Loading Situations Research Articles

Enhancement of mechanical strength of miter joints in pultruded fiberglass/epoxy composite

Abstract In this research, we experimentally investigated how the shape of fittings affects the load-carrying capacity of miter joints in pultruded glass/epoxy composite frames. Specifically, three types of steel fittings – dovetail (D-shaped), H-shaped, and rectangular (U-shaped) were utilized to reinforce the miter joints in composite frames. Tension and compression tests were performed to assess the load-carrying capacity of these joint configurations. Additionally, finite element analysis (FEA) was employed to examine stress distribution patterns within the joint configurations, allowing us to make comparisons among the joint configurations in terms of their strength. The findings of the study demonstrated that all types of joint configurations successfully improved the joint strength, regardless of whether they were subjected to tensile or compressive loading conditions. Notably, H and D type steel fittings exhibited superior effectiveness in strengthening the adhesive miter joints when compared to U type steel fittings, particularly in tensile loading scenarios. Moreover, all types of steel fittings displayed promise as viable options for enhancing joint strength in compressive loading situations.

Correction of Thermal Errors in Machine Tools by a Hybrid Model Approach

Thermally induced position errors are one of the main error sources on the workpiece caused by the behavior of the machine tool. In today’s industrial environment, the correction of thermal errors is usually based on simple regression approaches, where the characteristic diagrams for correction are generated experimentally. The performance of these approaches is only valid for the corresponding load regimes, which often results in insufficient correction quality in practical applications. Consequently, there is only a limited benefit or even a deterioration in machine behavior if the correction characteristic is based on an inapplicable load case compared to the initial experiment. Simulation-generated characteristic diagrams using finite element models solve this disadvantage, but do not answer the question about the choice of the right characteristic matching the current load situation, and, in addition, calculate very slowly. Structural model-based correction using reduced models, on the other hand, calculates quickly, but requires a high modeling effort for accurate correction. The approach, presented in this contribution, combines simulation-generated characteristic diagrams and a structural model-based decision algorithm for a new hybrid model in order to select the appropriate characteristic diagram for the present load situation in the control system. This paper presents the simulative characteristic diagram generation by a finite element model validated by experiments in a climate chamber and a validated structural model including the concept for the decision algorithm.

Patient-specific mechanical analysis of PCL periodontal membrane: Modeling and simulation

This research fills a knowledge gap in bone tissue engineering by examining the mechanical characteristics of scaffolds at bone-tissue interfaces utilizing a cutting-edge technique involving the creation of 3D scaffolds from Polycaprolactone (PCL). The work employs Finite element analysis to measure the scaffolds' maximum principal and Von Mises stresses and strains. CT scans of the Maxilla and Mandible were used to apply load conditions to 3D models of the upper central incisor. In the derived computational model, four different load situations considered were: the masticatory load (70–100 N at 45°), two parafunctional habits (100–130 N) and 500–550 N at the incisal edge, both at 45°), and a trauma case (800–850 N applied perpendicularly from the inwards direction at 90°). The findings revealed that the central tooth region experiences the highest stress concentration, while the Maxilla and Mandible regions show the least stress. These results provide critical insights into the mechanical behavior of scaffolds at bone-tissue interfaces, suggesting a research direction for developing scaffolds that closely mimic real bone characteristics. The results of this study are particularly significant for using bone replacement materials, providing an approach to more effective healing options for bone traumas and degenerative bone disorders.

Reliability updating for lateral failure of historic quay walls

ABSTRACT The historic canal walls of Amsterdam, stretching 200 km in total, are constructed as a masonry wall on a timber deck supported by vertical timber piles. Understanding the resistance against lateral failure of these quays has been challenging due to uncertainties in their working principles, geometry, soil and structural properties. This paper proposes a Bayesian approach to include evidence from past loading situations and corresponding deformations into the reliability assessment. This approach enables refinement of the reliability predictions and parameter distribution uncertainties, leading to a more accurate prediction of the resistance against the lateral failure of historic quay wall. Depending on the type of evidence, an a-priori reliability prediction for a quay wall that fails to meet safety standards can be updated to any of the three consequence classes outlined in NEN8700. In a case study, a quay wall with an a-priori reliability of β = 1.5 has been increased to β = 3.2 by including evidence of an extreme survived load of 10 kN/m2 that resulted in displacements of less than 4 mm. This is a decrease in failure probability by two orders of magnitude, showing the potential impact of using observational information in combination with Bayesian updating.

The impact of perceptual complexity on road crossing decisions in younger and older adults

Cognitive abilities decline with healthy ageing which can have a critical impact on day-to-day activities. One example is road crossing where older adults (OAs) disproportionally fall victim to pedestrian accidents. The current research examined two virtual reality experiments that investigated how the complexity of the road crossing situation impacts OAs (N = 19, ages 65–85) and younger adults (YAs, N = 34, ages 18–24) with a range of executive functioning abilities (EFs). Overall, we found that OAs were able to make safe crossing decisions, and were more cautious than YAs. This continued to be the case in high cognitive load situations. In these situations, safe decisions were associated with an increase in head movements for participants with poorer attention switching than participants with better attention switching suggesting these groups developed compensation strategies to continue to make safe decisions. In situations where participants had less time to make a crossing decision all participants had difficulties making safe crossing decisions which was amplified for OAs and participants with poorer EFs. Our findings suggest more effort should be taken to ensure that road crossing points are clear of visual obstructions and more speed limits should be placed around retirement or care homes, neither of which are legislated for in the UK and Australia.

Novel Control System Based in DSPs for 800 kW Wind Power Station.

Wind energy conversion is a very mature technology. Its applications are widely accepted all over the world. Consequently, a tendency to erect more wind turbines can be observed. Therefore, wind turbines may gradually start to replace the output of conventional generators in the future, specially during low load situations with much wind. The wind power has a huge potential to supply electrical power without generating pollution. It has the potential to provide many countries with more of one-third of their electricity demand. A novel control system for a variable speed wind turbine generator has been developed in order to improve the wind turbine behaviour, the hardware is based in two digital signals processors (DSPs) in parallel operation, first one is a TMS320VC33, which manages all the signal analysis, control strategies, the protection systems and mechanical behaviour, and second one is a TMS320LF2407, that controls the PC monitoring program communication, the chopper and inverter PWM devices, temperature measures, encoders velocity and the programmable logic controller communication. The conjunction of the variable speed constant-frequency operation with the digital signal processors capacities improves cost and reliability, low Harmonic distortion (THD), stresses reduction in the drive train, turbine efficiency, audible noise minimization, mechanical design, active power production, reactive production or absorption (leading or lagging power factor) and control strategies (PWM, for example).

Three-dimensional theoretical model for effectively describing the effect of craniomaxillofacial structural factors on loading situation in the temporomandibular joint

BackgroundTemporomandibular joint (TMJ) overloading is considered a primary cause of temporomandibular joint disorders (TMD). Accordingly, craniomaxillofacial structural parameters affect the loading situation in the TMJ. However, no effective method exists for quantitatively measuring the loading variation in human TMJs. Clinical statistics, which draws from general rules from large amounts of clinical data, cannot entry for exploring the underlying biomechanical mechanism in craniomaxillofacial system. The finite element method (FEM) is an effective tool for analyze the stress and load on TMJs for several cases in a short period of time; however, it is difficult to generalize general patterns through calculations between different cases due to the different geometric characteristics and occlusal contacts between each case. Methods(1) This study included 88 subjects with 176 unilateral data to measure angle (α) of the distance to the plane of occlusion. The bone destruction score was evaluated for clinical statistics. To rule out effects of the potential factors and ensure the generality of the study, one participant with no obvious bone destruction was selected as the standard case for establishing the three-dimensional (3D) theoretical model and FEM. (2) Three groups of forces, including biting, muscles and joint reaction forces on mandible, were adopted to establish a 3D theoretical model. (3) By modifying the sagittal α and coronal three types of deviation angle (φ) of the original model, nine candidate models were obtained for the FEM studies. Results(1) The static equilibrium equations, were used to establish a 3D theoretical model for describing the loading of the TMJ. The theoretical model was validated by monotonously modifying the structural parameter in comparison to two-dimensional theoretical models reported previously; (2) The force on the TMJ gradually decreased with α, and this trend was validated by both clinic statistics and FEM results; (3) The effects of the three types of deviation angle were different. The results of the case where only rotating biting forces were considered was consistent with clinical statistics, indicating that the side with lower α experiences higher TMJ load. (4) Changing the unilateral proportionality coefficients of biting and muscle force produced opposite effects, wherein the effects of the muscle force were stronger than those of the biting forces. ConclusionsA negative correlation was observed between the joint load and α. Among the three types of asymmetric deformities, occlusal deviations were the primary factors leading to TMD. Unilateral occlusion can result in a greater load on the ipsilateral joint and should be avoided when using the side corresponding to the TMD. This study provides a theoretical basis for the biomechanical mechanism of TMD and also enables the targeted mitigation and treatment of TMD through structural modification.

MECHANICAL STIMULATION OF PIEZOELECTRIC SCAFFOLDS PROMOTES CELL OSTEOGENIC DIFFERENTIATION

Bone is a dynamic tissue that undergoes continuous mechanical forces. Mechanical stimuli applied on scaffolds resembling a part of the human bone tissue affects the osteogenesis [1]. Poly(3,4-ethylenedioxythiophene) (PEDOT) is a piezoelectric material that responds to mechanical stimulation producing an electrical signal, which in turn promotes the osteogenic differentiation of bone-forming cells by opening voltage-gated calcium channels [2]. In this study we examined the biological behavior of pre-osteoblastic cells seeded onto lyophilized piezoelectric PEDOT-containing scaffolds applying uniaxial compression.Two different concentrations of PEDOT (0.10 and 0.15% w/v) were combined with a 5% w/v poly(vinyl alcohol) (PVA) and 5% w/v gelatin, casted into wells, freeze dried and crosslinked with 2% v/v (3-glycidyloxypropyl)trimethoxysilane and 0.025% w/v glutaraldehyde. The scaffolds were physicochemically characterized by FTIR, measurement of the elastic modulus, swelling ratio and degradation rate. The cell-loaded scaffolds were subjected to uniaxial compression with a frequency of 1 Hz and a strain of 10% for 1 h every second day for 21 days. The loading parameters were selected to resemble the in vivo loading situation [3]. Cell viability and morphology on the PEDOT/PVA/gelatin scaffolds was determined. The alkaline phosphatase (ALP) activity, the collagen and calcium production were determined.The elastic modulus of PEDOT/PVA/gelatin scaffolds ranged between 1 and 5 MPa. The degradation rate indicates a mass loss of 15% after 21 days. The cell viability assessment displays excellent biocompatibility, while SEM images display well-spread cells. The ALP activity at days 3, 7 and 18 as well as the calcium production are higher in the dynamic culture compared to the static one. Moreover, energy dispersive spectroscopy analysis revealed the presence of calcium phosphate in the extracellular matrix after 14 days. The results demonstrate that PEDOT/PVA/gelatin scaffolds promote the adhesion, proliferation, and osteogenic differentiation of pre-osteoblastic cells under mechanical stimulation, thus favoring bone regeneration.

Bearing Health Evaluation Model using Segmentive Technique and Cosine KNN in Different Loading Situations

Bearing faults are a common cause of machinery failure, and bearing vibration analysis is critical in preventing any unacceptable consequences of such failures. Advancements in smart data and computing make Artificial Intelligence (AI) preferable for bearing vibration analysis. Typically, signal processing and feature engineering are essential for achieving satisfactory classification accuracy. Additionally, a drop in classification accuracy is commonly observed during different loading situations due to the vastly varying vibration characteristics under different loads. This paper evaluates an AI model in variable loading situations using raw vibration signals, devoid of signal processing and feature engineering. The proposed AI model, Segmentive Cosine K-Nearest Neighbours (SCosKNN), demonstrated a higher overall classification accuracy of 90.6–94.3% in same loading situations, and 72.1–84.2% in different loading situations. An improvement of around 9% in same loadings and 10–14% in different loadings were observed compared to a model without Segmentive Technique

A New Hybrid Supervisory Control System for Cabinet-Type Firebox Furnaces

In this paper, an intelligent hybrid Industrial Control System (ICS) and a Supervisory Control System (SCS) are proposed to improve the efficiency, safety, availability, and control capabilities of industrial furnaces. The main components of ICS are process control systems and advanced control systems that consist of overheating protection and load control. New soft sensors are designed as a combination of Laguerre filters and an artificial neural network to estimate the surface temperature of the furnace’s tubes, which allows the protection system to adjust fuel flow rate via overriding commands. Model-based fault detection systems are developed to detect faults in the combustion system and fouling in the furnace tubes and prepare features for the supervisory system. The supervisory control system is responsible for interfering between different components, evaluating the situation, and decision making based on the unit status and process conditions. An intuitionistic fuzzy inference system is employed as the core of the supervisory controller to tolerate disturbance and faults by switching the control modes. Test studies using experimental data of the furnace indicate the capability of the proposed monitoring and control system to operate in various loading situations and recover the system from abnormal conditions. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In petrochemical industries, several reports have been issued about the load reduction of fired-heater furnaces imposed by combustion system faults and emergency shutdowns to carry out un-planned repairs due to fouling and wax-formation in tubes. Different activities such as detecting abnormal conditions, identifying faults, and enforcing corrective action can be performed by operators through manual actions. This paper is focused on designing a new supervisory control system (SCS) to be able to recover the fired heater furnace from abnormal conditions and keep running the plant. The SCS evaluates the condition of the unit by acquiring information from main variables, sensors, actuators, operating status of components and utilities, and operator commands. By identifying the root cause of faults, SCS makes decision on recognizing hazard degree, raising alarms, and applying automatic corrective actions.

Design of Fibre-Reinforced Concrete Structures

Different types of concrete are invented in the past years, in order to improve it`s behaviour for different loading and environmental situations. Among them, fibre reinforced concrete (FRC) is one of the most recently developed concrete types. Design procedures for the FRC elements are included in only a few existing code provisions. Among them, fib Model Code 2010 (MC 2010) provides the biggest amount of necessary information and recommendations in order to design FRC elements. Yet, a lack of the guidelines for the design of elements loaded with different combinations of bending moment and axial force is noticed in the existing code provisions. Therefore, in the scope of this paper, interaction curves for FRC are developed. The interaction curves are developed for both, ultimate limit state (ULS) and serviceability limit state (SLS). Furthermore, example of the use of such interaction curves is given. Comparison in the design of reservoir made of reinforced concrete (RC) and FRC is performed. It is shown that the use of FRC especial benefits design according to SLS, as FRC provides better behaviour regarding crack spacing and crack width of element, while developed interaction curves for SLS significantly decrease the time necessary for such a design.

Comparative Analysis of Reinforced Concrete Structure with Traditional and Decoupled Masonry Infill Under Earthquake

Different types of concrete are invented in the past years, in order to improve it`s behavior for different loading and environmental situations. Among them, fibre reinforced concrete (FRC) is one of the most recently developed concrete types. Design procedures for the FRC elements are included in only a few existing code provisions. Among them, fib Model Code 2010 (MC 2010) provides the biggest amount of necessary information and recommendations in order to design FRC elements. Yet, a lack of the guidelines for the design of elements loaded with different combinations of bending moment and axial force is noticed in the existing code provisions. Therefore, in the scope of this paper, interaction curves for FRC are developed. The interaction curves are developed for both, ultimate limit state (ULS) and serviceability limit state (SLS). Furthermore, example of the use of such interaction curves is given. Comparison in the design of reservoir made of reinforced concrete (RC) and FRC is performed. It is shown that the use of FRC especial benefits design according to SLS, as FRC provides better behaviour regarding crack spacing and crack width of element, while developed interaction curves for SLS significantly decrease the time necessary for such a design.

Extreme resilience and dissipation in heterogeneous elasto-plastomeric crystals.

We present a microstructure-topology-based approach for designing macroscopic, heterogeneous soft materials that exhibit outstanding mechanical resilience and energy dissipation. We investigate a variety of geometric configurations of resilient yet dissipative heterogeneous elasto-plastomeric materials that possess long-range order whose microstructural features are inspired by crystalline metals and block copolymers. We combine experiments and numerical simulations on 3D-printed prototypes to study the extreme mechanics of these heterogeneous soft materials under cyclic deformation conditions up to an extreme strain of >200% with strain rates ranging from quasi-static (5.0 × 10-3 s-1) to high levels of >6.0 × 101 s-1. Moreover, we investigate the complexity of elastic and inelastic "unloading" mechanisms crucial for the understanding of shape recovery and energy dissipation in extreme loading situations. Furthermore, we propose a simple but physically intuitive approach for designing microstructures that exhibit a nearly isotropic behavior in both elasticity and inelasticity across different crystallographic orientations from small to large strains. Overall, our study sets a significant step toward the development of sustainable, heterogeneous soft material architectures at macroscopic scales that can withstand harsh mechanical environments.

L-M Based ANN for Predicting the Location of DG under Contingency Condition

The continuing monitoring of online voltage stability and the increased loadability of the transmission lines for the existing electrical power system are the two major challenges that today's energy management systems must deal with. As a result, evaluating online voltage stability under various loading situations is extremely challenging and time-consuming. The line voltage stability indices using an Artificial Neural Network (ANN), the system describes online voltage monitoring and warns the operator before voltage dips. The simulation's findings show that the proposed system may boost system loadability while also lowering the cost of installing an electrical power system and guaranteeing the security of power system operation.

Effects of open and minimally invasive Transforaminal Lumbar Interbody Fusion (TLIF) surgical techniques on mechanical behaviour of fused L3-L4 FSU: A comparative finite element study

For predicting the biomechanical effects of the fusion procedure, finite element (FE) analysis is widely used as a preclinical tool. Although several FE studies examined the efficacies of various fusion surgical techniques, comparative studies on Open and minimally invasive (MIS) transforaminal lumbar interbody fusion (TLIF) procedures incorporating a follower coordinate system have not been investigated yet. The current FE study evaluates the ranges of motion (ROM) and load distributions of Open-TLIF and MIS-TLIF implanted models, under physiological loading such as compression, flexion, extension and lateral bending. The most noteworthy finding from the investigation is that both the fusion procedures significantly reduced the ROMs of the implanted segment (L3-L4) and full model (L1-L5) by at least 89 % and 44 %, respectively, compared to the intact model. For all loading situations, over 95 % of the implanted models' cancellous bone volume was subjected to von Mises strains ranging from 0.0003 to 0.005. The maximum von Mises strain was observed to be localized on a small amount of cancellous bone volume (<5 %). The likelihood of adjacent segment degeneration is higher in the case of MIS-TLIF due to the higher stress (22–53 MPa) and strain (0.018–0.087) noticed on the upper facet of the L3 vertebra.

Structure design and tribological properties of Cu–SiC foam ceramic composites

Tribological properties at high temperature are an important research aspect for high speed or heavy load situation. This paper is to study the structure effects on the tribological properties of Cu–SiC foam ceramic (SiCf) composites at high temperature. Cu-SiCf composites form two interconnected three-dimensional (3D) network structure, which tribological properties could be controlled by designing SiCf ceramic volume fractions, friction components and mesh size. The results showed that SiCf ceramic has overall enhancement mechanism to Cu alloy and friction components by 3D-structure. Additionally, Cu-SiCf composites have friction properties of high temperature resistance, low wear rate, and stable coefficient of friction (COF).

Monitoring system for the construction of buildings in the area of mining exploitation impact

Observations of building structures in mining areas, reveal the occurrence of periodic and permanent excessive loading situations. These include ground deformations associated with the extraction of underground mineral deposits. In urban areas, these deformations significantly alter the operating conditions of building structures. For this reason, forecasts of ground transformation and analyses of possible changes in the technical condition of buildings on the ground surface are made in advance, even before mining is commenced. Taking into account previous in-house experience of the observed effects of mining impacts on building structures, an original method of monitoring changes in the condition of these structures has been developed. The aim of the monitoring is to record phenomena that change the operating conditions of the structures. In the developed method, measurements are made quasi-continuously using strain and deflection sensors mounted directly on structural elements. In the mining area affected by the mining operation being carried out in the years 2020 - 2022, and with a further one planned in the years 2023 - 2024, through the extraction of 14 coal parcels, three public utilities of special interest were monitored. The measurement results of deformation changes in the elements allow for an assessment of changes in the stress state of the structures, and the integration of sensors mounted on the structures into a wireless network fulfils the demands for maintaining public safety conditions in mining areas. It also contributes to the analysis of fatigue issues in masonry structures due to long-term multidirectional loads.

Robust energy storage system for stable in wind and solar

Energy storage systems (ESS) have become a conspicuous research hotspot since they store power and supply it during peak hours. Existing storage systems must be replaced by advanced energy storage with improved performance, energy management, and a control interface due to issues with size, dependability, and charging/discharging. The suggested robust energy retention system uses a battery and a super-capacitor to generate power from wind and solar energy. A Multiport DC converter with a buck-boost capacitor is used to properly discharge the stored energy to DC loads via a DC bus. The inverter is then delivered to a Power Flow Controller (PFC) and a Voltage Source Inverter (VSI). The Gravitational Search Algorithm (GSA) method optimizes the power controller settings based on the fluctuation of the system's active and reactive power. The optimization method ensures improved power flow while dealing with the least amount of power variance in imbalanced load situations. Based on the power variation, the proposed method generates appropriate control signals for the inverter system. The covers convert the inverter and reduce harmonics with a controller. Furthermore, the inverter AC supplied to the AC bus is converted into reactive power by an inductive load, and unwanted signals and harmonics are extracted using a Cascaded C-type filter. As a result, the described method has preserved total harmonic distortion, electrical efficiency, and finer transient stability.

Dynamic Power Consumption in Base Transceiver Station in Urban and Rural Setting in Awka, Nigeria using Multi-Attribute Decision-Making Technique

The goal of this paper was to lower base transceiver station (BTS) dynamic power consumption. A multi-attribute decision-making technique was implemented that reflects the stochastic nature of cellular networks and guarantees cost-effective traffic generation and improved BTS power consumption performance. Every related candidate or attribute that is taken into consideration to help reduce power consumption is given a utility function, and the candidate with the highest utility value is chosen to meet the target. The Utility function that the Technique selects is the weighted sum of the normalized attributes. In contrast to the works of other authors, which lowered consumption by 20%, the developed dynamic power consumption model cut consumption to 25.14 percent. The two BTS of interest were measured, and the results showed that Mgbakwu BTS has two Peak (Busy) Hour periods: in the morning, 9.55Erlangs from 7.30am to 8.30am, and in the evening, 10.7Erlangs from 8.30pm to 9.30pm. The BTS is located in a rural/residential area. The BTS measurement and analysis for the UNIZIK temporary site revealed that it is located in a commercial/business setting with a morning peak (busy) hour period of 19.1 Erlangs between 10 and 11 a.m. 14.6 Erlangs is the afternoon peak hour, which runs from 3.30 to 4.30 p.m. The traffic generated in the BTS under various load situations is reflected in the relevant Power Consumption for both BTS.

Economic analysis and TOPSIS approach to optimize the CI engine characteristics using span 80 mixed carbon nanotubes emulsified Sapindus trifoliatus (soapnut) biodiesel by artificial neural network prediction model

The rise in fuel use within the vehicle sector leads to a corresponding escalation in energy demand. To achieve optimal operating conditions, it is necessary to reduce energy usage. For that, the primary objective of this study is to utilize an artificial neural network (ANN) and the optimization approach as a technique for order performance by similarity to the ideal solution (TOPSIS) to forecast the optimal features of a compression ignition (CI) engine. The experiment was performed with a four-stroke mono-cylinder compression ignition (CI) engine under different load situations. The study considers six operational parameters, including brake thermal efficiency (BTE), specific fuel consumption (SFC), as well as emission characteristics including carbon monoxide (CO), hydrocarbon (HC), Nitrogen oxides (NOx), and smoke. From the ANN results, the correlation coefficients for BTE, SFC NOx, smoke, HC, and CO were 0.9712, 0.9862, 0.964, 0.941, 0.998, and 0.978, respectively. The SNBD25 + 30 mg/L SP80 + 30 mg/L CNT blend exhibited the maximum closeness coefficient under various load conditions. The maximum closeness coefficient obtained from the TOPSIS optimisation approach under full load conditions is 0.982386. From the result of the ANN prediction technique, for TOPSIS optimised blend SNBD25 + 30 mg/L SP80 + 30 mg/L CNT a 13.84% increase in BTE, 11.21% decrease in SFC, 16.67% decrease in CO, 13.87% decrease in NOx, 19.23% decrease in HC, and 32.53% decrease in smoke. Based on the outcomes obtained from the ANN and TOPSIS methodologies, it can be concluded that the SNBD25 + 30 mg/L SP80 + 30 mg/L CNT blend exhibits superior performance in terms of reduced NOx emissions and enhanced efficiency, surpassing the other blends under consideration. The incorporation of carbon nanotubes (CNTs) into a system leads to an increase in the carbon-to‑oxygen ratio, resulting in a reduction in the generation of nitrogen oxides (NOx). The cost of a mixture consisting of SNBD25 + 30 mg/L SP80 + 30 mg/L blend is 20% lower than the cost of diesel on a per-litre basis.