Energy Ratio Research Articles

Effect of Multiple Injection Strategy Under High Ammonia Ratio on Combustion and Emissions of Liquid Ammonia/Diesel Dual DI Engine

With the increasingly prominent environmental and energy issues, emission regulations are becoming more stringent. Ammonia diesel dual fuel (ADDF) engine is one of the effective ways to reduce carbon emissions. This study investigated the effect of multiple injection strategy on the combustion and emission characteristics of liquid ammonia/diesel dual direct injection (DI) engines through numerical simulation. The results showed that under the condition of maintaining the same pre injection diesel fuel and high ammonia energy ratio (80%), with the introduction of multiple injection, the peak cylinder pressure decreased and the peak phase advanced, the combustion start angle (CA10) advanced, the heat release showed a multi-stage pattern. The times of injection (TSOI) has a significant effect on combustion and emissions. As TSOI increased, ignition delay decreased, the combustion duration is shortened, and the combustion is accelerated. Notably, overall emissions of NOx and N2O have decreased, but the emissions of unburned NH3 have increased. Optimized the state of ammonia injection (SOAI) timing and ammonia injection pressure (AIP), showed that advancing SOAI timing and increasing AIP improved combustion. Advanced the SOAI timing to −8 °CA ATDC, resulted in a significant NOx emissions decrease with an increase in TSOI, reaching over 50%. Although increasing injection pressure can improve combustion, it also results in higher N2O emissions.

New geographic information system based sustainability metric for isolated photovoltaic systems

The integration of photovoltaic (PV) technologies is vital for achieving sustainable energy solutions in isolated systems. However, A critical challenge that remains is maintaining the sustainability of these systems under the fluctuating conditions of solar irradiance, which is key for isolated energy systems. This study hypothesizes that the sustainability of PV systems can be accurately assessed through a new metric that incorporates performance consistency, variability, and resilience, using real-time energy production data alongside GIS-based solar radiation models. By analyzing fixed PV, concentrated PV (CPV), and dual axis tracking PV (DATPV) systems over a three-year period (2017–2019), The analysis indicates that DATPV systems achieved the highest energy output, with energy ratios exceeding 300% in 2019, though this was accompanied by substantial variability in performance. Fixed PV systems demonstrated the most stable performance, with a consistency term reaching 0.93 and a sustainability score of 0.87 in 2019. CPV systems performed moderately, with a sustainability score of 0.66 in 2017. These results highlight the trade-off between energy capture and operational stability, which is critical for sustainable energy management in isolated systems.

Weak Fault Feature Extraction in Non-Gaussian Noise Interference Based on Adaptive Recombination Empirical Wavelet Transform Incorporated by Sparse Coding Shrinkage

Abstract The fast kurtogram (FK) is a very useful tool in the field of fault diagnosis, but it also contains two drawbacks. On one hand, its kurtosis indicator is susceptible to random impulse interference, leading to frequency band mis-selection. On the other hand, the frequency band division method determined by the tree filter bank may cause under or over decomposition problems. Therefore, in this paper a novel fault diagnosis theory is constructed combining the adaptive recombination empirical wavelet transform (AREWT) with the envelope spectral energy ratio (ESER). Adaptive decomposition of frequency bands is first performed using AREWT. Afterwards, the ESER is proposed as a statistical indicator to choose optimal demodulation frequency band which overcomes the effects of non-Gaussian noise interference and improves diagnostic accuracy. To further highlight the fault elements of the selected components, the adaptive sparse coding shrinkage algorithm (ASCS) is introduced to sparsely denoising sensitive components. Correspondingly, clear fault feature frequency components could be extracted from envelope spectrum. Finally, the practicability and superiority of proposed AREWT-ESER approach were fully validated through numerical simulation signal and case studies.

Bearing Fault Feature Extraction Method Based on Adaptive Time-Varying Filtering Empirical Mode Decomposition and Singular Value Decomposition Denoising

Aiming to address the difficulty in extracting the early weak fault features of bearings under complex operating conditions, a fault diagnosis method is proposed based on the adaptive fusion of time-varying filtering empirical mode decomposition (TVF-EMD) modal components and singular value decomposition (SVD) noise reduction. First, the snake optimization (SO) technique is used to optimize the TVF-EMD algorithm in order to determine the optimal parameters that match the input signal. Then, the bearing signal is divided into a number of intrinsic mode functions (IMFs) using TVF-EMD in order to reduce the nonlinearity and non-stationary characteristics of the fault signal. An index for the envelope fault information energy ratio (EFIER) is created to overcome the drawback of there being too many IMF components after TVF-EMD decomposition. The IMF components are ranked in descending order according to the EFIER, and they are fused according to the maximum principle of the energy ratio of envelope fault information until the optimal fusion component is determined. Finally, the fault feature is extracted when the optimal fusion component is denoised using SVD. Two measured bearing fault signals and simulation signals are used to validate the performance of the proposed method. The experimental findings demonstrate that the approach has good sensitive feature screening, fusion, and noise reduction capabilities. The proposed method can more precisely extract the early fault features of bearings and accurately identify fault types.

In-Depth Analysis of Photovoltaic-Integrated Shading Systems’ Performance in Residential Buildings: A Prospective of Numerical Techniques Toward Net-Zero Energy Buildings

The three categories of energy scarcity, population growth and environmental concerns explain the need for new energy sources. Saudi Arabia has become one of the regions capable of using solar energy, particularly through the use of photovoltaic systems, thanks to Saudi Arabia’s excellent ability to effectively utilize the sunlight. This study examines the performance of photovoltaic-integrated shading systems (PVIS) in enhancing energy efficiency for residential buildings under the extreme climatic conditions of Riyadh and Abha in Saudi Arabia. The study advances the knowledge of PVIS applications by addressing the dual challenges of energy efficiency and sustainability in urban residential settings. Leveraging numerical simulations conducted with EnergyPlus, the research evaluates various shading configurations, including louvers, horizontal and sidefin canopies, to quantify their impact on cooling, heating, lighting demands and energy production. The annual efficiency of the proposed integrated systems to achieve sustainable and net-zero energy buildings (NZEBs) is a key metric evaluated in this study. The key findings highlight the effectiveness of horizontal PVIS in achieving the highest energy efficiency, with up to 27.19% in Abha and 24.72% in Riyadh, based on the ratio of annual available solar energy to PV energy production. The integration of PVIS not only reduces the cooling loads by optimizing shading but also contributes significantly to renewable energy production toward NZEBs. The lifecycle cost analysis (LCCA) identifies horizontal canopies as the most cost-effective configuration, with a payback period of 8.6 years in Abha and 10.2 years in Riyadh.

Study on the Hydrogen Evolution Reaction of Reinforced Concrete during Electrochemical Repair under the Influence of BIEM.

Based on the bidirectional electromigration (BIEM) technique, a corrosion inhibitor solution was prepared by mixing 1 mol/L triethylene tetramine with deionized water. The effects of current density, charging time, and corrosion inhibitor on critical current density and hydrogen content of rebar were investigated. Subsequently, the hydrogen embrittlement risk of rebar was further characterized by mechanical property tests. Finally, the bearing capacity and crack distribution characteristics of the components during electrochemical repair were revealed based on the microstructure of the steel fracture. Studies have shown that the corrosion inhibitor in the BIEM electrolyte reduces the polarization potential, increases the critical current density, and finally inhibits the hydrogen evolution rate. The hydrogen evolution reaction increases with the increase of current density and energizing time. The critical hydrogen evolution current density of concrete specimens measured ranges from 0.796 to 0.833 A/m2. In addition, the current density range of 1-7 A/m2 has no effect on the yield strength, yield platform, and ultimate strength of steel. With the increase of 1 μg/g hydrogen content, the fracture energy ratio of steel bars decreases by 12.18%, and the sensitivity coefficient of hydrogen brittleness increases by 9.92%.

Pasteurized waste milk vs. milk replacer at the same crude protein:metabolizable energy ratio with different energy sources (fat vs. lactose) to pre-weaning Holstein calves: Effects on growth performance, feeding behavior, and health.

The improved growth performance of calves at weaning results from an effective pre-weaning feeding strategy. The type and pasteurization process of liquid feed are among the most variable feeding practices affecting calves' growth and health. In previous studies that compared waste milk (WM) vs. milk replacer (MR), little consideration has been given to the variations in chemical composition and feeding behavior between them, and there has been a lack of justification for the crude protein: metabolizable energy (CP:ME) ratio adopted. Hence, this study aimed to evaluate the effects of feeding pasteurized WM or MR differing in energy source (fat vs. lactose, respectively) with similar CP:ME ratio on intake, growth, feeding behavior, and health of newborn Holstein calves. Thirty-two male calves (4-d-old; 40.0 ± 0.58 kg BW) were assigned to the trial and randomly allocated to each liquid feed diet (WM or MR). Calves were housed in individual pens with free access to starter feed and fresh water. Calves were weaned on d 61 and assessed until d 101 as the postweaning period. WM-fed calves had greater total nutrient intake (DM, CP, EE, and ME), weight gain, final BW, skeletal growth parameters, and feed efficiency (d 30). Calves WM-fed sorted less against particles retained on the 2.36-mm sieve but more against particles retained on the sieve of 0.6 mm. In WM-fed calves, the sorting index decreased for feedstuff retaining on the bottom pan compared with MR-fed calves. Irrespective of the type of the liquid feed, all calves sorted for particles retaining on the sieve of 4.75 mm and the bottom pan, and against the particles that were retained on the sieves of 2.36- (MR-fed calves only), 1.18- and 0.6-mm. Starter feed nutrient intake and particle size intake from the sieves of 4.75-, 2.36-, and 1.18-mm increased in WM- vs. MR-fed calves. Eating rate and meal size but not meal frequency and length were greater in WM-fed calves, leading to higher pre- and post-weaning starter feed intake. Calves WM-fed spent less time eating and standing but more time ruminating and lying than MR-fed calves. Calves WM-fed had a lower likelihood of having elevated general appearance (score ≥2; hazard ratio = 2.79), diarrhea (score ≥3; hazard ratio = 1.35), and pneumonia (hazard ratio = 4.77). Calves WM-fed experienced shorter days with elevated general appearance, diarrhea, and pneumonia. Overall, feeding WM led to increased starter feed intake by boosting the eating rate and meal size, promoting greater growth than MR. Additionally, compared with MR, WM feeding increased time spent ruminating and lying and reduced susceptibility to diarrhea and pneumonia.

Efficiency evaluation of the milling process based on the granulometric analysis of crushed stone-mastic asphalt concrete granulate

Introduction. The working process of milling asphalt concrete pavements. The working process of asphalt concrete milling is considered as a set of destruction processes of the stone fraction, bitumen bonds and other phenomena unrelated to the formation of new surfaces. The conducted analysis is based on the assessment of the ratio of energy spent on milling in general and the energy needed for the formation of new surfaces made from separate fractions of asphalt concrete granulate and crushed stone aggregate.Materials and methods. The work is based on carried out experimental studies of the granulometric composition of asphalt concrete granulate obtained by milling crushed stone-mastic asphalt concrete pavement, and, separately, the stone fraction of asphalt concrete got by burning out a bitumen matrix. A standard method was also used to determine the specific energy of destruction of bitumen bonds when determining the fracture disruption resistance of a sample in tension while splitting.Results. As a result of sieving, granulometric curves of the composition of asphalt concrete granulate and stone fraction were obtained. Calculation methods have determined the components of energy consumption for the formation of new surfaces made from asphalt concrete granulate and new surfaces from stone fraction.Discussion and conclusion. At the end of the study, quantitative ratios of various fractions of asphalt concrete granulate of stone-mastic asphalt concrete formed during milling, as well as the crushing grade of stone fractions, were obtained. The specific energy consumption during the milling of asphalt concrete has been determined. It was found that the largest part of the energy during milling (64.7% for this study) is needed for the destruction of bitumen bonds. The vast majority of this energy is used for the formation of the fine granulate fraction. An insignificant part of the energy is spent on the destruction of the stone fraction. In general, the share of energy consumption aimed at the formation of new surfaces accounts for this study 66.14% of the total energy costs. The research development prospects of granulometric analysis for evaluating the effectiveness of the asphalt concrete milling process have been noted.

Enhanced waste-to-biomass conversion and reduced nitrogen emissions for black soldier fly larvae (Hermetia illucens) through modifying protein to energy ratio.

The appropriate protein to energy ratio (P/E ratio) has played a crucial role in maximizing waste-to-biomass conversion and minimizing nitrogen emissions. Black soldier fly larvae (Hermetia illucens, BSFL), capable of converting organic wastes into nutrient-rich biomass, it has the potential to become an innovative solution to reduce environmental impacts and optimize waste resource utilization. However, the appropriate P/E ratio for BSFL in the waste treatment process has remained unknown so far. This study utilized several common production chain residues to prepare diets with varying P/E ratios, to observe growth performance, nutritional components, fatty acid composition, fatty acid conversion, amino acid composition, waste-to-biomass conversion, and nitrogen emission levels of the BSFL. The results indicated that by adjusting the P/E ratio within the range of 9.79-17.8mg/kJ, biomass conversion increased from 8.79% to 11.60% (an increase of 31.97%), nitrogen conversion enhanced from 27.31% to 40.99% (an increase of 50.10%), while nitrogen emissions reduced from 2.69g to 0.48g (a reduction of 82.16%). Compared to other reported methods, adjusting the P/E ratio proved more effective and cost-efficient. The P/E ratio 11.67mg/kJ is relatively more suitable for using BSFL in organic waste treatment. Due to the significant variation in nitrogen levels within typical organic waste, our research findings advocate for the mixed treatment of multiple waste types to ensure the P/E ratio close to 11.67mg/kJ. The findings will provide new insights into the application of BSFL biotransformation technology in organic waste management.

Investigation of moisture content and higher heating value in refuse-derived fuel from agricultural residues using statistical modelling

<p>There is an increasing interest in using agricultural residues and wastes for energy production due to concerns regarding climate change and energy security issues. One of the alternative fuels considered is Refuse-derived fuel (RDF) from biomass, which has a Higher Heating Value (HHV) comparable to coal. This study aims to investigate the relationship between the moisture content and the HHV value. Palm kernel shells (PKS), coconut husks (CH), and coconut shells (CS) were blended at various ratios (10%–80%) and moisture levels (5%, 7%, 10%). The HHV was analyzed through a proximate analysis, with JMP Pro 17.0 modelling the HHV against the moisture content. Then, the Tukey-Kramer analysis identified the optimal energy ratio, thus providing insights into maximizing the RDF efficiency. The result showed that the highest HHV was 21.617 MJ/kg with the RDF2 formulation. Notably, the RDF2 energy content was less than 4% of that of coal, thus demonstrating the potential of utilizing agricultural waste to produce solid fuel with a positive environmental impact.</p>

Investigation on combustion and emissions of ammonia-diesel dual-fuel engine in relation to ammonia energy ratio and injection parameters

Investigation on combustion and emissions of ammonia-diesel dual-fuel engine in relation to ammonia energy ratio and injection parameters

Characteristic Energy Ratio Ramanujan-Gram: A Novel Optimal Multibands Demodulation Method

Characteristic Energy Ratio Ramanujan-Gram: A Novel Optimal Multibands Demodulation Method

A novel real-time structural acceleration-based methodology for detecting support loss under PCC pavement subjected to vehicle loading

ABSTRACT Support loss is a concealed distress in Portland cement concrete (PCC) pavements. This study proposes a real-time methodology to detect support loss under PCC pavements using structural acceleration responses. Full-scale tests were conducted under different support loss conditions. The sports utility vehicle (SUV), truck, and FWD were used. The results revealed that the main frequency of acceleration signals of PCC slabs under FWD and vehicle loads varied between 20~25 Hz and 10~15 Hz, respectively. When support loss occurs, both the acceleration amplitude and the signal energy within high-frequency range increase. By calculating the signal energy of acceleration response at slab corner (Scor) or longitudinal edge midpoint (Smid), support loss is indicated at slab corner when signal energy at Scor increases by about 90 times or signal energy at Smid increases by about 10 times. Additionally, by calculating the ratio of signal energy within high-frequency range to that within low-frequency range (ER) of acceleration signals at Smid, support loss at slab center is considered to have occurred when ER exceeds 3. To reduce costs, only one sensor can be placed at Smid. The proposed method has advantages of not requiring traffic closure, realizing real-time monitoring, and facilitating intelligent maintenance.

COVID-19 Implications on School Dietary Behavior in Chinese College Students: Based on the Longitudinal Assessment of Dietary Records from Intelligent Ordering System

Objectives: The coronavirus disease 2019 (COVID-19) pandemic has changed the dietary behavior of college students; however, the persistence of the changes in dietary behavior remains uncertain. This study aims to explore the changes in school food consumption and dietary quality of college students during three distinct COVID-19 periods: pre-epidemic (stage T1), epidemic (stage T2), and post-COVID-19 epidemic (stage T3). Methods: The persistent 6-year data, involving 3,484,081 dietary records from January 2018 to December 2023, for college students were acquired from the “Intelligent Ordering System (IOS)”. School food consumption and total energy intake of each college student per day were evaluated by information on three meals in the IOS combined with the corresponding food database of each dish. The school dietary quality of college students was evaluated by the Chinese Healthy Eating Index (CHEI). Results: In total, 459 college students were included in the T1 period, 530 in the T2 period, and 1316 in the T3 period. At stages T2 and T3, the energy, protein, and fat intakes of college students were higher than those at stage T1 (p < 0.001). Meanwhile, the breakfast energy ratio exhibited a significant decrease (0.27 vs. 0.25), while the lunch (0.37 vs. 0.38) and dinner (0.37 vs. 0.38) energy ratios exhibited varying degrees of increase (p < 0.001). After the COVID-19 pandemic, the components’ score of the CHEI for dark vegetables, red meats, and sodium showed an increase, while tubers exhibited a decrease (p < 0.01). Conclusions: This study provides compelling evidence of the significantly negative impact of the COVID-19 pandemic on school food consumption and dietary quality among Chinese college students. However, the duration of this effect may be limited. There was a certain degree of improvement in the food consumption and school diet quality of college students in China following the conclusion of the epidemic.

Performance Analysis of Desiccant Dehumidifier with an Expanded Regeneration Section

Temperature and humidity are critical parameters for maintaining the storage conditions and ensuring the post-harvest quality and shelf life of agricultural products. This study evaluates the performance of a desiccant dehumidifier under varying conditions to optimize storage environments. The relative humidity of the process air ranges from 60% to 90%, while the regeneration air temperature varies from 60°C to 80°C. The flow rates of process air and regeneration air are fixed at 350 m³/h and 760 m³/h, respectively. The relative humidity of the process air is reduced from 61%–91% at the inlet to 33.5%–48.75% at the outlet. During the experiment, the process air inlet temperature varies between 27.75°C and 36°C, while the regeneration air outlet temperature ranges from 37.75°C to 57.5°C. Performance parameters such as dehumidification effectiveness (η), moisture removal capacity (MRC), coefficient of performance (COP), and sensible energy ratio (SER) were analyzed. At 90% relative humidity and 80°C regeneration air temperature, a maximum dehumidification of 13.35 g/kg was achieved, whereas the lowest dehumidification of 5.5 g/kg was observed at 60% relative humidity and 60°C regeneration air temperature. These findings demonstrate the potential of the desiccant dehumidifier to maintain optimal temperature and humidity levels for prolonged shelf life and reduced post-harvest losses.

Non-destructive inspection of interfacial debonding in concrete-filled steel tube bridges

ABSTRACT Concrete-filled steel tube (CFST) structures are widely used in the construction of large-scale structures owing to its exceptional load-bearing capacity. However, inadequate construction quality and improper maintenance may cause debonding defects at the steel-concrete interface. Two non-destructive testing methods, i.e. the ultrasonic phased array (UPA) method and the impact acoustic method, are developed for deboning detection. A combined inspection procedure is proposed to balance the detection accuracy and efficiency, where the impact acoustic method is utilised for a rapid preliminary inspection to pinpoint the suspected debonding areas, while the UPA method is sequentially applied to accurately evaluate the debonding rates in the suspected areas. The impact acoustic method analyzes the time-frequency spectrum from the echo signals using wavelet transform, and calculates the vibration energy ratio for debonding detection. The UPA method applies the total focusing method for image reconstruction, and extracts the reflection coefficient at the steel–concrete interface for debonding evaluation. The laboratory experimental results show that the combined method possesses a high accuracy and accurately delineates the range of the debonding defect while preserving the detection efficiency. Field tests conducted on an arch bridge in Foshan, China, verified the effectiveness of the proposed evaluation method.

Sub-Alfvénic Turbulence: Magnetic-to-kinetic Energy Ratio, Modification of Weak Cascade, and Implications for Magnetic Field Strength Measurements

We study the properties of sub-Alfvénic magnetohydrodynamic (MHD) turbulence, i.e., turbulence with Alfvén mach number M A = V L /V A < 1, where V L is the velocity at the injection scale and V A is the Alfvén velocity. We demonstrate that MHD turbulence can have different properties, depending on whether it is driven by velocity or magnetic fluctuations. If the turbulence is driven by isotropic bulk forces acting upon the fluid, i.e., is velocity driven, in an incompressible conducting fluid we predict that the kinetic energy is MA−2 times larger than the energy of magnetic fluctuations. This effect arises from the long parallel wavelength tail of the forcing, which excites modes with k ∥/k ⊥ < M A. We also predict that as the MHD turbulent cascade reaches the strong regime, the energy of slow modes exceeds the energy of Alfvén modes by a factor MA−1 . These effects are absent if the turbulence is driven through magnetic fluctuations at the injection scale. We confirm our predictions with numerical simulations. Since the assumption of magnetic and kinetic energy equipartition is at the core of the Davis–Chandrasekhar–Fermi (DCF) approach to measuring magnetic field strength in sub-Alfvénic turbulence, we conclude that the DCF technique is not universally applicable. In particular, we suggest that the dynamical excitation of long azimuthal wavelength modes in the galactic disk may compromise the use of the DCF technique. We discuss alternative expressions that can be used to obtain magnetic field strength from observations and consider ways of distinguishing the cases of velocity and magnetically driven turbulence using observational data.

Energy Efficiency and Economic Viability of Mechanized and Conventional Cotton Production Systems under Rainfed Vertisols of Tamil Nadu

Energy efficiency is crucial for optimizing energy use, conserving resources, and assessing the input efficiency of agronomic practices. Cotton is known for its economic importance, thus many mechanized cultivation practices have been introduced. This study aimed to evaluate energy consumption and perform an economic analysis of mechanized and conventional cotton production under rainfed conditions in Tamil Nadu. The energy requirements for mechanized and conventional cotton cultivation were 17,001.1 and 15,456.0 MJ ha-1, respectively, with fertilizer application as the most energy consuming component of cotton cultivation in both the methods. Manual cotton cultivation proved to be labor-intensive, requiring 2,215.6 MJ ha-1 of labor energy, compared to just 174.2 MJ ha-1 in mechanized cultivation. Mechanization reduced labor needs by utilizing machinery such as power tillers for weeding and spindle-type cotton pickers for harvesting. In mechanized and conventional cotton cultivation, the contribution of direct, indirect, renewable, and non-renewable energy was 26.7%, 73.3%, 1.0%, 99.0%, and 24.4%, 75.6%, 14.3%, 85.7%, respectively. While the energy ratio, net energy gain, and energy productivity were higher in conventional methods, and mechanized cultivation had a higher specific energy. The total production cost for mechanized cultivation was Rs. 74,290 ha-1, which is 47.8% lower than conventional cultivation (Rs. 140,440 ha-1). Adopting mechanized practices could save Rs. 93,250 ha-1 in labor costs compared to conventional methods. Although the gross income from the Suraksha variety was 10.7% higher with conventional methods, the net income and benefit-cost ratio were greater with mechanized cultivation due to its lower total production costs. The study suggests that efforts to enhance cotton production's energy efficiency should focus on efficient fertilizer use, labor management, and reducing diesel fuel consumption by improving machinery performance.

Enhancing the efficiency of solar-powered water distillation units by utilization of waste heat

ABSTRACT Thermal water desalination is based on the evaporation and condensation of water, and such a process consumes a lot of energy, which lowers the economy of the process for commercial water desalination. The objective of this research is to improve the desalination energy efficiency of a novel domestic water desalination unit, which is based on thermal desalination, and this is done via utilization of the waste heat in the generated steam and reducing the operating costs. The distillation process begins with solar-powered evaporation of the salty water in the evaporator, followed by condensation of the generated water vapor coming from the evaporator over the cross-flow heat exchangers located in the condenser, which preheats the incoming saline water from the saltwater tank before it enters the evaporator. To assess the system's performance, comprehensive measurements are taken, including the electrical energy output from the PV panels and the volume of the output distilled water. Notably, the energy efficiency of the distillation is defined as the ratio of the heat energy gained by the distilled water, i.e. collected at the end of the day, to the electrical energy input to the electric heater, and it is found to be, on average, 82%.

Adaptive Clustering and Trust Aware Routing (ACTAR) for Wireless Sensor Networks in IoT Environments

ABSTRACTThe Internet of Things (IoT) has emerged as a revolutionary technology, connecting a vast number of people to the internet through various devices such as smartphones, laptops, sensors, and more. An essential component of IoT, the wireless sensor network (WSN), enables automation in processes like sensing, node monitoring, and data transmission. However, the full potential of IoT is hindered by cyber threats and unreliable communication. Although several security algorithms exist, they are not suitable for energy‐constrained sensor nodes. To address this issue, this paper proposes an energy‐efficient security mechanism called adaptive clustering and trust aware routing (ACTAR) for IoT‐WSNs. ACTAR operates in three phases: adaptive and hybrid clustering (AHC), multiobjective function‐based cluster head selection (MOCH), and trust aware routing (TAR). First, AHC utilizes a nonuniform clustering mechanism to categorize the network into nearby and distant clusters. Next, the selection of cluster heads is based on four metrics: coverage, communication cost, residual energy, and node proximity. Finally, TAR calculates the trust degree of sensor nodes by evaluating their direct and indirect behavior in terms of communication interactions and energy consumption. The node with the highest trust degree is selected as the next‐hop forwarding node, followed by the route with the highest trust degree. Extensive simulations of ACTAR demonstrate its performance in terms of malicious detection rate, false‐positive rate, residual energy, and packet delivery ratio. Comparative analysis shows that ACTAR outperforms existing methods, proving its superiority.