to the movement of normal shock wave ahead of the strut. It is noticed that the increase in hydrogen jet pressure in the supersonic flow field improves the jet penetration rate in the lateral direction of the flow and also increases the total pressure loss as compared with the baseline injection pressure condition.

The outcome of this research provides the influence of fuel injection pressure variations in the supersonic combustion phenomenon of hypersonic vehicles.

This paper substantiates the effect of increasing hydrogen jet pressure in the reacting supersonic airstream on the performance of a scramjet combustor.

Carbon dioxide (CO₂) has attracted special scientific interest over the last years mainly because of its relation to climate change and indoor air quality. Except for this, CO₂ can be used as an indicator of food freshness, patients’ clinical state and fire detection. Therefore, the accurate monitoring and controlling of CO₂ levels are imperative. The development of highly sensitive, selective and reliable sensors that can efficiently distinguish CO₂ in various conditions of temperature, humidity and other gases’ interference is the subject of intensive research with chemi-resistive zinc oxide (ZnO)-based sensors holding a privileged position. Several ZnO nanostructures have been used in sensing applications because of their versatile features. However, the deficient selectivity and long-term stability remain major concerns, especially when operating at room temperature. This study aims to encompass an extensive study of CO₂ chemi-resistive sensors based on ZnO, introducing the most significant advances of recent years and the best strategies for enhancing ZnO sensing properties.

An overview of the different ZnO nanostructures used for CO₂ sensing and their synthesis methods is presented, focusing on the parameters that highly affect the sensing mechanism and, thus, the performance of CO₂ sensors.

The selectivity and sensitivity of ZnO sensors can be enhanced by adjusting various parameters during their synthesis and by doping or treating ZnO with suitable materials.

This paper summarises the advances in the rapidly evolving field of CO₂ sensing by ZnO sensors and provides research directions for optimised sensors in the future.

Cloud computing gives several on-demand infrastructural services by dynamically pooling heterogeneous resources to cater to users’ applications. The task scheduling needs to be done optimally to achieve proficient results in a cloud computing environment. While satisfying the user’s requirements in a cloud environment, scheduling has been proven an NP-hard problem. Therefore, it leaves scope to develop new allocation models for the problem. The aim of the study is to develop load balancing method to maximize the resource utilization in cloud environment.

In this paper, the parallelized task allocation with load balancing (PTAL) hybrid heuristic is proposed for jobs coming from various users. These jobs are allocated on the resources one by one in a parallelized manner as they arrive in the cloud system. The novel algorithm works in three phases: parallelization, task allocation and task reallocation. The proposed model is designed for efficient task allocation, reallocation of resources and adequate load balancing to achieve better quality of service (QoS) results.

The acquired empirical results show that PTAL performs better than other scheduling strategies under various cases for different QoS parameters under study.

The outcome has been examined for the real data set to evaluate it with different state-of-the-art heuristics having comparable objective parameters.

Load balancing is an important issue for a heterogeneous distributed computing system environment that has been proven to be a nondeterministic polynomial time hard problem. This paper aims to propose a resource-aware load balancing (REAL) model for a batch of independent tasks with a centralized load balancer to make the solution appropriate for a practical heterogeneous distributed environment having a migration cost with the objective of maximizing the level of load balancing considering bandwidth requirements for migration of the tasks.

To achieve the effective schedule, load balancing issues should be addressed and tackled through efficient workload distribution. In this approach, the migration has been carried out in two phases, namely, initial migration and best-fit migration. Using the best-fit policy in migrations helps in the possible performance improvement by minimizing the remaining idle slots on underloaded nodes that remain unentertained during the initial migration.

The experimental results reveal that the proposed model exhibits a superior performance among the other strategies on considered parameters such as makespan, average utilization and level of load balancing under study for a heterogeneous distributed environment.

Design of the REAL model and a comparative performance evaluation with LBSM and ITSLB have been conducted by using MATLAB 8.5.0.

Poly(styrenesulphonic acid)‐doped polyaniline has been synthesised and the influence of this polymeric compound on the inhibition of corrosion of mild steel in 1M HCl has been investigated using weight loss measurements, galvanostatic polarisation studies, electropermeation studies and a.c. impedance measurements. The polymer acts predominantly as an anodic inhibitor. Hydrogen permeation studies and a.c. impedance measurements clearly indicate a very effective performance of the compound as a corrosion inhibitor. The adsorption of the compound on the mild steel surface obeys Temkin's adsorption isotherm.

The purpose of this paper is to discover the impact of different dimensions of organizational culture (mission culture, adaptability culture, involvement culture and consistency culture) on business excellence results criteria (customer results, people results, society results and business results) in the United Arab Emirates (UAE) and explore the moderating role of information and communication technology (ICT) use in both service and manufacturing industries.

Data were collected by questionnaire from 448 managers in nine companies that have won the Sheikh Khalifa Excellence Award in the last three years. Structural equation modeling was used to examine the data.

Organizational culture is significantly related to business excellence. However, these effects varied for different business excellence criteria. Three organizational culture types had a significant positive role in achieving excellent customer-related results. All four types of organizational culture had a positive role in achieving excellent people-related results. Only two culture types had significant role in achieving excellent society-related results. Business results were positively related to a balance between the four types of organizational culture. ICT use moderated the relationship between organizational culture and results related to customers, people and business, but not society.

This study had some conceptual limitations. In particular, it considered the organizational culture as four types in the research model, but without structuring the indices under each type. It also had some methodological limitations. It was cross-sectional and used a self-administered questionnaire, which means that no causal relationships can be implied, and there may have been some bias in responding.

This is one of the first studies that investigate the relationship between organizational culture and business excellence in UAE excellence award-winning companies.

This paper aims to report the effect of titanium oxide (TiO₂) particles on the specific wear rate (SWR) of alkaline treated bamboo and flax fiber-reinforced composites (FRCs) under dry sliding condition by using a robust statistical method.

In this research, the epoxy/bamboo and epoxy/flax composites filled with 0–8 Wt.% TiO₂ particles have been fabricated using simple hand layup techniques, and wear testing of the composite was done in accordance with the ASTM G99-05 standard. The Taguchi design of experiments (DOE) was used to conduct a statistical analysis of experimental wear results. An analysis of variance (ANOVA) was conducted to identify significant control factors affecting SWR under dry sliding conditions. Taguchi prediction model is also developed to verify the correlation between the test parameters and performance output.

The research study reveals that TiO₂ filler particles in the epoxy/bamboo and epoxy/flax composite will improve the tribological properties of the developed composites. Statistical analysis of SWR concludes that normal load is the most influencing factor, followed by sliding distance, Wt.% TiO2 filler and sliding velocity. ANOVA concludes that normal load has the maximum effect of 31.92% and 35.77% and Wt.% of TiO2 filler has the effect of 17.33% and 16.98%, respectively, on the SWR of bamboo and flax FRCs. A fairly good agreement between the Taguchi predictive model and experimental results is obtained.

This research paper attempts to include both TiO₂ filler and bamboo/flax fibers to develop a novel hybrid composite material. TiO₂ micro and nanoparticles are promising filler materials, it helps to enhance the mechanical and tribological properties of the epoxy composites. Taguchi DOE and ANOVA used for statistical analysis serve as guidelines for academicians and practitioners on how to best optimize the control variable with particular reference to natural FRCs.

The purpose of this paper is to analyse fatigue-life prediction based on a reliability assessment for coil springs of vehicle suspension systems using different road excitations under random loading.

In this study, a reliability assessment was conducted to predict the fatigue life of an automobile coil spring during different road data surfaces. Campus, urban and highway road surfaces were considered to capture fatigue load strain histories using a data acquisition system. Random loadings are applied on top of a coil spring where coil is fixed from down. Fatigue reliability was established as a system of correlated events during the service life to predict the probability of fatigue life using Coffin–Manson, Morrow and Smith–Watson–Topper (SWT) models.

Fatigue-life prediction based on a reliability assessment revealed that the Morrow model can predict a safe region of a life data point for the three road surfaces. Highway road data indicated the highest rate of reliability at 0.8 for approximately 1.69 × 10⁵ cycles for the SWT model.

Reliability assessment of the fatigue life of vehicle coil springs is vital for safe operation. The reliability analysis of a coil spring under random loading excitations can be used for fatigue-life prediction.

The purpose of this paper is to present a method for generating a set of feasible, optimized production schedules for the erection process of compact shipyards building complex ship types.

A bi-objective mathematical model is developed based on the process constraints. A Pareto front of possible erection schedules is created using a the Non-dominated Sorting Genetic Algorithm II with a custom heuristic fitness function and constraint violation.

It was possible to consistently generate a wide variety of production schedules with superior performance to those manually created by shipyard planner in negligible computational time.

The set of optimized production schedules generated by the developed methodology can be used as a starting point by existing shipyard planners when drafting the initial erection planning for a new project. This allows the planners to consider wider variety of options in less time.

No other published approach for the automatic generation of optimized production schedules of the erection process is specifically tailored to the construction of complex ships.