Uniform Model Research Articles

The rigid-flexible coupling vibration of assembled disk-composite conical shell structure of electric aircraft in hygrothermal circumstance

A novel theoretical formulation for addressing the coupling vibration of the rigid disc and flexible composite conical shell structure (RDFCCSs) in hygrothermal circumstances is established to investigate the vibration evolution of the rigid-flexible composite thin-walled coupled structure of new energy electric aircraft. According to Donnell's thin shell theory, the potential energy of the composite conical shell under hygrothermal load is calculated. A uniform mass model and a set of artificial springs distributed on the interface of the shell and disk are imported to simulate the RDFCCSs. The governing equation of the RDFCCSs with arbitrary foundations in hygrothermal circumstances is deduced according to the Rayleigh-Ritz variational procedure. Systematic experiments and finite element simulations have been demonstrated to confirm the accuracy of the proposed method. Three new rigid-flexible coupling vibration modes of the RDFCCSs that differ from the traditional single thin-walled conical shell element due to the influence of the disk have been revealed. After that, the unique vibration characteristics of RDFCCSs under various masses, axial loads, hygrothermal environments and interface connection stiffnesses are discussed in detail.

Project Dinos I: A joint lensing–dynamics constraint on the deviation from the power law in the mass profile of massive ellipticals

ABSTRACT The mass distribution in massive elliptical galaxies encodes their evolutionary history, thus providing an avenue to constrain the baryonic astrophysics in their evolution. The power-law assumption for the radial mass profile in ellipticals has been sufficient to describe several observables to the noise level, including strong lensing and stellar dynamics. In this paper, we quantitatively constrained any deviation, or the lack thereof, from the power-law mass profile in massive ellipticals through joint lensing–dynamics analysis of a large statistical sample with 77 galaxy–galaxy lens systems. We performed an improved and uniform lens modelling of these systems from archival Hubble Space Telescope imaging using the automated lens modelling pipeline dolphin. We combined the lens model posteriors with the stellar dynamics to constrain the deviation from the power law after accounting for the line-of-sight lensing effects, a first for analyses on galaxy–galaxy lenses. We find that the Sloan Lens ACS Survey lens galaxies with a mean redshift of 0.2 are consistent with the power-law profile within 1.1σ (2.8σ) and the Strong Lensing Legacy Survey lens galaxies with a mean redshift of 0.6 are consistent within 0.8σ (2.1σ), for a spatially constant (Osipkov–Merritt) stellar anisotropy profile. We adopted the spatially constant anisotropy profile as our baseline choice based on previous dynamical observables of local ellipticals. However, spatially resolved stellar kinematics of lens galaxies are necessary to differentiate between the two anisotropy models. Future studies will use our lens models to constrain the mass distribution individually in the dark matter and baryonic components.

The distortion and misinterpretation of TEM responses caused by the IP effect

Abstract Transient electromagnetic surveys are commonly conducted to map the distribution of resistivity, a key physical property in mineral exploration and other geological prospecting problems. However, the responses obtained in regions associated with chargeable minerals are always distorted by the induced polarization effects. In this study, the distorted responses are initially simulated in the frequency domain employing the Cole–Cole complex resistivity model and subsequently converted into the time domain through a time-frequency transformation method. A uniform half-space model is employed to validate the algorithm and illustrate the distortion characteristics of the responses in polarizable formations. A three-layer model is designed to estimate the misinterpretation of slightly complicated models. An actual misinterpretation is demonstrated by field responses containing induced polarization effects collected in the Wulong Gold Mine. The results show that the distortions under different geoelectrical conditions are consistent, enhancing the responses in the early stage and counteracting the responses in the late stage. The strong induced polarizable effects distort the responses by causing explicit sign reversals, whereas the weak induced polarizable effects only distort the decay rate of the responses. These distortions are prone to causing misinterpretations and resulting in excessively intricate geological structures.

The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models

Thompson sampling (TS) has been known for its outstanding empirical performance supported by theoretical guarantees across various reward models in the classical stochastic multi-armed bandit problems. Nonetheless, its optimality is often restricted to specific priors due to the common observation that TS is fairly insensitive to the choice of the prior when it comes to asymptotic regret bounds. However, when the model contains multiple parameters, the optimality of TS highly depends on the choice of priors, which casts doubt on the generalizability of previous findings to other models. To address this gap, this study explores the impact of selecting noninformative priors, offering insights into the performance of TS when dealing with new models that lack theoretical understanding. We first extend the regret analysis of TS to the model of uniform distributions with unknown supports, which would be the simplest non-regular model. Our findings reveal that changing noninformative priors can significantly affect the expected regret, aligning with previously known results in other multiparameter bandit models. Although the uniform prior is shown to be optimal, we highlight the inherent limitation of its optimality, which is limited to specific parameterizations and emphasizes the significance of the invariance property of priors. In light of this limitation, we propose a slightly modified TS-based policy, called TS with Truncation (TS-T), which can achieve the asymptotic optimality for the Gaussian models and the uniform models by using the reference prior and the Jeffreys prior that are invariant under one-to-one reparameterizations. This policy provides an alternative approach to achieving optimality by employing fine-tuned truncation, which would be much easier than hunting for optimal priors in practice.

Model Counting and Sampling via Semiring Extensions

Many decision and optimization problems have natural extensions as counting problems. The best known example is the Boolean satisfiability problem (SAT), where we want to count the satisfying assignments of truth values to the variables, which is known as the #SAT problem. Likewise, for discrete optimization problems, we want to count the states on which the objective function attains the optimal value. Both SAT and discrete optimization can be formulated as selective marginalize a product function (MPF) queries. Here, we show how general selective MPF queries can be extended for model counting. MPF queries are encoded as tensor hypernetworks over suitable semirings that can be solved by generic tensor hypernetwork contraction algorithms. Our model counting extension is again an MPF query, on an extended semiring, that can be solved by the same contraction algorithms. Model counting is required for uniform model sampling. We show how the counting extension can be further extended for model sampling by constructing yet another semiring. We have implemented the model counting and sampling extensions. Experiments show that our generic approach is competitive with the state of the art in model counting and model sampling.

Optimal green investment strategy for grid-connected microgrid considering the impact of renewable energy source endowment and incentive policy

Microgrid is a promising way to integrate renewable distributed generation into the electric power sector, which has received widespread attention. In this paper, a uniform capacity-constrained optimization model under different power purchase and sale price contracts is developed to explore the optimal green investment strategy for grid-connected microgrid (GCM) with three configuration types. The impact of renewable energy source endowment and incentive policy is focused when macrogrid’s generators emit more pollution than GCM’s non-renewable generators, such as in China and India. The results show that: (1) GCM with renewable generation can only be invested in a site with relatively abundant renewable endowment; (2) carbon tax effectively promotes the deployment of GCM with renewable generation and achieves carbon emission abatement, but excessive carbon tax cannot incentive investment in the most desired GCM type; (3) a subsidy trap is found under feed-in tariff (FIT) subsidy, which implies that the fade-out or exit of FIT subsidy is beneficial for microgrid’s healthy development; (4) and the comparisons under different price contracts emphasize the importance of macrogrid providing non-discriminatory access to feed-in and feed-out services to microgrid.

LACE and the APRN Consensus Model: Implications for Advancing Nursing Practice.

Understanding the historical context and contemporary trends in advanced practice registered nurse (APRN) education and regulation is pivotal for effective professional advocacy. Until the release of the APRN Consensus Model in 2008, a uniform model for APRN regulation was lacking. Adopting the model's recommendations has implications for APRNs beyond licensure and regulation, including full practice authority, license portability, and patient access to APRN-led care. A comprehensive understanding of APRN education and regulation empowers nurses, APRNs, and stakeholders to drive the profession forward through informed advocacy.

Complex Rupture Features and Triggering during the 2022 Chishang Earthquake Sequence in Eastern Taiwan Estimated by InSAR, GPS, Strong Motion, and Teleseismic Waveform Evidence

Abstract The most recent 2022 Chishang earthquake sequence broke a long-time seismic quiescence on the Central Range fault (CRF), attracting lots of attention to the seismic behaviors and fault interactions of the Longitudinal Valley zone (LVZ), eastern Taiwan orogeny. However, detailed rupture features of both the foreshock and mainshock are still scarce. Here, available static displacements (i.e., Interferometric Synthetic Aperture Radar [InSAR], Global Positioning System [GPS], and strong motion [SM]) and kinematic waveform evidence (i.e., high-frequency GPS, strong motion, and teleseismic data) are used to delineate the rupture behaviors of both the foreshock and mainshock in this sequence. Our results indicate that the static displacements derived from strong-motion sites rival the high precision of GPS observations, replenishing the near-field constraints on the hanging wall together with InSAR and GPS. The optimal uniform slip models exhibit that both the foreshock and mainshock generally ruptured the west-dipping CRF along the south-southwest-striking direction with a steep dip angle >65°. The slip distribution models revealed that the rupture of foreshock and mainshock nearly ruptured a total length of CRF within 65 km from the Guanshan to Ruisui at a depth of above 14 km, and their slips are concentrated within one asperity and two asperities, respectively. The spatial evolution of this sequence’s ruptures exhibits a discontinued and separated pattern, and is well consistent with the local seismicity. Considering that the mainshock was initialed in a weak slip and negative static Coulomb stress region caused by the foreshock, the 2022 sequence occurrence is in favor of a preslip triggering mechanism. The rupture region of the 2022 sequence filled the “seismic gap” along the western flank of the LVZ and will promote the potential seismic hazard in this region.

Discrete Distribution Model of Ship Noise Source in Shipping Channel

Ship noise plays an important role in low-frequency ocean ambient noise. With the increasingly busy sea traffic, the randomness of the spatiotemporal distribution characteristics of ship noise is also increasing. However, most ships sail in a relatively fixed range in different sea areas. Most of the previous studies assumed that the ship noise sources in shipping channel satisfy a uniformly distribution, actually all kinds of large ships are not uniformly distributed in the shipping channel, and there are also many small boats distributed on the channel that contribute significantly to low-frequency ocean ambient noise. The channel within a certain sea area will be divided into different regions, and ship information (AIS) in different regions will be analyzed statistically in this paper. It is assumed that the ship noise sources in different channel regions are discrete point noise sources that obey a certain spatiotemporal statistical distribution, combined with the noise source level models of different types of ships to form a discrete source model of ship noise in shipping channel. Using the ray propagation theory considering the horizontal refraction of sound energy, the vertical distribution of the ship noise level in this sea area is calculated, and compared with the vertical noise level distribution of ship noise source uniform distribution model, the variation range of noise level vertical distribution of two models is close calculated noise level (such as maximum and minimum values) is consistent with the measured data. The discrete source model of ship noise established in this paper may provide a technical support for predicting low-frequency ambient noise characteristics near the channel.

X-ray diffraction analysis of orthorhombic SnSe nanoparticles by Williamson–Hall, Halder–Wagner and Size–Strain plot methods

SnSe nanoparticles were synthesized using the sonochemical exfoliation technique, employing SnSe single crystals. Various analysis, including Energy Dispersive Analysis of X-rays-Elemental mapping, X-ray Diffraction (XRD), High-Resolution Transmission Electron Microscopy, Ultra-Violet Diffused Reflectance Spectroscopy-Photoluminescence measurements, Raman spectroscopy, and X-ray Photoelectron Spectroscopy, were conducted to determine the chemical composition, crystalline phase, morphological characteristics, optical properties, vibrational modes, and oxidation states of the synthesized nanoparticles. The XRD peak broadening analysis, specifically employing Williamson–Hall (W-H), Size–Strain Plot (SSP), and Halder–Wagner Method (H-W), was employed to examine particle size and intrinsic strain. Additionally, three models within the W-H method, namely the uniform deformation model (UDM), uniform stress deformation model (USDM), and uniform deformation energy density model (UDEDM), were used to investigate physical and microstructural parameters such as strain, stress, and energy density. A comprehensive comparison of the average particle size results obtained from Williamson–Hall, Size–Strain, and Halder–Wagner Methods, along with results from HR-TEM and Particle Size Analysis, was carried out. The comprehensive comparison of results from different techniques adds credibility to the reported findings.

Time-variant seismic resilience of reinforced concrete buildings subjected to spatiotemporal random deterioration

Corrosion-induced deterioration weakens the seismic capacity of buildings in coastal areas. This paper presents an investigation into the seismic resilience of RC frame structures experiencing spatiotemporal random deterioration. Two probabilistic distributions of corrosion were simulated using two modeling approaches: uniform and spatial corrosion assumptions. The incremental dynamic analysis (IDA) approach was used to obtain fragility curves for a 5-story RC frame designed according to Chinese codes. The impact of corrosion over a service life ranging from 0 to 50 years was assessed. The loss evaluation was subsequently conducted using the method proposed by Federal Emergency Management Agency (FEMA). The functionality curves and normalized resilience indices for different seismic hazard levels were estimated. The results indicate that the seismic probabilistic capacity and resilience of the 5-story RC frame studied here decrease as service time increases. The damage to structural members is more sensitive than that to nonstructural components. The total losses of the RC frame investigated in this study mainly result from nonstructural repair losses at first, then the collapse losses will become the main contributor to total loss as the seismic hazard level increases. Both uniform and spatial corrosion modeling approaches are valuable for representing the impact of corrosion on the restoration capabilities of RC frames.

Applying the Akaike Information Criterion (AIC) in earthquake spatial forecasting: a case study on probabilistic seismic hazard function (PSHF) estimation in the Sumatra subduction zone

This study uses complete earthquake catalog data and spatio-temporal analysis to construct a reliable model to forecast the potential seismogenic earthquake or earthquake fault zones. It integrates models developed based on different researchers’ methods and earthquake catalogs from different periods. It constructs and compares models - Model-1, Model-2, and Model-3 - from the complete shallow earthquake catalog between 1963-1999 and 1963-2006. The δAIC is used to evaluate the reliability of the models, with Model-3 emerging as the most reliable in all tests in this study. The model is constructed based on the product of the normalized model of the combined smooth seismicity model of a relatively small to moderate complete earthquake catalog data with a relatively uniform background model and weighted by the normalized seismic moment rate derived from the surface strain rate. It is suggested that a more extended observation period and using a complete, albeit relatively small-to-moderate, earthquake catalog leads to a more reliable and accurate model. Implementation of the Probabilistic Seismic Hazard Function (PSHF) window using the b-value of a 5-year window length with a 1-year sliding window prior to a significant seismic event proved successful, and the methodology demonstrates the importance of the temporal "b-value" in conjunction with the reliable seismicity rate and spatial probabilistic earthquake forecasting models in earthquake forecasting. The results showed large changes in the PSHF prior to giant and large earthquakes and the finding of a correlation between decreased b-value time window length and earthquake magnitude. The results have implications for the implementation of seismic mitigation measures.

A comparative study in estimating of crystallite sizes of synthesized and natural hydroxyapatites using Scherrer Method, Williamson-Hall model, Size-Strain Plot and Halder-Wagner Method

In this study, an approach was made to create hydroxyapatite (HAp) crystals on nanoscale ranges from CaCO3 and H3PO4 utilizing a wet chemical process. Both fish and cow bones were used effectively for making bone powder as the natural sources of HAp. X-ray diffraction approach proved that powdered bone and HAp were in the crystalline phase. The determination of crystallite size in synthesized HAp crystals and bone powders was investigated using a range of techniques, including Linear Straight-Line Method (LSLM), Williamson-Hall Method (WHM), Size-Strain Plot (SSP), Halder-Wagner Method (HWM), and Sahadat-Scherrer Method (SSM). We also employed different Williamson-Hall models to quantify the stress and strain of the powdered materials for all diffraction peaks, including the Uniform Deformation Model (UDM), Uniform Stress Deformation Model (USDM), and Uniform Deformation Energy Density Model (UDEDM). Williamson-Hall is regarded as the best approach out of all of them since it was used to find the energy density, lattice stress, lattice strain, and crystallite size of the formed crystal. All the results from each model were compared to check the variation of analyzed data. The obtained results confirmed that there was an interrelation between the particle sizes of the Size Strain Plot and the Williamson-Hall method.

Numerical analysis on the effect of graded porosity in closed-cell metal foams/PCM composites

The porous metal foams are potential to integrate phase change materials (PCMs) to form the shape-stabilized composited PCMs for the applications of thermal energy management and temperature regulation. However, the effect of porosity distribution of foam keeps challenging in designing such PCM-based composites. In this work, the closed-cell graded porosity foams (GPFs) involving various gradient directions and gradient differences of porosity are engineered by shrinking Voronoi tessellations to achieve precisely tunable microstructure. Then the GPF/PW composite is formed by integrating paraffin wax (PW) in each pore and its melting performance is investigated by the computational model, which is validated by the melting experiment of a specific sample. The investigations on the gradient configurations of foams reveal that the gradient direction and gradient difference of porosity have significant influences on the pore-scale melting behavior, liquid fraction variation in time and overall energy storage efficiency of PW. The positive gradient variation along the direction of heating source and the moderate gradient difference, i.e. 20% or 30%, are beneficial to improve the melting behavior of graded models. In contrast to the uniform model, the complete melting time of the graded models can maximum shorten by 5.6%, 3.8% and 3.7% for the bottom, lateral and top heating modes, respectively.

Group sequential designs for pragmatic clinical trials with early outcomes: methods and guidance for planning and implementation

BackgroundGroup sequential designs are one of the most widely used methodologies for adaptive design in randomized clinical trials. In settings where early outcomes are available, they offer large gains in efficiency compared to a fixed design. However, such designs are underused and used predominantly in therapeutic areas where there is expertise and experience in implementation. One barrier to their greater use is the requirement to undertake simulation studies at the planning stage that require considerable knowledge, coding experience and additional costs. Based on some modest assumptions about the likely patterns of recruitment and the covariance structure of the outcomes, some simple analytic expressions are presented that negate the need to undertake simulations.MethodsA model for longitudinal outcomes with an assumed approximate multivariate normal distribution and three contrasting simple recruitment models are described, based on fixed, increasing and decreasing rates. For assumed uniform and exponential correlation models, analytic expressions for the variance of the treatment effect and the effects of the early outcomes on reducing this variance at the primary outcome time-point are presented. Expressions for the minimum and maximum values show how the correlations and timing of the early outcomes affect design efficiency.ResultsSimulations showed how patterns of information accrual varied between correlation and recruitment models, and consequentially to some general guidance for planning a trial. Using a previously reported group sequential trial as an exemplar, it is shown how the analytic expressions given here could have been used as a quick and flexible planning tool, avoiding the need for extensive simulation studies based on individual participant data.ConclusionsThe analytic expressions described can be routinely used at the planning stage of a putative trial, based on some modest assumptions about the likely number of outcomes and when they might occur and the expected recruitment patterns. Numerical simulations showed that these models behaved sensibly and allowed a range of design options to be explored in a way that would have been difficult and time-consuming if the previously described method of simulating individual trial participant data had been used.

Clade size distribution under neutral evolutionary models

Given a labeled tree topology t, consider a population P of k leaves chosen among those of t. The clade of P is the minimal subtree of t containing P and its size is given by the number of leaves in the clade. When t is selected under the Yule or uniform distribution among the labeled topologies of size n, we study the “clade size” random variable determining closed formulas for its probability mass function, its mean, and its variance. Our calculations show that for large n the clade size tends to be smaller under the uniform model than under the Yule model, with a larger variability in the first scenario for values of k≥5. We apply our probability formulas to investigate set-theoretic relationships between the clades of two populations in a random tree, determining how likely one clade is contained in or it is equal to the other. Our study relates to earlier calculations for the probability that under the Yule model the clade size of P equals the size of P—that is, the population P forms a monophyletic group—and extends known results for the probability that the minimal (non-trivial) clade containing a random taxon has a given size.

A numerical and closed-form analytical solution for the global buckling critical load of tall buildings considering soil flexibility: A coupled shear-flexural model

The critical global buckling load is a fundamental parameter governing the performance of tall buildings, however, the existing literature lacks an efficient solution that comprehensively captures the behavior of tall structures with uniform or variable properties. In response to this gap, this study introduces a novel and generalized solution, employing the coupled shear-flexural model. This solution is designed for determining the critical global buckling load in tall buildings subjected to vertical loads with diverse profiles, while also incorporating soil flexibility. The analytical solution, designed for the uniform continuous model, offers a breakthrough by providing graphical representations facilitating the direct determination of eigenvalues based on a single dimensionless parameter. Addressing the unique challenge posed by tall buildings with variable properties, a numerical transfer matrix method based on a Laplacian approach is proposed. This method enables the direct calculation of the transfer matrix for each level, displaying exceptional convergence in just three iterations. The study sheds light on a crucial finding that emphasizes the adverse impact of rotational flexibility on soil, leading to a decrease in eigenvalues as soil flexibility increases. Importantly, the proposed solution methods not only show excellent accuracy but also serve as invaluable tools for performing parametric analyses. Furthermore, they present cost-effective alternatives to exact methods, providing a solid foundation for studying the overall stability of tall buildings. This research contributes significantly to the existing literature by introducing efficient methodologies that improve our understanding and analysis of the behavior of tall buildings under vertical loads.

Microstructural, optical, and morphological investigations of SnO2 nanomaterials grown by microwave assisted sol gel method

Tin Oxide (SnO2) nanomaterials were grown using the microwave-assisted sol–gel method at different concentrations of tin precursor (namely 0.05, 0.1, 0.2, and 0.3 M). Stannous chloride is used as a Sn precursor. Liquid ammonia was used to maintain the pH in the range of 12–13. Synthesis was carried out in an aqueous medium using a Teflon container in a microwave oven for 1 hour. Precipitate was annealed in ambient air for 600oC. Structural, optical, and morphological investigations were done. XRD reveals the growth of the tetragonal phase of SnO2. The prominent presence of (110), (101), and (211) reflections was noticed at 26.6, 33.7, and 52 two-theta values. Tin oxide is transparent in the visible region of the electromagnetic spectrum. However, several attempts have been made to decrease the visible blindness of tin oxide. The band gap is a property of nanomaterials that can tailor their application in the optoelectronic field. Band gap and crystallite size show a prominent relationship in the nano-domain. Strain was not considered while calculating crystallite size using the Scherrer formula. In this investigation, we have measured the crystallite size and other structural features such as strain, stress, deformation energy, dislocation de\ sity, etc using the W-H plot method. All modified models of the W-H method have been utilized for this measurement. A comparative and comprehensive study of structural features was carried out using the Scherrer method, the Williamson–Hall method, and all its modified models. The crystallite size measured by the Scherrer method and various models of the W-H method shows a peak at 0.2 M concentration. Crystallite size plots of various modified W-H methods show similar trends, followed by the Scherrer plot. Strain calculated by Brag’s theory as well as all modified W-H depicts similar behaviour upon changing the concentration. Globular agglomerated morphology was revealed by scanning electron microscopy (SEM). The presence of tin (Sn) and oxygen (O) was confirmed by energy dispersive x-ray spectroscopy. The band gap was obtained using the Tauc theory, which portrays variation in the range of 3.4 to 3.6 eV.

Analysis method of permanent magnet eddy current brake under impact load

Permanent magnet eddy current brake (PMECB) with high damping performance is widely used in engineering vibration suppression and braking. In this study, based on the braking dynamics of PMECB under impact load, the analysis method related to the damping characteristics are established, including a static magnetic model with flux leakage, a uniform damping force model with demagnetization effect and skin effect, and an acceleration damping force model with magnetic field distortion. The comparison of the analysis method, numerical simulation and experimental results verifies that the analysis method can reproduce the damping law under impact load. The results show that the maximum displacements of the analysis method and numerical simulation deviate from the experimental results within 3%. The analysis method can complete the calculation of the damping characteristics within a few seconds. The variations of the thickness, conductivity of the conductive cylinder, and air gap thickness have significant effects on the nonlinear and critical characteristics of the velocity-damping force curve, which can be corrected by changing the coefficients in the analysis method. In summary, the proposed analysis method can provide insights for rapid engineering design and optimization calculation of the PMECB by its completeness, accuracy, adaptability and rapidity.

A timely efficient and emissions-aware multiobjective truck-sharing integrated scheduling model in container terminals

In line with the development of green port terminals and the necessity of environmentally friendly efficient use of handling and transportation equipment, criteria such as emission reduction, energy minimization, and efficiency in a container terminal are prominent issues, which in recent years, have been the main concern of container terminal managers in developing terminal operating systems. Therefore, in this study, a bi-objective mixed integer mathematical programing model of integrated scheduling for ships’ loading and unloading operation sequencing in container terminals is proposed, which considers the minimization of containers’ flow time, trucks’ emission, and energy consumption as well as sharing trucks among quay cranes and decreasing their empty trips. In this model trucks’ technical specifications and polluting levels are input parameters for estimating emission and energy consumption of operation, which consequently leads to two uniform parallel machine scheduling models. To derive the exact solution of the model, the epsilon-constraint method is applied. Nevertheless, due to the problem’s NP-hardness attribute, two variants of non-dominated sorting genetic algorithm and multiobjective particle swarm optimization metaheuristic algorithms are proposed to identify the approximate Pareto front of solutions. In large-size problems, these algorithms outperform the epsilon-constraint method by finding acceptable results in a reasonable time. This model, which could be embedded in terminal operating software, not only yields a practical optimum operational sequence but also measures the amount of energy and emission from trucks during loading and unloading operations. The results, which utilized the data collected from Shahid Rajaee port in southern Iran, indicate that this practical model as compared to the current procedure in the terminal, results in a significant improvement in energy and emission reduction and terminal flow time.