• Energy Research

AbstractLignocellulosic biomass is a highly available and suitable candidate for biogas/biomethane production. However, high concentration of recalcitrant lignin is the major obstacle in successful anaerobic digestion (AD). The main aim of this review is to highlight the applications and challenges of lignocellulosic biomass in AD from the recent reports. Potential approaches to improve instabilities in mesophilic AD process (such as microbial communities' development, co‐digestion, biofilm carrier's addition, and essential nutrients supplement) were also reported. This review goes one more step deeper to discuss the key microbes involved in lignocellulosic biomass degradation. Biofilm carriers provide attached growth systems for microbes in AD and acts as redox mediators to accelerate the biotransformation of recalcitrant pollutants. Addition of nanoparticles (NPs) stimulate Firmicutes, Bacteroidetes, Methanosaeta, Methanobacterium, and Methanosarcina population which further improve biomethanation. The comprehensive study of these proposed strategies and microbial stimulation through additives would make the lignocellulosic biomethanation more feasible. © 2021 Society of Chemical Industry (SCI).

Abstract This study addresses environmental concerns related to sugarcane biomass as an industrial fuel source by exploring its potential for textile applications. Bagasse undergoes sequential alkali-H2O2 treatment, followed by varying concentrations of silicone softener (50 g l−1 − 100 g l−1 − 150g l−1). The goal is to enhance fiber fineness and softness. Comprehensive physical and chemical characterization reveals significant alterations in treated fibers, impacting surface morphology, crystallinity, linear density, and moisture regain. Results indicate a decline in fiber linear density from 59.47tex to 48.84tex, thus improved fineness, moisture regain initial from 6.9% to 4.7%, reduced crystallinity, and enhanced mechanical strength with silicone softener treatment. Treated fibers show promise as a sustainable alternative to conventional cotton, emphasizing the importance of sugarcane biomass for eco-friendly textile manufacturing.

Cyber-threats are becoming a big concern due to the potential severe consequences of such threats is false data injection (FDI) attacks where the measures data is manipulated such that the detection is unfeasible using traditional approaches. This work focuses on detecting FDIs for phasor measurement units where compromising one unit is sufficient for launching such attacks. In the proposed approach, moving averages and correlation are used along with machine learning algorithms to detect such attacks. The proposed approach is tested and validated using the IEEE 14-bus and the IEEE 30-bus test systems. The proposed performance was sufficient for detecting the location and attack instances under different scenarios and circumstances.

We investigate fluid flow and heat transfer in a channel obstructed by nail-shaped hurdles under forced convection using the Finite Difference Method. Due to the absence of an analytical solution, numerical techniques are employed. The channel is geometrically transformed into a rectangular configuration using curvilinear coordinates. Elliptic grid generation is used to discretize the domain. The Navier–Stokes equations are reformulated through the vorticity stream function formulation, and the Finite Difference Method incorporates a coordinate transformation approach. Effects of Reynolds numbers between (20≤Re≤600), Prandtl numbers (0.71,17.1), and nail spans (0.1≤h≤0.7) on velocity, temperature profiles is studied. Local and Average Nusselt numbers on Nail-shaped hurdle are also calculated. The observed maximum Nusselt numbers are 13.49,27.83, and 11.86 at Ra=600,Pr=7.1, and h=0.1, respectively Results show that higher Reynolds and Prandtl numbers increase Nusselt numbers, enhancing heat transfer. Narrower nail spans improve heat transfer efficiency.

<abstract> <p>Integrating Green Renewable Energy Sources (GRES) as substitutes for fossil fuel-based energy sources is essential for reducing harmful emissions. The GRES are intermittent and their integration into the conventional IEEE 30 bus configuration increases the complexity and nonlinearity of the system. The Grey Wolf optimizer (GWO) has excellent exploration capability but needs exploitation capability to enhance its convergence speed. Adding particle swarm optimization (PSO) with excellent convergence capability to GWO leads to the development of a novel algorithm, namely a Grey Wolf particle swarm optimization (GWPSO) algorithm with excellent exploration and exploitation capabilities. This study utilizes the advantages of the GWPSO algorithm to solve the optimal power flow (OPF) problem for adaptive IEEE 30 bus systems, including thermal, solar photovoltaic (SP), wind turbine (WT), and small hydropower (SHP) sources. Weibull, Lognormal, and Gumbel probability density functions (PDFs) are employed to forecast the output power of WT, SP, and SHP power sources after evaluating 8000 Monte Carlo possibilities, respectively. The multi-objective green economic optimal solution consisted of 11 control variables to reduce the cost, power losses, and harmful emissions. The proposed method to address the OPF problem is validated using an adaptive IEEE bus system. The proposed GWPSO algorithm is evaluated by comparing it with PSO and GWO optimization algorithms in terms of achieving an optimal green economic solution for the adaptive IEEE 30 bus system. This evaluation is conducted within the confines of the same test system using identical system constraints and control variables. The integration of a small SHP with WT and SP sources, along with the proposed GWPSO algorithm, led to a yearly cost reduction ranging from <bold>$\$$19,368</bold> to <bold>$\$$30,081</bold>. Simulation findings endorsed that the proposed GWPSO algorithm executes fruitfully compared to alternative algorithms regarding a consistent convergence curve and robustness, proving its potential as a viable choice for achieving cost-effective solutions in power systems incorporating GRES.</p> </abstract>

Safety and critical applications employ fault-tolerant control systems (FTCS) to increase reliability and availability in the event of a failure of critical components. Process facilities may employ these technologies to cut down on production losses caused by equipment failures that occur on an irregular or unscheduled basis. Air–fuel ratio (AFR) adjustment in the fuel system of internal combustion engines (ICE) is crucial for enhancing engine efficiency, saving fuel energy, and safeguarding the environment. This paper proposes a novel hybrid fault-tolerant control system (HFTCS) for controlling the AFR in ICEs that combines the features of both an active fault-tolerant control system (AFTCS) and a passive fault-tolerant control system (PFTCS). The fault detection and isolation (FDI) unit is designed using fuzzy logic (FL) as part of an AFTCS to give estimated sensor values to the engine controller when the sensor becomes faulty. Super-twisting sliding mode control (ST-SMC) is implemented as part of a PFTCS to maintain AFR by adjusting the throttle actuator in the fuel supply line under faulty conditions. Lyapunov stability analysis is also performed to make sure that the system remains stable in both normal and faulty conditions. According to the results in the Matlab/Simulink environment, the suggested system stays robust and stable during sensor faults. In faulty situations, it also maintains the AFR at 14.6 without any degradation, and a comparison with previous studies is carried out. The study shows that the suggested approach is an innovative and highly dependable solution for AFR control in ICEs, preventing engine shutdown and output loss for higher profitability.

The conventional open ponding system employed for palm oil mill agro-effluent (POME) treatment fails to lower the levels of organic pollutants to the mandatory standard discharge limits. In this work, carbon doped black TiO2 (CB-TiO2) and carbon-nitrogen co-doped black TiO2 (CNB-TiO2) were synthesized via glycerol assisted sol-gel techniques and employed for the remediation of treated palm oil mill effluent (TPOME). Both the samples were anatase phase, with a crystallite size of 11.09–22.18 nm, lower bandgap of 2.06–2.63 eV, superior visible light absorption ability, and a high surface area of 239.99–347.26 m2/g. The performance of CNB-TiO2 was higher (51.48%) compared to only (45.72%) CB-TiO2. Thus, the CNB-TiO2 is employed in sonophotocatalytic reactions. Sonophotocatalytic process based on CNB-TiO2, assisted by hydrogen peroxide (H2O2), and operated at an ultrasonication (US) frequency of 30 kHz and 40 W power under visible light irradiation proved to be the most efficient for chemical oxygen demand (COD) removal. More than 90% of COD was removed within 60 min of sonophotocatalytic reaction, producing the effluent with the COD concentration well below the stipulated permissible limit of 50 mg/L. The electrical energy required per order of magnitude was estimated to be only 177.59 kWh/m3, indicating extreme viability of the proposed process for the remediation of TPOME.

Owing to increased environmental awareness and the implementation of stringent governmental regulations, the demand for the valorization of natural fibers has increased in recent years. Sugarcane bagasse after juice extraction could be a potential source of natural fibers to be used in textile applications. In this paper, sugarcane bagasse is converted to textile fibers. Sugarcane fibers are extracted through alkali and H2O2 treatment with varying concentrations (6, 10, 14) g/L and (8, 12, 16) g/L, respectively. To soften the fibers for textile use, extracted fibers were post-treated with a constant ratio of silicone softener (50 g/L). Treatment of sugarcane fibers with varying concentrations of alkali–H2O2 significantly influenced the fiber surface morphology. Furthermore, an increase in the crystallinity of extracted fibers was observed, whereas a reduction in fiber linear density from 54.82 tex to 45.13 tex as well as moisture regain (6.1% to 5.1%) was observed as the ratio of alkali–H2O2 treatment was increased. A notable improvement in overall mechanical strength was achieved upon alkali–H2O2 treatment, but at a higher concentration (conc.) there was a loss of mechanical strength, and the torsional and flexural rigidity also increased significantly. Based on the results, sugarcane fibers treated with 10 g/L NaOH, 12 g/L H2O2 and 50 g/L silicone softener showed the most optimum results. These sustainable fibers have the potential to be used in textile applications due to their enhanced softness, optimum moisture regain, and better mechanical properties.