Reliability Prediction of Wrought Carbon Steel Castings under Fatigue Loading Using Coupled Mold Optimization and Finite Element Simulation

The fatigue life and reliability of wrought carbon steel castings produced with an optimized mold design are predicted using a finite element method integrated with reliability calculations.The optimization of the mold is carried out using MAGMASoft mainly based on porosity reduction as a response.After validating the initial mold design with experimental data,a spring flap,a common component of an automotive suspension system is designed and optimized followed by fatigue life prediction based on simulation using Fe-safe.By taking into consideration the variation in both stress and strength,the stress-strength model is used to predict the reliability of the component under fatigue loading.Under typical loading conditions of 70 kN,the analysis showed that 95%of the steel spring flaps achieve infinite life.However,under maximum loading conditions of 90 kN,reliability declined significantly,with only 65%of the spring flaps expected to withstand the stress without failure.The study also identified a safe load-induced stress of 95 MPa on the spring flap.The findings suggest that transitioning from forged to cast spring flaps is a promising option,particularly if further improvements in casting design reduce porosity to negligible levels,potentially achieving 100%reliability under typical loading conditions.This integrated approach of mold optimization coupled with reliability estimation under realistic service loading conditions offers significant potential for the casting industry to produce robust,cost-effective products.

A review on the parasitic isopod genus Notophryxus G.O.Sars,1883(Crustacea:Isopoda),and first report of Notophryxus globularis G.O.Sars,1885 from Lakshadweep Sea(Amini Island)

Isopod crustaceans of the family Dajidae are exclusively marine ectoparasites.The genus Notophryxus G.O.Sars,1883 currently includes nine nominal species,which are very rarely reported as the chances for encountering these specimens are unpredictable.Our comprehension of the taxonomy,biology,ecology,and life cycle of species belonging to the Notophryxus genus is notably lacking.All nominal species of Notophryxus genus are reviewed here to obtain a comprehensive and integrative taxonomic understanding of this genus,in an attempt to address the lacunae.This paper also documents the rediscovery of an ectoparasitic isopod from the genus Notophryxus in Indian waters,after 55 years.Adult isopod specimens obtained from the outer reefs of Amini Island in the Lakshadweep archipelago,Southeastern Arabian Sea,display morphological congruence to Notophryxus globularis G.O.Sars,1885.The only previous report on this species dates back to 1885 from G.O.Sars'description of N.globularis as an ectoparasite on the euphausiid Thysanoessa gregaria G.O.Sars,1883 in the North Pacific.This discovery represents a range extension of N.globularis from the North Pacific to the Arabian Sea.Two cryptoniscid larvae and three adult females of N.globularis(with dwarf males)were found attached to four adult mysid specimens of Siriella aequiremis Hansen,1910.The present study provides an improved diagnosis of N.globularis with the aid of light microscopy images and line drawings which was not given in the original G.O.Sars,1885 report.This research also provides a concise description of cryptoniscid larvae from the same sampling location and same host which is most likely to be N.globularis larvae.

Predictive modelling of volumetric and Marshall properties of asphalt mixtures modified with waste tire-derived char:A statistical neural network approach

The goals of this study are to assess the viability of waste tire-derived char(WTDC)as a sustainable,low-cost fine aggregate surrogate material for asphalt mixtures and to develop the statistically coupled neural network(SCNN)model for predicting volumetric and Marshall properties of asphalt mixtures modified with WTDC.The study is based on experimental data acquired from laboratory volumetric and Marshall properties testing on WTDCmodified asphalt mixtures(WTDC-MAM).The input variables comprised waste tire char content and asphalt binder content.The output variables comprised mixture unit weight,total voids,voids filled with asphalt,Marshall stability,and flow.Statistical coupled neural networks were utilized to predict the volumetric and Marshall properties of asphalt mixtures.For predictive modeling,the SCNN model is employed,incorporating a three-layer neural network and preprocessing techniques to enhance accuracy and reliability.The optimal network architecture,using the collected dataset,was a 2:6:5 structure,and the neural network was trained with 60%of the data,whereas the other 20%was used for cross-validation and testing respectively.The network employed a hyperbolic tangent(tanh)activation function and a feed-forward backpropagation.According to the results,the network model could accurately predict the volumetric and Marshall properties.The predicted accuracy of SCNN was found to be as high value>98%and low prediction errors for both volumetric and Marshall properties.This study demonstrates WTDC's potential as a low-cost,sustainable aggregate replacement.The SCNN-based predictive model proves its efficiency and versatility and promotes sustainable practices.

Unsteady Flow and Heat Transfer of a Casson Micropolar Nanofluid over a Curved Stretching/Shrinking Surface

We present the results of an investigation into the behavior of the unsteady flow of a Casson Micropolar nanofluid over a shrinking/stretching curved surface,together with a heat transfer analysis of the same problem.The body force acting perpendicular to the surface wall is in charge of regulating the fluid flow rate.Curvilinear coordinates are used to account for the considered curved geometry and a set of balance equations for mass,momentum,energy and concentration is obtained accordingly.These are turned into ordinary differential equations using a similarity transformation.We show that these equations have dual solutions for a number of different combinations of various parameters.The stability of such solutions is investigated by applying perturbations on the steady states.It is found that high values of the Micropolar and Casson parameters cause the flow to move more slowly.However,when compared to a shrunken surface,a stretched surface produces a greater Micro-rotation flux.

CO_(2)utilization in syngas conversion to dimethyl ether and aromatics:Roles and challenges of zeolites-based catalysts

Several studies have proven a strong correlation between global warming and CO_(2)emissions.Annually,38 billion tons of CO_(2)are approximately emitted into the atmosphere.Utilizing CO_(2)via chemical conversion to clean fuels and value-added aromatics can substantially contribute to controlling the problem.Considering the thermodynamic and environmental limitations of hydrogenation of CO_(2)alone to value-added aromatics and fuels,CO_(2)utilization has currently emerged as a promising and practical approach for the production of fuels and aromatics with simultaneous utilization of both CO and CO_(2)wastes.As such,the approach is economically preferable.CO_(2)could be converted directly to fuels by the hydrogenation process or as a part of a syngas mixture.Dimethyl ether(DME)is a clean fuel with a higher energy density,which could be used as a substituent for several fuels such as diesel.In the same vein,value-added aromatics such as benzene,toluene,and xylene(BTX)can be produced from a similar process.Herein,we report a review that collects the most recent studies for the conversion of CO_(2)to DME and aromatics via zeolite-based bifunctional catalysts.We highlighted the main routes for producing DME and aromatics,as well as thoroughly discussed the conducted studies on CO_(2)hydrogenation and CO_(2)-rich syngas utilized as feedstock for conversion to DME and aromatics.The CO_(2)hydrogenation mostly occurs through the methanol-mediated reaction route but is most often limited by low selectivity and catalyst deactivation,particularly in the utilization of CO_(2)alone for the reduction reaction.The review takes an overview of the progress made so far and concluded by identifying the roles and challenges of zeolite-based catalysts for CO_(2)utilization and conversion to DME and aromatics.Accordingly,despite the incredible growth the field received in the last couple of years,however,many research challenges and opportunities associated with this process are still abounded and required to be addressed.Special attention is required for the development of approaches to block diffusion of H2O through zeolite to suppress the excess formation of CO_(2)in CO_(2)-rich syngas hydrogenation to DME and aromatics,exceed the product distribution limits,and suppress catalysts deactivation.

Effective desalination and anti-biofouling performance via surface immobilized MWCNTs on RO membrane

Desalination is considered a viable method to overcome the issue of water scarcity either from waste water or seawater. For this purpose, this study employed a facile approach to develop surface immobilized oxidized-MWCNTs(o-MWCNTs) onto crosslinked polyvinyl alcohol(PVA) membrane. Firstly, modified polysulphone substrate was synthesized on to which crosslinked PVA layer was spread onto it. PVA layer act as active layer for surface immobilization of o-MWCNTs in varying concentration. The functional group analysis, morphology and roughness of membranes surface was conducted out using FTIR, SEM and AFM respectively. The results showed that modified membranes, immobilized o-MWCNTs enhanced the salt rejection(Na_(2)SO_(4)) upto 99.8%. After contacting with Escherichia coli and Staphylococcus aureus for 2.5 h the bacteria mortalities of the fabricated membrane could reach 96.9%. Furthermore, the antibiofouling tests showed that OP-MWCNTs(1-5) modified membranes have higher anti-biofouling property than the control membrane.

Implications of electrode modifications in aqueous organic redox flow batteries

Aqueous organic redox flow batteries(RFBs)exhibit favorable characteristics,such as tunability,multielectron transfer capability,and stability of the redox active molecules utilized as anolytes and catholytes,making them very viable contenders for large-scale grid storage applications.Considerable attention has been paid on the development of efficient redox-active molecules and their performance optimization through chemical substitutions at various places on the backbone as part of the pursuit for high-performance RFBs.Despite the fact that electrodes are vital to optimal performance,they have not garnered significant attention.Limited research has been conducted on the effects of electrode modifications to improve the performance of RFBs.The primary emphasis has been given on the impact of electrode engineering to augment the efficiency of aqueous organic RFBs.An overview of electron transfer at the electrode-electrolyte interface is provided.The implications of electrode modification on the performance of redox flow batteries,with a particular focus on the anodic and cathodic half-cells separately,are then discussed.In each section,significant discrepancies surrounding the effects of electrode engineering are thoroughly examined and discussed.Finally,we have presented a comprehensive assessment along with our perspectives on the future trajectory.

A Lightweight Intrusion Detection System Using Convolutional Neural Network and Long Short-Term Memory in Fog Computing

The Internet of Things(IoT)links various devices to digital services and significantly improves the quality of our lives.However,as IoT connectivity is growing rapidly,so do the risks of network vulnerabilities and threats.Many interesting Intrusion Detection Systems(IDSs)are presented based on machine learning(ML)techniques to overcome this problem.Given the resource limitations of fog computing environments,a lightweight IDS is essential.This paper introduces a hybrid deep learning(DL)method that combines convolutional neural networks(CNN)and long short-term memory(LSTM)to build an energy-aware,anomaly-based IDS.We test this system on a recent dataset,focusing on reducing overhead while maintaining high accuracy and a low false alarm rate.We compare CICIoT2023,KDD-99 and NSL-KDD datasets to evaluate the performance of the proposed IDS model based on key metrics,including latency,energy consumption,false alarm rate and detection rate metrics.Our findings show an accuracy rate over 92%and a false alarm rate below 0.38%.These results demonstrate that our system provides strong security without excessive resource use.The practicality of deploying IDS with limited resources is demonstrated by the successful implementation of IDS functionality on a Raspberry Pi acting as a Fog node.The proposed lightweight model,with a maximum power consumption of 6.12 W,demonstrates its potential to operate effectively on energy-limited devices such as low-power fog nodes or edge devices.We prioritize energy efficiency whilemaintaining high accuracy,distinguishing our scheme fromexisting approaches.Extensive experiments demonstrate a significant reduction in false positives,ensuring accurate identification of genuine security threats while minimizing unnecessary alerts.

An Optimization Approach of IoD Deployment for Optimal Coverage Based on Radio Frequency Model

Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread applications.However,deploying IoD for area coverage poses numerous limitations and challenges.These include interference between neighboring drones,the need for directional antennas,and altitude restrictions for drones.These challenges necessitate the development of efficient solutions.This research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges effectively.The primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhile minimizing interference between neighboring drones.In deployment problem,the interference increases as the number of deployed drones increases,resulting in bad quality of communication.On the other hand,deploying a few drones cannot satisfy the coverage demand.To accomplish this,an enhanced version of a concise population-based meta-heuristic algorithm,namely Improved Particle SwarmOptimization(IPSO),is applied.The objective function of IPSO is defined based on the coverage probability,which is primarily influenced by the characteristics of the antennas and drone altitude.A radio frequency(RF)model is derived to evaluate the coverage quality,considering both Line of Sight(LOS)and Non-Line of Sight(NLOS)down-link coverage probabilities for ground communication.It is assumed that each drone is equipped with a directional antenna to optimize coverage in a given region.Extensive simulations are conducted to assess the effectiveness of the proposed approach.Results demonstrate that the proposed method achieves maximum coverage with minimum transmission power.Furthermore,a comparison is made against Collaborative Visual Area Coverage Approach(CVACA),and a game-based approach in terms of coverage quality and convergence speed.The simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage and convergence speed.Comparisons validate the superiority of our approach over existing methods.To assess the robustness of the proposed RFmodel,we have considered two distinct ranges of noise:range1 spanning from−120 to−90 dBm,and range2 spanning from−90 to−70 dBmfor different numbers of UAVs.In summary,this research presents a cooperative decision-making approach for efficient IoD deployment to address the challenges associatedwith area coverage and achieves an optimal coveragewithminimal interference.

Decoding molecular mechanisms:brain aging and Alzheimer's disease

The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for centuries.The aging process alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as Alzheimer's disease.Beyond these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging brain.Understanding these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect cognition.This review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of Alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly Alzheimer's disease.

Potential of MXenes in Water Desalination: Current Status and Perspectives

MXenes,novel 2D transition metal carbides,have emerged as wonderful nanomaterials and a superlative contestant for a host of applications.The tremendous characteristics of MXenes,i.e.,high surface area,high metallic conductivity,ease of functionalization,biocompatibility,activated metallic hydroxide sites,and hydrophilicity,make them the best aspirant for applications in energy storage,catalysis,sensors,electronics,and environmental remediation.Due to their exceptional physicochemical properties and multifarious chemical compositions,MXenes have gained considerable attention for applications in water treatment and desalination in recent times.It is vital to understand the current status of MXene applications in desalination in order to define the roadmap for the development of MXene-based materials and endorse their practical applications in the future.This paper critically reviews the recent advancement in the synthesis of MXenes and MXene-based composites for applications in desalination.The desalination potential of MXenes is portrayed in detail with a focus on ion-sieving membranes,capacitive deionization,and solar desalination.The ion removal mechanism and regeneration ability of MXenes are also summarized to get insight into the process.The key challenges and issues associated with the synthesis and applications of MXenes and MXene-based composites in desalination are highlighted.Lastly,research directions are provided to guarantee the synthesis and applications of MXenes in a more effective way.This review may provide an insight into the applications of MXenes for water desalination in the future.

A review of pressure transient analysis in reservoirs with natural fractures,vugs and/or caves

A review of the pressure transient analysis of flow in reservoirs having natural fractures,vugs and/or caves is presented to provide an insight into how much knowledge has been acquired about this phenomenon and to highlight the gaps still open for further research.A comparison-based approach is adopted which involved the review of works by several authors and identifying the limiting assumptions,model restrictions and applicability.Pressure transient analysis provides information to aid the identification of important features of reservoirs.It also provides an explanation to complex reservoir pressuredependent variations which have led to improved understanding and optimization of the reservoir dynamics.Pressure transient analysis techniques,however,have limitations as not all its models find application in naturally fractured and vuggy reservoirs as the flow dynamics differ considerably.Pollard’s model presented in 1953 provided the foundation for existing pressure transient analysis in these types of reservoirs,and since then,several authors have modified this basic model and come up with more accurate models to characterize the dynamic pressure behavior in reservoirs with natural fractures,vugs and/or caves,with most having inherent limitations.This paper summarizes what has been done,what knowledge is considered established and the gaps left to be researched on.

ELASTIC MEMBRANE EQUATION WITH MEMORY TERM AND NONLINEAR BOUNDARY DAMPING:GLOBAL EXISTENCE,DECAY AND BLOWUP OF THE SOLUTION

In this paper we consider the Elastic membrane equation：with memory term and nonlinear boundary damping： Under some appropriate assumptions on the relaxation function h and with certain initial data, the global existence of solutions ：and a general decay for the energy are established using the multiplier technique. Also, ＇we show that a nonlinear source of polynomial type is able to force solutions to blow up in finite time even in presence of a nonlinear damping.

Biological Stability of Water-Based Cutting Fluids:Progress and Application

The application of cutting fluid in the field of engineering manufacturing has a history of hundreds of years,and it plays a vital role in the processing efficiency and surface quality of parts.Among them,water-based cutting fluid accounts for more than 90%of the consumption of cutting fluid.However,long-term recycling of water-based cutting fluid could easily cause deterioration,and the breeding of bacteria could cause the cutting fluid to fail,increase manufacturing costs,and even endanger the health of workers.Traditional bactericides could improve the biological stability of cutting fluids,but they are toxic to the environment and do not conform to the development trend of low-carbon manufacturing.Low-carbon manufacturing is inevitable and the direction of sustainable manufacturing.The use of nanomaterials,transition metal complexes,and physical sterilization methods on the bacterial cell membrane and genetic material could effectively solve this problem.In this article,the mechanism of action of additives and microbial metabolites was first analyzed.Then,the denaturation mechanism of traditional bactericides on the target protein and the effect of sterilization efficiency were summarized.Further,the mechanism of nanomaterials disrupting cell membrane potential was discussed.The effects of lipophilicity and the atomic number of transition metal complexes on cell membrane penetration were also summarized,and the effects of ultraviolet rays and ozone on the destruction of bacterial genetic material were reviewed.In other words,the bactericidal performance,hazard,degradability,and economics of various sterilization methods were comprehensively evaluated,and the potential development direction of improving the biological stability of cutting fluid was proposed.

Tribological Performance of Different Concentrations of Al_(2)O_(3)Nanofluids on Minimum Quantity Lubrication Milling

Nanofluid minimum quantity lubrication(NMQL)is a green processing technology.Cottonseed oil is suitable as base oil because of excellent lubrication performance,low freezing temperature,and high yield.Al_(2)O_(3)nanoparticles improve not only the heat transfer capacity but also the lubrication performance.The physical and chemical proper-ties of nanofluid change when Al_(2)O_(3)nanoparticles are added.However,the effects of the concentration of nanofluid on lubrication performance remain unknown.Furthermore,the mechanisms of interaction between Al_(2)O_(3)nanoparti-cles and cottonseed oil are unclear.In this research,nanofluid is prepared by adding different mass concentrations of Al_(2)O_(3)nanoparticles(0,0.2%,0.5%,1%,1.5%,and 2%wt)to cottonseed oil during minimum quantity lubrication(MQL)milling 45 steel.The tribological properties of nanofluid with different concentrations at the tool/workpiece interface are studied through macro-evaluation parameters(milling force,specific energy)and micro-evaluation parameters(surface roughness,micro morphology,contact angle).The result show that the specific energy is at the minimum(114 J/mm^(3)),and the roughness value is the lowest(1.63μm)when the concentration is 0.5 wt%.The surfaces of the chip and workpiece are the smoothest,and the contact angle is the lowest,indicating that the tribological proper-ties are the best under 0.5 wt%.This research investigates the intercoupling mechanisms of Al_(2)O_(3)nanoparticles and cottonseed base oil,and acquires the optimal Al_(2)O_(3)nanofluid concentration to receive satisfactory tribological properties.

Synthesis, characterization and electrochemical evaluation of anticorrosion property of a tetrapolymer for carbon steel in strong acid media

A novel tetrapolymer(TP) consisting of carboxylate, sulphonate, phosphonate and sulfur dioxide based comonomers was synthesized using Butler cyclopoymerization technique. The synthesized tetrapolymer was characterized using FTIR,1H-NMR,13CNMR and elemental analysis. The performance of the tetrapolymer as a corrosion inhibitor for St37 carbon steel in 15% HCl and 15% H2SO4 acid media was assessed using electrochemical impedance spectroscopy(EIS), linear polarization resistance(LPR), potentiodynamic polarization(PDP) and electrochemical frequency modulation(EFM) techniques. The influence of addition of a small amount of KI on the corrosion inhibition efficiency of TP was also assessed. Results obtained showed that the tetrapolymer moderately inhibited the corrosion of St37 steel in the acid media with protection efficiency of 79.5% and 61.1% at the optimum concentration of 1000 mg·L^-1 studied in HCl and H2SO4 media respectively. On addition of 5 mmol·L^-1 KI to the optimum tetrapolymer concentration, the protection efficiency was upgraded to 90.6% and 93.5% in HCl and H2SO4 environment, respectively. The enhanced performance of the polymer in the presence of KI is due to synergistic action deduced from synergism parameter(S1) which was found to be greater than unity.The tetrapolymer afforded the corrosion inhibition of St37 steel in the acid media by virtue of adsorption of the polymer molecules on the steel surface which was confirmed by ATR-FTIR analysis of the adsorbed film extracted from the steel surface. TP + KI formed complex with St37 steel surface in H2SO4 solution but not in HCl solution.

Molecular Simulation of Cement-Based Materials and Their Properties

Hydrated cement is one of the complex composite systems due to the presence of multi-scale phases with varying morphologies.Calcium silicate hydrate,which is the principal binder phase in the hydrated cement,is responsible for the stiffness,strength,and durability of Portland cement concrete.To understand the mechanical and durability behavior of concrete,it is important to investigate the interactions of hydrated cement phases with other materials at the nanoscale.In this regard,the molecular simulation of cement-based materials is an effective approach to study the properties and interactions of the cement system at the fundamental scale.Recently,many studies have been published regarding atomistic simulations to investigate the cement phases to define/explain the microscopic physical and chemical properties,thereby improving the macroscopic performance of hardened binders.The research in molecular simulation of cementitious systems involves researchers with multidisciplinary backgrounds,mainly in two areas:(1)cement chemistry,where the hydration reactions govern most of the chemical and physical properties at the atomic scale;and(2)computational materials science and engineering,where the bottom-up approach is required.The latter approach is still in its infancy,and as such,a study of the prevailing knowledge is useful,namely through an exhaustive literature review.This state-of-theart report provides a comprehensive survey on studies that were conducted in this area and cites the important findings.

Statistical prediction of waterflooding performance by K-means clustering and empirical modeling

Statistical prediction is often required in reservoir simulation to quantify production uncertainty or assess potential risks.Most existing uncertainty quantification procedures aim to decompose the input random field to independent random variables,and may suffer from the curse of dimensionality if the correlation scale is small compared to the domain size.In this work,we develop and test a new approach,K-means clustering assisted empirical modeling,for efficiently estimating waterflooding performance for multiple geological realizations.This method performs single-phase flow simulations in a large number of realizations,and uses K-means clustering to select only a few representatives,on which the two-phase flow simulations are implemented.The empirical models are then adopted to describe the relation between the single-phase solutions and the two-phase solutions using these representatives.Finally,the two-phase solutions in all realizations can be predicted using the empirical models readily.The method is applied to both 2D and 3D synthetic models and is shown to perform well in the P10,P50 and P90 of production rates,as well as the probability distributions as illustrated by cumulative density functions.It is able to capture the ensemble statistics of the Monte Carlo simulation results with a large number of realizations,and the computational cost is significantly reduced.

Synthesis and characterization of a series of cross-linked polyamines for removal of Erichrome Black T from aqueous solution

A new series of polymers comprising four terpolymers was synthesized via Mannich polycondensation of benzene1,4diamine,formaldehyde and piperazine by varying the benzene1,4diamine and piperazine ratio.The new polyamines(labeled Dipip)were characterized using 13C solidstate NMR,FTIR,TGA,DSC,XRD,SEM and EDX.The adsorptive performances of the synthesized polymers for Erichrome Black T(EBT)uptake from aqueous solution were investigated under batch process.Equilibrium,kinetic,and thermodynamic studies were conducted to determine the influence of different operational parameters of the adsorption process.The two most promising polymers among the series show an excellent EBT removal efficiency of~100%and~95%with high adsorption capacities of 775 mgg 1 and 917 mgg 1,respectively at a meager dosage of 5 mg.The sorption of EBT on the polymers was well described by RedlichPeterson&Langmuir model while the kinetic studies indicate that pseudosecond order model was followed.For the thermodynamic studies,the negative AG and positive AH values obtained suggest a spontaneity of the sorption process which was endothermic in nature.The results of reusability test of the resins were promising even at the fourth cycle,showcasing the potentials of the new polymers in dyes contaminated water treatment.

Experimental investigation of effect of refrigerant gases,compressor lubricant and operating conditions on performance of a heat pump

In the field of heat pumps,there are a number of parameters that affect the performance and efficiency of the apparatus,which have been the subject of studies by individual researchers in the literature.This study describes an experimental method in order to investigate the effects of some significant parameters on heat pump performance.In this regard,a laboratory heat pump setup has been utilized to operate in different working conditions for achieving an appropriate estimation to find out effects of mentioned parameters such as refrigerant type and charge amount,compressor oil viscosity,compressor cooling fan,secondary fluids temperature and flow rate.Different refrigerants have been selected and used as circulating fluid in the installed heat pump.Although this work has been devoted to a detailed attempt to recognize the effects of various parameters on the coefficient of performance(COP) value,an appropriate method has been carried out to survey the obtained results by using economic analysis.It was revealed that one of the main parameters is refrigerant charge amount which has a notable effect on COP.The temperature of the heat source was also tested and the performance of the system increased by more than 11% by employing mentioned modifications and various operating conditions.In addition,by selecting a low viscosity compressor oil,the system performance increased by 18%.This improvement is more than 6% for the case that cooling fan is installed to cool the compressor element.