Process Optimization of Biodiesel Production Using the Laplacian Harris Hawk Optimization (LHHO) Algorithm

Abstract

Continuous power consumption from standard fuel resources is responsible for producing large-scale environmental greenhouse gases. Production of biodiesel fuels from the vegetable oils can be considered an alternative source. Effect of greenhouse gases can also be diminished. The production of biodiesel is done by a chemical process namely transesterification and usually maximized by using the Response Surface Methodology (RSM) tool. This paper presents a new approach to optimize the production of biodiesel by introducing a new variant of recently published metaheuristic Harris Hawk Optimization (HHO). The developed variant is based on the replacement of random numbers of normal distribution at the initialization phase by the random numbers generated from the Laplacian distribution. The proposed variant is named as the Laplacian Harris Hawk Optimization (LHHO) algorithm. The contribution of this paper is in twofold: firstly the performance of the proposed algorithm is verified over a well-known set of benchmark functions, and then, we applied the LHHO to maximize biodiesel production. Comparison of LHHO is carried out with five other recent metaheuristic algorithms. An optimization routine is formulated in the form of a single-objective function with a temperature, methanol to oil ratio, and catalyst concentration as the optimization variables. These parameters are optimized to maximize the production of biodiesel. The results obtained using the proposed LHHO show significant improvement as compared to other algorithms.

Hybrid MWCNT and TiO2 Nanoparticle-Suspended Waste Tyre Oil Biodiesel for CI Engines

“…Hence, in this investigation, alternate fuels like BWTPO with MWCNT nanoparticles of 300 ppm (BWTPO + MWCNT), BWTPO with TiO 2 nanoparticles of 300 ppm (BWTPO + TiO 2 ), BWTPO with MWCNT nanoparticles of 150 ppm and TiO 2 nanoparticles of 150 ppm (BWTPO + MWCNT and TiO 2 ), and 100% of BWTPO were prepared and characterized for fuel properties to ensure the fuel for supply and energy requirements (Table 1), and high cetane numbers 58 and 59 were found in nanofuels and hybrid nanofuels, respectively [25][26][27][28]. Te engine performance of nanofuels and hybrid nanofuels is as follows: BWTPO + MWCNT, BWTPO + TiO 2 , and BWTPO + MWC NT and TiO 2 have 13%, 10%, and 20% more brake thermal efciency, respectively.…”

Process Optimization, Kinetic Modelling and Characterization of Biodiesel Produced From Moringa Oleifera Oil: A Review

“…Sharma et al, [70] proposed a nature-inspired algorithm named Laplacian Harris Hawk Optimization (LHHO) to optimize biodiesel production instead of the well-known transesterification process.…”

Building a Digital Twin Simulator Checking the Effectiveness of TEG-ICE Integration in Reducing Fuel Consumption Using Spatiotemporal Thermal Filming Handled by Neural Network Technique

“…Additionally, ρ = 0.8917 is the pheromone trail evaporation rate, as shown in the first and second terms of Equation ( 13), which reflects the local and global updates of the pheromone in working hours t + 1 based on the solution of working hours t, respectively. The term ∆τ nl ≈ 0.0501 refers to the pheromone increment (the number of connected cracks' positions) and is expressed in Equation (14).…”

“…Peltier and Thomson's effects are also thermoelectric phenomena used in thermal measurements to achieve reversible thermal and electrical energy transformations and vice versa. The thermoelectric generators (TEG) work on the heat waste extracted from ICE generators or other sources that can absorb thermal energy [13,14] and track their behavior through the digital-twin simulator, which is fed by spatiotemporal thermal analysis films to guarantee steady-state electricity power generation. The main component in the TEG is the thermal conductors' legs, which must be better because of the impact on the generated electricity.…”