Developing a novel big dataset and a deep neural network to predict the bearing capacity of a ring footing

The accurate prediction of the bearing capacity of ring footings,which is crucial for civil engineering projects,has historically posed significant challenges.Previous research in this area has been constrained by considering only a limited number of parameters or utilizing relatively small datasets.To overcome these limitations,a comprehensive finite element limit analysis(FELA)was conducted to predict the bearing capacity of ring footings.The study considered a range of effective parameters,including clay undrained shear strength,heterogeneity factor of clay,soil friction angle of the sand layer,radius ratio of the ring footing,sand layer thickness,and the interface between the ring footing and the soil.An extensive dataset comprising 80,000 samples was assembled,exceeding the limitations of previous research.The availability of this dataset enabled more robust and statistically significant analyses and predictions of ring footing bearing capacity.In light of the time-intensive nature of gathering a substantial dataset,a customized deep neural network(DNN)was developed specifically to predict the bearing capacity of the dataset rapidly.Both computational and comparative results indicate that the proposed DNN(i.e.DNN-4)can accurately predict the bearing capacity of a soil with an R2 value greater than 0.99 and a mean squared error(MSE)below 0.009 in a fraction of 1 s,reflecting the effectiveness and efficiency of the proposed method.

Synthesis, Crystal Structure and Theoretical Calculations of N-Benzyl-1-(5-(3-chlorophenyl)-1,3,4-oxadiazol-2-yl)cyclopentanamine

N-benzyl-1-（5-（3-chlorophenyl）-1,3,4-oxadiazol-2-yl）cyclopentanamine was synthesized via one-pot reaction of appropriate benzylamine, cyclopentanone,（N-isocyanimino）triphenylphosphorane and m-chlorobenzoic acid. The quantum theoretical calculations for crystal structure were performed by density functional theory（DFT/B3LYP/6-311＋G＊）. From the optimized structure, geometric parameters were obtained and experimental measurements were compared with the calculated data. Frontier molecular orbitals（FMOs）, total density of states（DOS）, molecular electrostatic potential（MEP）, molecular properties, natural charges, NMR parameters and NBO analysis for the product were investigated by theoretical calculations.

Deep Transfer Learning Techniques in Intrusion Detection System-Internet of Vehicles: A State-of-the-Art Review

The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)technology.The functional advantages of IoV include online communication services,accident prevention,cost reduction,and enhanced traffic regularity.Despite these benefits,IoV technology is susceptible to cyber-attacks,which can exploit vulnerabilities in the vehicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and vehicle immobilization.This paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of Vehicles(IDS-IoV)based on anomaly detection.IDS-IoV leverages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by cyber-attacks.These systems can autonomously create specific models based on network data to differentiate between regular traffic and cyber-attacks.Among these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational complexity.We evaluate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and stability.This review highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-IoV systems.By examining recent advancements,we provide insights into how DTL can effectively address cyber-attack challenges in IoV environments,ensuring safer and more efficient transportation networks.

Damping controller design based on FO-PID-EMA in VSC HVDC system to improve stability of hybrid power system

Wind energy sources have different structures and functions from conventional power plants in the power system.These resources can affect the exchange of active and reactive power of the network.Therefore,power system stability will be affected by the performance of wind power plants,especially in the event of a fault.In this paper,the improvement of the dynamic stability in power system equipped by wind farm is examined through the supplementary controller design in the high voltage direct current(HVDC)based on voltage source converter(VSC)transmission system.In this regard,impacts of the VSC HVDC system and wind farm on the improvement of system stability are considered.Also,an algorithm based on controllability(observability)concept is proposed to select most appropriate and effective coupling between inputs-outputs(IO)signals of system in different work conditions.The selected coupling is used to apply damping controller signal.Finally,a fractional order PID controller(FO-PID)based on exchange market algorithm(EMA)is designed as damping controller.The analysis of the results shows that the wind farm does not directly contribute to the improvement of the dynamic stability of power system.However,it can increase the controllability of the oscillatory mode and improve the performance of the supplementary controller.

Converting circular tubes into square cross-sectional parts using incremental forming process

Incremental forming process is recently developed to form tubular parts.The fabrication cost and accuracy could be optimized if the effects of process parameters and the optimum values are specified.The aim of this research is using incremental forming of copper tubes to convert a circular tube into a square cross-sectional part.An experimental setup,consisting of a spherical forming punch and a fixture for clamping the tube is designed.The forming punch movement is controlled by a CNC machine.Full factorial design of experiments is carried out in order to determine the effects of process parameters including linear velocity,radial feed,and axial feed of the tool on the thinning ratio and the maximum outer diameter of the square cross-sectional parts.Results show that the radial feed has the major influence on the thinning ratio,while the axial feed plays the major role for the final profile.Increase of radial feed results in higher thinning ratio,and decrease of axial feed results in better shape conformity.Linear velocity does not have a significant effect on thinning ratio.Regression models are also given for predicting the determined responses.

Differentiation of Fungal Destructive Behaviour of Wood by the White-Rot Fungus Fomes fomentarius by MALDI-TOF Mass Spectrometry

There are many methods to identify and recognize the molecular and behavioural differences between organisms.One of the methods for the detection and identification of unknown organisms as well as intermolecular and intramolecular structural differences is MALDI-TOF mass spectrometry.Therefore,differentiation of Fomes fomentarius decay capabilities on the chemical properties of the wood cell wall of the tree species Quercus castaneifolia,Juglans regia,and Carpinus betulus were used to determine and characterize the destructive behaviour of F.fomentarius decay by MALDI-TOF mass spectrometry.The results showed that the fungus had more significant destructive behaviour on J.regia than the other species.For this evidence,completely removal of xylan hemicellulose fragment+Na+at peak 1227 Da and severe digestion of fragment of glucomannan hemicellulose at peak 1477–1480 Da that it seems that signs of soft-rot patterns were obtained from the decayed sample of J.regia,while these were incremental and unchanged for C.betulus and Q.castaneifolia,respectively.However,C.betulus had different peaks of atomic mass than J.regia and Q.castaneifolia wood,respectively.These results showed that this technique could be useful for separating and identifying unknown compounds of the wood cell wall attacked by fungi relying on their biological behaviour.

Finite Element Analysis of the Groove Pressing of Aluminum Alloy

In this paper, the finite element method was applied to analyze the deformation behavior of Al-1%Mg alloy during constrained groove pressing (CGP). Deformation inhomogeneity was studied in term of plastic strain distribution during deformation. It was found that after first pressing and flattening steps, the plastic strain is inhomogeneous but second pressing and flattening improve deformation distribution considerably. Also the regions between flat and inclined parts of sample receive less shear strain and consequently after four passes the deformation distribution is still inhomogeneous and doesn’t improve remarkably with more deformation steps.

Experimental Analysis and Evaluation of Thermostat Effects on Engine Cooling System

Thermostat as a part of engine cooling system has a significant role in the shortening warm-up time and regulating the engine in proper temperature to approach optimal performance.Whereas,there is not adequate research on this part of the cooling system and its responsibility.Considering this gap and also being used in large scale,this study is intended to evaluate performance and reflex of the wax type thermostat in different engine working conditions.In this regard,performance of engine cooling system was investigated in various engine speeds and loads to reveal positive and negative influences of thermostat on engine cooling efficiency and engine performance.According to observed results,warm-up period and fuel consumption decrease by using a thermostat.On the other hand,however,the temperature oscillation of coolant fluid passing through engine increases sharply,which causes a disruption in the regulating engine temperature and also a possibility of the fluid boiling rises in some regions of the engine that increases the risk of damage in the engine parts.Engine temperature,fuel consumption,warm-up duration and emissions were provided and compared in two operation modes,with and without thermostat.

Do clinical and paraclinical findings have the power to predict critical conditions of injured patients after traumatic injury resuscitation?Using data mining artificial intelligence

Purpose The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury.Early recognition of patients is an important case of such decision-making with risk of worse prognosis.This article is to answer if clinical and paraclinical signs can predict the critical conditions of injured patients after traumatic injury resuscitation.Methods The study included 1107 trauma patients,16 years and older.The patients were trauma victims of Levels I and II triage and admitted to the Rajaee(Emtiaz)Trauma Hospital,Shiraz,in 2014–2015.The cross-industry process for data mining methodology and modeling was used for assessing the best early clinical and paraclinical variables to predict the patients’prognosis.Five modeling methods including the support vector machine,K-nearest neighbor algorithms,Bagging and Adaboost,and the neural network were compared by some evaluation criteria.Results Learning algorithms can predict the deterioration of injured patients by monitoring the Bagging and SVM models with 99%accuracy.The most-fitted variables were Glasgow Coma Scale score,base deficit,and diastolic blood pressure especially after initial resuscitation in the algorithms for overall outcome predictions.Conclusion Data mining could help in triage,initial treatment,and further decision-making for outcome measures in trauma patients.Clinical and paraclinical variables after resuscitation could predict short-term outcomes much better than variables on arrival.With artificial intelligence modeling system,diastolic blood pressure after resuscitation has a greater association with predicting early mortality rather than systolic blood pressure after resuscitation.Artificial intelligence monitoring may have a role in trauma care and should be further investigated.

Using Pantheon and Hubble parameter data to constrain the Ricci dark energy in a Bianchi Ⅰ Universe

In this work,we use the most recent publicly available type Ⅰa supernova(SNIa) compilations and H(z) data.A well formulated cosmological model based on Bianchi type Ⅰ(BI) metric is implemented in the presence of the Ricci dark energy model.Using the maximum likelihood technique,we estimate the present value of Hubble's constant H_(0)=70.339±0.743,matter density parameter Ω_(m_(0))=0.297±0.031,anisotropy parameter Ω_(σ_(0))=-0.004 01 ± 0.001 07 within 1σ′ confidence level by bounding our derived model with recent joint Pantheon and H(z)data.We have constrained the present value of the equation of state parameter as ω_(de)=-1.17 joint with the observational data.The present value of the deceleration parameter of the Universe in the derived model is obtained as q_(0)=-0.749_(-0.086)^(+0.076).Transition redshift is also derived as z_(tr)~0.551 with the recent observations(Pantheon+H(z)) datasets.Finally,we compare the anisotropy effects on the evolution of H(z) for the proposed model under consideration with different observational datasets.

Simulation of CO_(2) removal from ethane with Sulfinol-MtAMP solvent instead of DEA solvent in the South Pars phases 9 and 10 gas processing facility

Raw gas gathered from well production has to be treated to extract its ethane,to remove carbon dioxide(CO2)from it and to dry it,so that the send-out ethane gas complies with transport constraints and meets sales-gas specifications.Two distinct families of solvents are used generically for such gas treatment:chemical and physical solvents.The South Pars gas field development phases 9 and 10 feeds gas and natural gas liquids into a processing and fractionation plant(one of the largest gas processing plants in Iran),and is associated with concentrations of 5.37%mole CO2 in the raw gas produced.Furthermore,there are potential problems associated with the CO2 treatment,such as the high-energy requirements for amine solvent regeneration,corrosion caused by aqueous amine solvents and waste/losses(solubility,vaporization)of the solvent used to remove CO2 in the ethane treatment unit.A feasibility simulation study was conducted to evaluate the utilization of Sulfinol-M t AMP solvent(Sulfolane plus Methyl di-ethanol amine plus 2-amino-2-methyl-1-propanol(AMP)plus H2O)to replace the aqueous amine solvent(DEA)currently used in the ethane treatment unit of South Pars phases 9 and 10 gas processing plant.The simulation of the Sulfinol-M t AMP process demonstrates less energy consumption(11241.242 kw versus 11290.398 kw for DEA),negligible corrosion and lower losses of solvent(376.493 kg/h versus 409.2421 kg/h)relative to alternative solvents considered,because of its low vapor pressure.

Swirling flow and capillary diameter effect on the performance of an active dry powder inhalers

For patients with lung disease,dry powder inhalers(DPI)are profoundly beneficial.The current study introduces and develops a series of dry powder inhalers(DPIs).A capsule-based(size 0)active DPI was considered.The study aims to investigate whether swirling flow and outlet capillary diameter(dc_out)affect the percentage of emitted doses(ED)released from the capsule.Spiral vanes were added to the capillary inlet to produce a swirling flow.Computational fluid dynamics(CFD)was applied to simulate the problem.The results were compared with previous in vitro and numerical studies to validate the results.Based on the derived results,the small swirl parameter(SP)enhances the secondary flow and recirculation zone.It increases the central jet flow,which increases the ED value by about 5–20%compared to no-swirl flow.However,as the airflow rate increases,the recirculation zone enlarges,vorticities become dominant,and asymmetrical flow patterns emerge.Consequently,ED%drops significantly(more than 50%).As d_(c_out)decreases,the vorticities around the outlet capillary become more potent,which is undesirable.Indeed,the emptying of the capsule does not happen ideally.The research provides a perspective on the device's design and DPI performance.

Numerical and analytical investigation of vapor flows in a flat plate heat pipe: Effects of length ratio and Reynolds number

Heat pipes are crucial in a wide range of applications,ranging from space satellites and industrial systems to electronic cooling and X-ray tube thermal management.This study introduces a method investigation into vapor flows within a flat plate heat pipe,utilizing the collocation method(CM)and the fourth-order Runge-Kutta-Fehlberg(RKF45)method.Building on previous efforts,this work explores the effects of the evaporator-to-condenser length ratio and Reynolds number on velocity and pressure distributions along the entire heat pipe.The significance of this research lies in its ability to elucidate critical parameters that directly influence heat pipe performance,offering deeper insights that are vital for optimizing design and efficiency.The primary motivation of this study is to fill existing gaps in the literature by developing a comprehensive analytical model that accurately characterizes vapor and liquid flow in asymmetrical flat plate heat pipes.The model’s validity is confirmed through a satisfactory agreement with numerical results,underscoring the reliability of the methods used.Notably,the findings reveal that higher Reynolds numbers reduce pressure drop and shift the maximum velocity toward the bottom wick in the evaporation section,providing valuable guidance for future design improvements.Additionally,this research presents a powerful method for solving non-linear ordinary differential equations,offering significant time savings and enabling predictive functions.These contributions are poised to enhance the performance of thermal management systems across various engineering disciplines.

Undrained seismic bearing capacity of strip footing adjacent to a heterogeneous excavation

The analysis of the bearing capacity of strip footings sited near an excavation is critical in geotechnics.In this study,the effects of the geometrical features of the excavation and the soil strength properties on the seismic bearing capacity of a strip footing resting on an excavation were evaluated using the lower and upper bounds of the finite element limit analysis method.The effects of the setback distance ratio(L/B),excavation height ratio(H/B),soil strength heterogeneity(kB/cu),and horizontal earthquake coefficient(kh)were analyzed.Design charts and tables were produced to clarify the relationship between the undrained seismic bearing capacity and the selected parameters.

Robust non-aggressive three-axis attitude control of spacecraft:dynamic sliding mode approach

Conventional sliding mode control(SMC)has been extensively applied in controlling spacecrafts because of its appealing characteristics such as robustness and a simple design procedure.Several methods such as second-order sliding modes and discontinuous controllers are applied for the SMC implementation.However,the main problems of these methods are convergence and error tracking in a finite amount of time.This paper combines an improved dynamic sliding mode controller and model predictive controller for spacecrafts to solve the chattering phenomenon in traditional sliding mode control.To this aim,this paper develops dynamic sliding mode control for spacecraft’s applications to omit the chattering issue.The proposed approach shows robust attitude tracking by a set of reaction wheels and stabilizes the spacecraft subject to disturbances and uncertainties.The proposed method improves the performance of the SMC for spacecraft by avoiding chattering.A set of simulation results are provided that show the advantages and improvements of this approach(in some sense)compared to SMC approaches.