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Fiber nonlinearities are anticipated to impose transmission limitations due to the enhanced total interaction length in long‐haul dense wavelength division multiplexing (DWDM) optical transmission systems. The purpose of this paper is to analytically study the combined effect of stimulated Raman scattering (SRS) and four‐wave mixing (FWM) in the presence of amplified spontaneous emission (ASE) noise generated by erbium‐doped fiber amplifiers (EDFAs).

The paper presents analytical analysis of DWDM optical transmission systems in the presence of two significant fiber nonlinearities (SRS and FWM).

Simple expressions are derived to study the dependence of signal‐to‐noise ratio (SNR) on the amplifier spacing between two consecutive amplifiers.

The authors have analytically studied the combined effect of SRS and FWM in the presence of ASE noise generated by EDFAs. The novelty of the work is that it has considered all the three factors simultaneously and the expressions are derived for calculation of SNR.

The current generation of light wave systems benefit from increased transmission distance by using optical amplification and increased capacity by using dense wavelength division multiplexing (DWDM) technology. The reach of present systems is limited by the noise contributed by the used amplifiers, combined with nonlinear effects from transmission. This paper aims to address these issues.

The nature and extent of degradations in the optical DWDM systems due to these limiting factors have been discussed in this paper.

It has been learnt that stimulated Raman scattering (SRS), four wave mixing (FWM) and amplified spontaneous emission (ASE) are the important factors in optical DWDM systems. These factors limit the system capacity of the transmission systems drastically.

It can be concluded from the discussion that while designing an efficient DWDM system, an optimization of the channel separation and the amplifier separation is required to minimize the nonlinear effects (FWM and SRS) along with the ASE noise introduced by inline optical amplifications.

The purpose of this paper is to cover an experimental investigation of the impulse response of the foam-mass system (FMS) to unveil some of the foam dynamic behavior features needed to optimize the impact comfort of seat-occupant system. The equation of motion of the studied system is modeled as a sum of a linear elastic, pneumatic damping and viscoelastic residual forces. An identification methodology based on two separated calibration processes of the viscoelastic parameters was developed.

The viscoelastic damping force representing the foam short memory effects was modeled through the hereditary formulation. Its parameters were predicted from the free vibrational response of the FMS using iterative Prony method for autoregressive–moving–average model. However, the viscoelastic residual force resulting in the long memory effects of the material was modeled with fractional derivative term and its derivative order was predicted from previous cyclic compression standards.

The coefficients of the motion law were determined using closed form solution approach. The predictions obtained from the simulations of the impulse and cyclic tests are reasonably accurate. The physical interpretations as well as the mathematical correlations between the system parameters were discussed in details.

The prediction model combines hereditary and fractional derivative formulations resulting in short and long physical memory effects, respectively. Simulation of impulse and cyclic behavior yields good correlation with experimental findings.

University department efficiency evaluation is a performance assessment on how departments use their resources to attain their goals. The most widely used tool in measuring the efficiency of academic departments in data envelopment analysis (DEA) deals with crisp data, which may be, often, imprecise, vague, missing or predicted. Current literature offers various approaches to addressing these uncertainties by introducing fuzzy set theory within the basic DEA framework. However, current fuzzy DEA approaches fail to handle missing data, particularly in output values, which are prevalent in real-life evaluation. Thus, this study aims to augment these limitations by offering a fuzzy DEA variation.

This paper proposes a more flexible approach by introducing the fuzzy preference programming – DEA (FPP-DEA), where the outputs are expressed as fuzzy numbers and the inputs are conveyed in their actual crisp values. A case study in one of the top higher education institutions in the Philippines was conducted to elucidate the proposed FPP-DEA with fuzzy outputs.

Due to its high discriminating power, the proposed model is more constricted in reporting the efficiency scores such that there are lesser reported efficient departments. Although the proposed model can still calculate efficiency no matter how much missing and unavailable, and uncertain data, more comprehensive data accessibility would return an accurate and precise efficiency score.

This study offers a fuzzy DEA formulation via FPP, which can handle missing, unavailable and imprecise data for output values.

The purpose of this paper is to develop a combined intuitionistic fuzzy analytic hierarchy process (IFAHP) and fuzzy multi-objective optimization approach to select suppliers and allocate the orders to them in the bottled water production context.

First, the primary weights of criteria associated with the supplier selection problem are calculated using the IFAHP technique. Then a fuzzy multi-objective optimization model is developed to allocate the appropriate amount of orders to each supplier.

The proposed methodology has been successfully implemented in the case of an Iranian food company in its bottled water factory. Results demonstrate our model is capable of practically handling the uncertainty in DMs’ preference that leads to effective and efficient supplier selection and order allocation decisions.

The authors develop a novel hybrid decision-making tool to tackle the uncertainty in decision-makers’ opinions with a demonstrated applicability and some promising outcomes in efficiently allocating the order quantity to suppliers in the area of bottled water production.

Batteries installed on electric vehicles (EVs) should normally be removed when their capacity falls to 70-80 per cent, but they are still usable for other purposes, such as energy storage. This paper studies an EV battery closed-loop supply chain (CLSC) consisting of a battery manufacturer and a remanufacturer. The manufacturer produces new batteries by using natural resources, while the remanufacturer collects returned batteries and makes decisions based on the return quality, that is, to reuse or recycle. The purpose of this paper is to maximise the individual profits through optimising the amount of manufacturing and remanufacturing, respectively, and optimising the purchase price of returned batteries.

Based on the Nash equilibrium, this paper develops a three-period model in the CLSC. In period 1, batteries are made from raw materials; in period 2, returned batteries from period 1 are sorted into low quality and high quality. Some high-quality returns can be reused for other purposes while those non-reusable returns are recycled into materials. In period 3, all the returns are recycled into materials. The analytical results are derived.

The result of the analyses suggest that first, among the variables that affect the (re-)manufacturing decision, the purchase price for returned batteries plays a critical role. In particular, the price of low-quality returns has more influence than the price of high quality returns. Second, the higher purchase price for re-usable returns does not necessarily lead to a higher return rate of reusable returns. Third, the manufacturer’s profit is normally higher than the remanufacturer’s. This suggests the need to design incentives to promote the remanufacturing sector. And finaly, although it is appreciated that maximising the utilisation of batteries over the life-cycle would benefit the environment, the economic benefit needs further investigation.

Although the CLSC has been widely studied, studies on the EV battery CLSC are scarce. The EV battery CLSC is particularly challenging in terms of the reusability of returns because used EV batteries cannot be reused for the original purpose, which complicates CLSC operations. This paper explores the interrelationship between manufacturer and remanufacturer, explaining the reasons why recycling is still underdeveloped, and suggests the possibility of enhancing remanufacturing profitability.

Thermo-magnetic convective flow analysis under the impact of thermal radiation for heat and entropy generation phenomena is an active research field for understanding the efficiency of thermodynamic systems in various engineering sectors. This study aims to examine the characteristics of convective heat transport and entropy generation within an inverted T-shaped porous enclosure saturated with a hybrid nanofluid under the influence of thermal radiation and magnetic field.

The mathematical model incorporates the Darcy-Forchheimer-Brinkmann model and considers thermal radiation in the energy balance equation. The complete mathematical model has been numerically simulated through the penalty finite element approach at varying values of flow parameters, such as Rayleigh number (Ra), Hartmann number (Ha), Darcy number (Da), radiation parameter (Rd) and porosity value (e). Furthermore, the graphical results for energy variation have been monitored through the energy-flux vector, whereas the entropy generation along with its individual components, namely, entropy generation due to heat transfer, fluid friction and magnetic field, are also presented. Furthermore, the results of the Bejan number for each component are also discussed in detail. Additionally, the concept of ecological coefficient of performance (ECOP) has also been included to analyse the thermal efficiency of the model.

The graphical analysis of results indicates that higher values of Ra, Da, e and Rd enhance the convective heat transport and entropy generation phenomena more rapidly. However, increasing Ha values have a detrimental effect due to the increasing impact of magnetic forces. Furthermore, the ECOP result suggests that the rising value of Da, e and Rd at smaller Ra show a maximum thermal efficiency of the mathematical model, which further declines as the Ra increases. Conversely, the thermal efficiency of the model improves with increasing Ha value, showing an opposite trend in ECOP.

Such complex porous enclosures have practical applications in engineering and science, including areas like solar power collectors, heat exchangers and electronic equipment. Furthermore, the present study of entropy generation would play a vital role in optimizing system performance, improving energy efficiency and promoting sustainable engineering practices during the natural convection process.

To the best of the authors’ knowledge, this study is the first ever attempted detailed investigation of heat transfer and entropy generation phenomena flow parameter ranges in an inverted T-shaped porous enclosure under a uniform magnetic field and thermal radiation.