Comparative Analysis Of Efficiency Research Articles

Land degradation assessment in South Punjab, Pakistan: a comparative analysis of rain use efficiency and weighted overlay methods

Land degradation assessment in South Punjab, Pakistan: a comparative analysis of rain use efficiency and weighted overlay methods

Исследование работы инверторной системы запуска дизельного двигателя при эксплуатации тепловоза 3ТЭ28

Purpose: carrying out operational tests of the start converter as a device of the preliminary diesel engine cranking of a diesel locomotive 3TE28 and the analysis of the obtained results. Methods: the functioning of the inverter starting system was studied within the framework of its operation as part of a diesel locomotive under different conditions of diesel engine starting (battery residual voltage, oil temperature) using a measuring complex and a set of additional sensors, as well as accumulation and analysis of the obtained measurement results. Results: operational tests of the inverter system of the start power plant on the diesel locomotive 3TE28 in locomotive depot “Tynda-Severnaya” were carried out. The circuit solutions and algorithms of the automatic control system of the inverter are verified. Comparative analysis of energy efficiency of inverter and starter-generator engine start systems is performed. Practical relevance: according to the results of operational tests the possibility of application of start converters for reliable diesel engine starts of diesel locomotives equipped with synchronous traction units instead of widespread nowadays starter-generator starting systems is confirmed. The developed technical solution can be duplicated on other series of locomotives, both newly developed and operated as part of their modernization or repair. The data accumulated in operation can be used for further improvement of the control system algorithms of the start converter.

Environmental Impacts of Transportation Electrification: A Comparative Analysis of Energy Efficiency and Pollution Reduction

The growing demand for energy has positioned transportation as a major driver of global energy consumption and environmental pollution. With increasing concerns about climate change, electrifying transportation has gained momentum as a critical solution for reducing emissions and improving energy efficiency. This paper focuses on assessing the environmental impact of transportation electrification by comparing the energy consumption and pollution levels of electrified systems with those of conventional transportation methods. The analysis is based on two major aspects: the utilization of electric power in various modes of transport and the transportation of electric power within the infrastructure. By reviewing recent data and studies, this paper demonstrates that electrified transportation significantly reduces both greenhouse gas emissions and other harmful pollutants while simultaneously improving energy conservation. The findings unveil the importance of adopting electrification to mitigate the negative environmental effects of the current transportation system. Additionally, the study suggests that electrifying transportation contributes to long-term sustainability goals, presenting a viable path forward in addressing environmental challenges and supporting global efforts toward a cleaner, more efficient future.

A low power design using FinFET-based 2N-N-2P adiabatic logic based 4 × 4 and 8 × 8 Reduced Complexity Wallace Tree Multiplier

ABSTRACT Multiplier circuits are essential components in the majority of arithmetic computations. In the VLSI industry, IC designers are increasingly concerned with ensuring low power consumption and high speed of components. From the various data processing processors; the Wallace Tree Multiplier (WTM) is one of the quickest multipliers for performing fast arithmetic functions. It is a powerful speed and strength multiplier. The adiabatic logic style is one method that is appealing for low-power electronics applications. The Reduced Complexity Wallace Tree Multiplier (RCWM) structure has the potential for area and power reduction. Here, present a FinFET-based 2N-N-2P adiabatic logic that uses fewer transistors and is more energy efficient than standard circuit schemes in this work. The ongoing scaling of MOSFETs to lower technology nodes has resulted in issues such as short-channel effects and increasing leakage currents. FinFETs can replace MOSFETs in this scenario because their gate structure completely encompasses the channel, a unique property that avoids the single-channel effect seen in MOSFETs. This article analyzes the effectiveness of energy recovery circuit designs using FinFETs that consume less energy. Performed a comparative analysis of the energy efficiency of FinFET-based 2N-N-2P, 2N2N2P, and Positive Feedback Adiabatic Logic (PFAL). The simulation results also validate the robustness and efficiency of the FinFET-based 2N-N-2P adiabatic logic circuit under varying process parameters in FinFET technology. The adiabatic logic removes all redundant logic operations present in the existing RCWM.

Integrating Ecosystem Service Assessment, Human Activity Impacts, and Priority Conservation Area Delineation into Ecological Management Frameworks

The comprehensive protection and restoration of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts is critical for enhancing ecological environmental quality and fulfilling the aspirations of ecological civilization in the modern era. Centered on the key project area of the Mountain-River Project within the Luohe River Basin of the Eastern Qinling Mountains, this study employs the InVEST model to assess spatiotemporal variations in habitat quality (HQ), water yield (WY), carbon sequestration (CS), and soil retention (SR) for the years 2000, 2010, and 2020. This study further examines the trade-offs and synergies among these ecosystem services, integrates the Ordered Weighted Averaging (OWA) and GIS methodology with human activity patterns, determines the optimal management scenario, and offers targeted recommendations for optimization. The findings reveal that areas of high habitat quality, carbon sequestration, and soil retention are predominantly concentrated in the western and southwestern regions of the basin, whereas high-value zones of water yield are primarily situated in the southern and southwestern sectors. Habitat quality demonstrates significant synergies with other ecosystem services, whereas water yield presents a notable trade-off with soil retention. By conducting a comparative analysis of protection efficiency, we identified priority conservation areas predominantly located in the southern and southwestern regions of the basin. Moreover, through overlaying the priority conservation zones with the Human Footprint Index (HFI), the priority conservation area was precisely delineated to encompass 5.41 × 105 hectares. This methodology provides critical guidance for the implementation of the Mountain-River Project and offers substantial value in scientifically advancing ecological restoration initiatives.

Comparative Analysis of Energy Efficiency in Conventional, Modular, and 3D-Printing Construction Using Building Information Modeling and Multi-Criteria Decision-Making

Energy efficiency has become a crucial focus with the growing attention on sustainable development and decreasing energy consumption in the built environment. Different construction methods are being applied worldwide, such as conventional, modular, and 3D-printing methods, to increase energy efficiency in buildings. This study aims to enhance the decision-making process by identifying optimal construction techniques, material selection, and ventilation window dimensions to promote sustainable energy use in buildings. A novel framework combining Building Information Modeling (BIM), computational analysis, and Multi-Criteria Decision-Making (MCDM) approaches is applied to assess the energy use intensity (EUI), annual electric energy consumption, and lifecycle energy cost across multiple sequences for each type of construction. Computational analysis in this research is combined in two main tools. Minitab is utilized for experimental design to determine the number and configurations of sequences analyzed. The Simple Additive Weighting (SAW) method, applied as an MCDM tool, is used to assess and rank the performance of sequences based on equally weighted criteria. Subsequently, 3D models of case study buildings are developed, and energy simulations are conducted using Autodesk Revit and Autodesk Green Building Studio, respectively, as BIM tools to compare the energy performance of various design alternatives. The results revealed that 3D printing surpassed other methods, where Sequence 7 achieved approximately 10.3% higher efficiency than modular methods and 40.5% better performance than conventional methods in the evaluated criteria. The findings underscore the higher energy efficiency of 3D printing, followed by modular construction as a competitive method, while conventional methods lagged significantly.

Comparative Analysis of Efficiency of Passive and Controlled Active Degassing Schemes of MSW Landfill

The disadvantages of existing technologies of landfill degassing are marked: at passive degassing there are no technological possibilities of biogas flow control in time at change of conditions of its formation in the process of biochemical fermentation and change of its chemical composition, and at active degassing of the landfill the volume of extracted gas from the body of the landfill cannot be significantly increased and accordingly the efficiency of technical methods at realization of the given method remains reduced. The technology of landfill degassing is proposed, which provides reduction of negative impact on the environment by controlling the flow rate and chemical composition of biogas emissions into the atmosphere, both during the operation of the landfill, and during the period of reclamation, and after it until the cessation of gas generation of the landfill body.

Comparative efficiency analysis of hashing algorithms for applications in zk-SNARK circuits in distributed ledgers

The paper presents a comparative efficiency analysis of hashing algorithms in terms of applicability in zk-SNARK based systems. We have considered the hash functions sha256, sha3, blake2, mimc and poseidon, which are most widely used in modern distributed ledgers. To conduct experiments with measuring parameters, an infrastructure based on the ZoKrates toolbox was developed. A series of measurements with different input data was carried out for each algorithm. The number of constraints in the R1CS representation of the algorithm, the length of the proof key and the verification key, the running time of the setup phase of the protocol, and the proof generation time were measured. Based on the obtained results, we determined the boundaries of the practical applicability of algorithms for the problem of proving the knowledge of the preimage of a hash function using zk-SNARK circuits in distributed ledgers, and also identified emerging efficiency problems.

Modelling the hydraulic performance of an array of centrifugal pumps operating under a variable pressure in a hydro-pneumatic energy storage system

Abstract The large pressure variation in hydro-pneumatic energy storage systems presents a major challenge for maintaining a high operating efficiency of the turbomachinery used in the hydro-electric energy conversion processes. This paper applies numerical modelling to compare the hydraulic performance of two pumping unit variants used for charging an offshore hydro-pneumatic energy storage (HPES) accumulator. The first unit consists of a single large centrifugal pump operated at variable speed while the second pumping unit is made up of an array of smaller, dynamically similar fixed-speed pumps. A number of series/parallel configurations for the latter option were derived in order to optimise the operational efficiency at various states of charge of a gas-charged accumulator, specifically between 80 and 200 bar. A comparative analysis of the operational hydraulic efficiencies for both pumping units shows that using an array of small fixed-speed pumps arranged in series/parallel configurations is more energy efficient than using a single large pump operated at variable speed.

Comparative Analysis of Organic Substrate Efficiency in Bio-hydrogen Production through Dark Fermentation

Comparative Analysis of Organic Substrate Efficiency in Bio-hydrogen Production through Dark Fermentation

A comparative analysis of the energy dissipation efficiency of various piano key weir types

Abstract Water levels in main or sub-channels can be controlled and regulated with the help of weirs. Piano key weirs (PKWs), a type of non-linear weir, include side crests, as well as front and back crests. Due to the fact that the PKW is a modern, newly installed infrastructure, several studies addressing the distribution of energy for each type are not yet available. This study examines the amount of energy dissipated for the four primary types, as well as the impact of altering the width ratio and the height ratio. To investigate the effects on energy dissipate, and compare the energy dissipate efficiency of the main types of PKWs, each type of PKW was created with five models using width ratios (W i/W o = 1.25, 1, and 0.8) and height ratios (P/L = 0.11 and 0.078). The energy dissipation depends on type of PKW and decreases as the width ratio increases by 5% and the energy dissipation increases, with the rise in the height ratio by 4%. Due to the overhang effect, type-C is the energy type that dissipates the most, making it the best example of PKW in terms of energy dissipation efficiency. Type-A follows type-C in this respect.

Comparative analysis of transient thermal behaviour and efficiency in longitudinal metal porous fin with combined heat and mass transfer under dehumidification conditions

This investigation explores the transient thermal characteristics of longitudinal porous fins made of Aluminium (Al) and Copper (Cu), exposed to a dynamic moist airstream under dehumidification conditions. Heat and mass transfer processes are initiated when the fin surface temperature falls below the dew point temperature of the surrounding air, driven by differences in temperature and humidity ratios. Heat transfer within the porous structure is modelled using temperature-dependent convective coefficients and Darcy’s flow model, with the governing nonlinear partial differential equation transformed into dimensionless form and solved using the Finite Difference Method (FDM) to analyse the fin thermal profile and efficiency over time. These results reveal that Cu fin due to their superior thermal conductivity exhibit higher temperature profile and efficiency compared to Al fin across all pertinent parameters. A key finding is the significant impact of Relative Humidity (RH) on the thermal behaviour of the fin: as RH increases by 400%, the temperature distribution from base to tip decreases by 138% in Al due to its higher specific heat capacity, which enables it to absorb more latent heat and 85% in Cu, where the superior thermal conductivity allows for faster heat dissipation. As Darcy number (Da) decreases by 99%, the temperature distribution along the fin from base to tip increases by 0.058% in Al due to its lower thermal conductivity and 0.041% in Cu, where its higher thermal conductivity enables more efficient heat dispersion. These insights are pivotal for advancing fin design and optimization, facilitating improved thermal management in industrial applications under transient and dehumidifying conditions.

Evaluating machine learning techniques for fluid mechanics: Comparative analysis of accuracy and computational efficiency

This study focuses on applying machine learning (ML) techniques to fluid mechanics problems. Various ML techniques were used to create a series of case studies, where their accuracy and computational costs were compared, and behavior patterns in different problem types were analyzed. The goal is to evaluate the effectiveness and efficiency of ML techniques in fluid mechanics and to contribute to the field by comparing them with traditional methods. Case studies were also conducted using Computational Fluid Dynamics (CFD), and the results were compared with those from ML techniques in terms of accuracy and computational cost. For Case 1, after optimizing relevant parameters, the Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM) models all achieved an R² value above 0.9. However, in Case 2, only the ANN method surpassed this threshold, likely due to the limited data available. In Case 3, all models except for Linear Regression (LR) demonstrated predictive abilities above the 0.9 threshold after parameter optimization. The LR method was found to have low applicability to fluid mechanics problems, while SVM and ANN methods proved to be particularly effective tools after grid search optimization.

Genetic Engineering in Bacteria, Fungi, and Oomycetes, Taking Advantage of CRISPR

Genetic engineering has revolutionized our ability to modify microorganisms for various applications in agriculture, medicine, and industry. This review examines recent advances in genetic engineering techniques for bacteria, fungi, and oomycetes, with a focus on CRISPR-Cas systems. In bacteria, CRISPR-Cas9 has enabled precise genome editing, enhancing applications in antibiotic production and metabolic engineering. For fungi, despite challenges associated with their complex cell structures, CRISPR/Cas9 has advanced the production of enzymes and secondary metabolites. In oomycetes, significant plant pathogens, modified Agrobacterium-mediated transformation, and CRISPR/Cas12a have contributed to developing disease-resistant crops. This review provides a comparative analysis of genetic engineering efficiencies across these microorganisms and addresses ethical and regulatory considerations. Future research directions include refining genetic tools to improve efficiency and expand applicability in non-model organisms. This comprehensive overview highlights the transformative potential of genetic engineering in microbiology and its implications for addressing global challenges in agriculture, medicine, and biotechnology.

Exergy Analysis of a District Heating System with a Predictive Model Based on Neural Network Algorithms

The article presents an exergy analysis of a district heating system (DHS) that incorporates a predictive model based on neural network algorithms. The study focuses on evaluating the thermodynamic efficiency of the DHS when these methods are applied, enabling the prediction of temperature changes and rapid adjustment of system parameters to enhance efficiency. The impact of increasing the number of connected consumers on the exergy efficiency of the DHS with the predictive model (DHPM) is examined. The use of neural network algorithms, such as LSTM, significantly enhances the system's ability to predict external temperature changes and respond promptly, resulting in optimized energy consumption and improved exergy efficiency, particularly at the beginning and end of the heating season. A comparative analysis of the exergy efficiency of traditional DHS and the system with the predictive model is included. The exergy analysis is based on modeling the system’s performance with varying numbers of consumers. The results indicate that an increase in the number of consumers leads to a rise in exergy efficiency due to better energy distribution management. The potential for significant thermal energy savings and reduced operational costs through the use of predictive methods is discussed. The study confirms that applying neural network algorithms in predictive models of DHS can substantially improve efficiency and reliability, leading to a more rational use of energy resources, cost reduction, and minimized environmental impact. The findings support the adoption of these methods in large-scale district heating systems for optimization and enhanced energy efficiency.

A Comparative Analysis of Efficiency and Losses in a 5 kW Hybrid and Full-SiC Converter, for PV Applications in Austria

Wide Bandgap (WBG) devices like SiC-MOSFETs have become quite popular in recent times due to their superior switching characteristics, high current carrying capability and temperature stability. They are being adopted for many different applications and for a wide range of power levels. For the case of PV applications, manufacturers are considering moving to SiC-based topologies due to higher converter efficiencies and improved power density. However, the present industry largely uses hybrid approaches (IGBT + SiC-diode) to optimize system cost. The aim of this paper is to present a fair comparison of an industry-grade hybrid converter with another similar counterpart where only the Si device has been replaced with the SiC device. The effects of such a direct replacement on the efficiency and losses of the converter are studied under various power ratings. Both converters consist of two stages—a boost converter and a three-phase three-level DC to AC converter. Simulation and experimental results comprehensively indicate a higher efficiency (improvements of up to 8 percent points) for the full-SiC converter, and this is more prominent at low input voltages, where the boost converter is active. However, the gains in efficiency are moderate for high input voltages (1 percent point at nominal voltage), where the boost converter is bypassed, and the losses are almost entirely attributed to the inverter. When set in the backdrop of the Austrian inverter market, the use of SiC devices in PV inverters has the potential for an estimated savings of 37.5 GWh/year in terms of loss reduction.

Comparative Analysis of Nitrogen Use Efficiency in Boro Rice under Long-term Inorganic and Organic Fertilization Practices

An experiment was conducted during Boro rice in the permanent experimental field of the Department of Soil Science, Bangladesh Agricultural University (BAU), Mymensingh to investigae the long term outcome of manure and fertilizers on the yield and Nitrogen Use Efficiency (NUE) of BRRI dhan29 in floodplain (Subtropical) soil (Aeric Haplaquepts). The experiment was designed in a randomized complete block design with three replications. There were ten treatment combinations viz, control; Nitrogen (N); (Nitrogen Phosphorus) NP; Nitrogen Potassium (NK); Nitrogen Phosphorus Potassium (NPK); Nitrogen Zinc (NZn); Nitrogen Sulphur (NS); Nitrogen Sulphur Zinc (NSZn), Nitrogen Phosphorus Potassium Sulphur Zinc (NPKSZn) and NPK+FYM. The yield contributing characters and yield of BRRI dhan29 significantly increased due to different treatments. Grain and straw yields were highly influenced by the application of nutrients in various combinations. The longest panicle length (25.3 cm), the highest 1000 grain weight (22.7 g), the maximum grain yield (6.29 t ha-1), the highest nitrogen uptake in grain (70.4 kg ha-1) were found for the NPKSZn treatment. Grain yield increased by 24.8%, 85.8%, 40.7%, 68.9%, 29.2%, 33.2%, 107.1%, 28.9% and 78.9% due to N, NP, NK, NPK, NS, NSZn, NPKSZn, NZn and NPK+FYM treatments respectively and the corresponding straw yields attainment by 49.6%, 51.1%, 82.0%, 95.3%, 37.8%, 34.4%, 82.7%, 41.8% and 90.2%. The maximum value of apparent nitrogen use efficiency was obtained with NPKSZn (54.06%) treatment which evidently suggested its resultness for the long term fertilized soil.

Comparative Analysis of Material Efficiency and the Impact of Perforations on Heat Sinks for Monocrystalline Photovoltaic Panel Cooling

In this research, the design and simulation of a heat sink for photovoltaic panels were carried out using aluminum and copper, the most commonly used materials in heat dissipation systems. This heat sink consisted of fins that were tested both perforated and non-perforated to improve heat dissipation efficiency. This research stems from the need to reduce the temperature of photovoltaic panels during operation, as scientific evidence shows that photovoltaic panels experience a decrease in efficiency as the temperature increases, taking as a reference the temperature under standard test conditions. The simulations of photovoltaic panels with aluminum and copper fins, both perforated and non-perforated, followed a rigorous methodology. For validation, the simulation results were compared with field data, yielding a mean absolute percentage error of 1.71%. The findings indicate that copper fins reduced the temperature of the photovoltaic panel by 2.62 K, resulting in a 1.31% increase in efficiency. Similarly, aluminum fins reduced the temperature by 2.10 K, with a 1.05% increase in efficiency. Perforated copper fins achieved a temperature reduction of 3.07 K, increasing efficiency by 1.54%, while perforated aluminum fins reduced the temperature by 2.49 K, contributing to a 1.25% increase in efficiency.

Perception of university social responsibility through the eyes of students: Comparative analysis of values, organisational efficiency, and educational process in Slovak universities

Perception of university social responsibility through the eyes of students: Comparative analysis of values, organisational efficiency, and educational process in Slovak universities

Comparative analysis of performance, efficiency, and resource usage between COMSOL Multiphysics and the MPh library of Python in the simulation of physical phenomena

MPh is a library of Python that makes possible to link the Python computer language with COMSOL Multiphysics. The use of the MPh library opens the possibility to save the computer resources employed when simulating physical phenomena and solving mathematical models and equations. In the Python command interpreter is possible to change or adjust some settings and parameters from the models created in COMSOL, and to execute the COMSOL kernel to solve those models. In this study, we compare the performance of COMSOL Multiphysics and the MPh library of Python when computing the magnetic field generated by a distribution of currents and ferromagnetic material. The metrics employed to do the comparison and the methodology to measure them are described, as well as the computer equipment where the programs ran. The results show that the execution time of the computations are similar in both software, but in the rest of the metrics, the execution in Python surpassed the execution in COMSOL. We showed that the MPh library of Python demands less CPU and RAM usage when solving the mathematical models and the files containing the solutions use less storage memory. As a conclusion, we propose the use of the MPh library of Python to improve the performance of the computer in charge of carrying out the calculations.