Classical Theory Research Articles

Development and preliminary evaluation of the Comprehensive Health Self-Assessment Questionnaire (CHSAQ) for individuals in the Chinese People Liberation Army

ObjectiveThere is currently no widely accepted multidimensional health assessment questionnaire for individuals in the Chinese People Liberation Army (PLA). This study developed a multidimensional health survey questionnaire (Comprehensive Health Self-Assessment Questionnaire, CHSAQ) suitable for personnel in the PLA and conducted a preliminary examination of its reliability, validity, and discriminative ability.MethodsAfter 183 items from 32 dimensions were selected to form the initial version of the CHSAQ, three groups of soldiers were selected from May 2022 to April 2023 and completed three survey rounds (with 183, 131, and 55 valid items). The items were screened based on classic test theory. After screening, the final questionnaire entries were formed, the structure of the questionnaire was explored through exploratory factor analysis and confirmatory factor analysis, and its reliability, structural validity, and discriminative ability were evaluated.ResultsThe final questionnaire consisted of 8 dimensions and 55 items on job satisfaction, anxiety and depression, daily activities, physical function, the otolaryngology system, the integumentary system, sleep disorders, and the visual system. The total cumulative variance contribution rate was 64.648% according to exploratory factor analysis. According to the confirmatory factor analysis, the normed fit index (NFI) was 0.880, and the comparison fit index (CFI) was 0.893 (close to 0.90). The Cronbach’s α coefficient of the total questionnaire was 0.970, the split half reliability coefficient was 0.937, and the retest reliability coefficient was 0.902. The results are presented as different pairwise comparisons.ConclusionOur study developed a self-report questionnaire for evaluating the comprehensive health status of personnel in the PLA in accordance with the standard procedure for questionnaire development. Our findings also showed that the CHSAQ for individuals in the PLA has good reliability and structural validity.

Micromechanical modeling and experimental study of the flexural properties of impregnated woven textile-reinforced concrete

As a high-performance composite material in construction, textile-reinforced concrete has been of interest in recent years. This study significantly contributes to the characterization of textile-reinforced concrete through an extensive experimental and analytical investigation, focusing on impregnated textile-reinforced concrete under flexural loading. For this purpose, two sets of experiments were conducted. The first set involved model input parameters tests, including the tensile test of epoxy resin and E-glass yarn, as well as the compression and flexural tests of concrete. The second set is related to validation tests, specifically focused on the flexural behavior of textile-reinforced concrete. Micromechanical frameworks were employed to model the flexural behavior of textile-reinforced concrete and a multiscale micromechanical model based on the classical lamination theory was developed to predict the load-deflection diagram of textile-reinforced concrete in the three-point bending test setup. The modeling results demonstrated a remarkable agreement between predictions and experimental data. Key performance indicators, including the first crack force, ultimate force, flexural modulus, and maximum deflection, were accurately predicted with errors of 2.4%, 6.1%, 11.1%, and 6.3%, respectively. Furthermore, from a parametric study, it is perceived that the flexural modulus of elasticity in textile-reinforced concrete is predominantly influenced by concrete properties, while the ultimate strength of textile-reinforced concrete is significantly affected by the properties of the impregnated fabric.

Review of Asymmetric Seafloor Spreading and Oceanic Ridge Jumps in the South China Sea

Seafloor spreading is an important cornerstone of the theory of plate tectonics. Asymmetric seafloor spreading and oceanic ridge jumps are common phenomena in this process and play important roles in controlling oceanic crust accretion, regional tectonics and geological geometric boundaries. As the largest marginal sea in the western Pacific, the South China Sea is an ideal laboratory for dissecting the Wilson cycle of small marginal sea-type ocean basins restricted by surrounding blocks and exploring the deep dynamic processes of confined small ocean basins. In recent years, a lot of research has been conducted on the spreading history of the South China Sea and has achieved fruitful results. However, the detailed dynamic mechanisms of asymmetric seafloor spreading and ridge jumps are still unclear. Therefore, this paper summarizes the basic understanding about the dynamic mechanisms of global asymmetric seafloor spreading and ridge jumps and reviews the related research results of asymmetric seafloor spreading and ridge jumps in the South China Sea. Previous studies have basically confirmed that seafloor spreading in the South China Sea started between ~32 and 34 Ma in the east sub-basin and ended at ~15 Ma in the northwest sub-basin, with at least once oceanic ridge jump in the east sub-basin. The current research mainly focuses on the age of the seafloor spreading in the South China Sea and the location, time and stage of the ridge jumps, but there are relatively few studies on high-resolution lithospheric structure across these ridges and the dynamic mechanism of oceanic ridge jumps. Based on the current research progress, we propose that further studies should focus on the lithosphere–asthenosphere scale in the future, suggesting that marine magnetotelluric and Ocean Bottom Seismometer (OBS) surveys should be conducted across the residual oceanic ridges to perform a detailed analysis of the tectonics magmatism in the east sub-basin to gain insights into the dynamic mechanisms of oceanic ridge jumps and asymmetric seafloor spreading, which can promote understanding of the tectonic evolution of the South China Sea and improve the classical plate tectonics theory that was constructed based on the open ocean basins.

Quantum symmetries in 2+1 dimensions: Carroll, (a)dS-Carroll, Galilei and (a)dS-Galilei

There is a surge of research devoted to the formalism and physical manifestations of non-Lorentzian kinematical symmetries, which focuses especially on the ones associated with the Galilei and Carroll relativistic limits (the speed of light taken to infinity or to zero, respectively). The investigations have also been extended to quantum deformations of the Carrollian and Galilean symmetries, in the sense of (quantum) Hopf algebras. The case of 2+1 dimensions is particularly worth to study due to both the mathematical nature of the corresponding (classical) theory of gravity, and the recently finalized classification of all quantum-deformed algebras of spacetime isometries. Consequently, the list of all quantum deformations of (anti-)de Sitter-Carroll algebra is immediately provided by its well-known isomorphism with either Poincaré or Euclidean algebra. Quantum contractions from the (anti-)de Sitter to (anti-)de Sitter-Carroll classification allow to almost completely recover the latter. One may therefore conjecture that the analogous contractions from the (anti-)de Sitter to (anti-)de Sitter-Galilei r-matrices provide (almost) all coboundary deformations of (anti-)de Sitter-Galilei algebra. This scheme is complemented by deriving (Carrollian and Galilean) quantum contractions of deformations of Poincaré algebra, leading to coboundary deformations of Carroll and Galilei algebras.

The Principles of the Classical Theory of Labor Law

The Classical Theory of Labor Law stands as a cornerstone in understanding the legal framework governing employer-employee relationships. This article delves into the foundational principles that underpin this theory, elucidating its historical context and theoretical framework. Beginning with an exploration of the concept of freedom of contract, the article examines how this principle has shaped the relationship between employers and employees, emphasizing autonomy and individual bargaining power. Furthermore, it analyzes the principle of equality, elucidating its role in safeguarding workers' rights and promoting fairness within the labor market. Additionally, the article discusses the principle of private property rights and its implications for labor relations, highlighting the balance between employers' prerogatives and employees' entitlements.

Electro-Mechanical Characterisation and Damage Monitoring by Acoustic Emission of 3D-Printed CB/PLA.

Even though the influence of the printing direction on the mechanical properties of 3D-printed samples by fused filament fabrication is established in the literature, very little is known about mechanical and electrical coupling. In this study, electrically conductive polylactic acid filled with carbon black particles undergoes monotonic and repeated progressive tensile loading to better understand the influence of the printing direction on the electro-mechanical properties of three-dimensional-printed samples. The objective is to analyse the electro-mechanical behaviour of this composite for its potential application as an actuator. The classical laminate theory is also applied to evaluate the relevance of this theory in predicting the mechanical characteristics of this material. In addition, a comprehensive damage analysis is performed using acoustic emission, infrared thermography, scanning electron microscopy, and X-ray microcomputed tomography imaging. Results show that the degradation of the mechanical and electrical properties is highly influenced by the printing direction. The appearance and development of crazes in 0° filaments are highlighted and quantified. The conclusions drawn by this study underline the interest in using longitudinal and unidirectional printing directions to improve the conductive path within the samples. Furthermore, the evolution of the resistance throughout the experiments emphasizes the need to control the implemented voltage in the design of future electro-thermally triggered actuators.

Grey wolf optimizer based-natural frequency optimization of laminated composite shells carrying distributed mass

In this study, a grey wolf optimizer is proposed to find the optimum stacking sequence to maximize the fundamental frequency of shells. The vibration analysis of the shells is done using first-order shear deformation theory and a nine-node isoparametric element with five degrees of freedom per node. A mass lumping scheme with rotary inertia is considered in the finite element formulation to include the rotary inertia effect. The design variable considered is the fiber angle orientation of the shells. The present approaches are compared with previously published results using layerwise optimization theory, the Ritz method, and classical lamination theory. A comparison study is also performed, comparing the GWO-based finite element model against six different metaheuristic approaches, and it demonstrates that the Grey Wolf Optimizer consistently outperforms these competing algorithms. The optimum fiber angle orientation of shells carrying distributed mass for various boundary conditions and shell types is analyzed for the first time, to the best of the author’s knowledge. This novel discovery will benefit future studies.

An analytical model for dynamic analysis of inhomogeneous sandwich plate

Sandwich plates are widely used in the engineering domain and are extensively studied by researchers for their special performances. Among them, the sandwich plate with coordinate-dependent material parameters has excellent vibration isolation performance. However, there are few effective and convenient analytical methods for solving the dynamic response of this type of sandwich plate. To solve this problem, an equivalent spring-based model for the dynamic analysis of the sandwich plate is proposed in this paper. Assuming that the sandwich plate is a linear elastic structure, and considering the core plate as equivalent springs, whose stiffness coefficients are derived based on the classical elasticity theory and Kirchhoff hypothesis. Besides, displacement solutions of base and constrained plates of the sandwich plate in the x, y and z directions are expressed as a two-dimensional Fourier series supplemented with several one-dimensional Fourier series, respectively. Then, according to the orthogonality of trigonometric functions and selectivity of Dirac functions, the displacements of the sandwich plate are solved accurately. By comparing with available analytical and numerical results, the proposed method is proven to have excellent performance in dealing with the sandwich plate with coordinate-dependent material parameters. Finally, the dynamic characteristics and vibration isolation performance of the inhomogeneous sandwich plate are discussed. The results show that the proposed method can be used to design the inhomogeneous sandwich plate and improve their vibration isolation performance significantly.

Multiscale simulation and prediction of mechanical properties for carbon fiber reinforced polymer orthotropic laminate

AbstractA multiscale analysis method based on numerical homogenization is presented for predicting the mechanical properties of carbon fiber reinforced polymer (CFRP) orthogonally symmetric laminate. Initially, based on the structural characteristics of CFRP orthotropic symmetric laminate, the relational equations for calculating the mechanical engineering constants from the stiffness coefficient are proposed. Subsequently, the finite element model (FEM) of orthotropic laminate is established. Corresponding subroutines are developed through ABAQUS‐Python to extract and compute the simulation results and obtain the mechanical properties of the laminate. Next, the macroscale mechanical properties are estimated by combining the micro‐scale mechanical model, classical laminate theory (CLT), and volume averaging method. Ultimately, the accuracy of the proposed equations and the feasibility of the numerical homogenization method are demonstrated by comparing the results of numerical simulation predictions, theoretical predictions, and experiments.Highlights Present the relational equations for calculating the mechanical engineering constants of CFRP orthotropic symmetric laminate from the stiffness coefficient. Establish the FEM of orthotropic laminate and develop corresponding subroutines to obtain the mechanical properties of the laminate. Analyze the mechanical properties of orthotropic laminate through microscopic modeling and CLT.

Elasticity-controlled jamming criticality in soft composite solids

Soft composite solids are made of inclusions dispersed within soft matrices. They are ubiquitous in nature and form the basis of many biological tissues. In the field of materials science, synthetic soft composites are promising candidates for building various engineering devices due to their highly programmable features. However, when the volume fraction of the inclusions increases, predicting the mechanical properties of these materials poses a significant challenge for the classical theories of composite mechanics. The difficulty arises from the inherently disordered, multi-scale interactions between the inclusions and the matrix. To address this challenge, we systematically investigated the mechanics of densely filled soft elastomers containing stiff microspheres. We experimentally demonstrate how the strain-stiffening response of the soft composites is governed by the critical scalings in the vicinity of a shear-jamming transition of the included particles. The proposed criticality framework quantitatively connects the overall mechanics of a soft composite with the elasticity of the matrix and the particles, and captures the diverse mechanical responses observed across a wide range of material parameters. The findings uncover a novel design paradigm of composite mechanics that relies on engineering the jamming properties of the embedded inclusions.

Mechanism of hydrogen isotope exchange for tritium removal in plasma-facing materials: a multi-scale investigation

The safety of future fusion reactors is critically dependent on the tritium (T) retention in plasma-facing materials. Hydrogen isotope (HI) exchange offers a method to redistribute HIs within solid materials, presenting a feasible approach for removing T from bulk materials and trapped by strong trapping sites. Nonetheless, unraveling the intricate mechanism behind HI exchange remains an urgent yet formidable challenge. This study undertakes a comprehensive investigation into the mechanism of HI exchange in tungsten materials across multiple scales. First, we developed a multi-component hydrogen isotope transport and exchange model (HIDTX) based on classical rate theory. The model validation was further carried out, demonstrating good consistency with the well-controlled laboratory experiments. From the results of different comparative models in HIDTX, it is found that the reduction in deuterium retention due to HI exchange was primarily driven by three synergistic effects: competitive re-trapping, collision, and swapping effects. Through molecular dynamics (MD) and first-principles calculations, the microscopic mechanism of HI exchange was revealed to be that the presence of hydrogen atoms in the interstitial sites surrounding a vacancy in tungsten decreased the binding energy between the vacancy and hydrogen. Meanwhile, we discovered that the combination of thermal desorption and HI exchange can significantly lower the temperature required for the hydrogen removal and enhance the removal rate. Particularly, the hydrogen removal time can be shortened by approximately 95% with simultaneous HI exchange compared to that with only thermal desorption. This work provides a practical guideline for comprehending and subsequently designing for efficient T removal in future nuclear fusion materials.

Carbon solute drag effect on the growth of carbon supersaturated bainitic ferrite: Modeling and experimental validations

The carbon partitioning and lengthening rate of bainitic ferrite (αb) are excellent experimental parameters to estimate our level of understanding of the mechanism of bainitic transformation from a continuum perspective and our ability to capture it in analytical expressions. For Fe-C alloys and relatively simple steels the classical Zener-Hillert theory captures the bainitic transformation rather well but mispredicts the level of carbon in solution in the bainite and overestimates the lengthening rates for transformations at lower temperatures. To address this issue, this paper presents a new thermo-kinetic model based on the Zener-Hillert theory and the Gibbs energy balance concept to simulate the lengthening behavior of αb in the Fe-C and low alloyed steels. The model incorporates the effect of the temperature dependent carbon diffusion within the migrating interface via a temperature dependent ferrite/austenite interfacial energy and a temperature dependent diffusion coefficient but does not impose local equilibrium across the interface. The good agreement between the model predictions and nine sets of published experiments indicates that both the carbon supersaturation in αb and the slower lengthening rate are caused by carbon diffusion within the migrating interface. It is found that the degree of carbon supersaturation in αb increases significantly with decreasing temperature. Consequently, the enhanced carbon solute drag effect, resulting from carbon diffusion within the interface, strongly retards the lengthening rates of αb at lower temperatures. Transformation strain is shown to have a modest effect on the lengthening rates but to lower the degree of carbon supersaturation.

Influence of Glyceryl Monostearate Adsorption on the Lubrication Behavior of a Slider Bearing

Glyceryl monostearate (GMS) was used as an organic friction modifier (OFM) and added to the base oil (PAO10, polyα-olefin) in this study. The film thickness and friction coefficient of the base oil added with GMS (PAO10G) under different slider inclinations and loads were investigated experimentally by using a slider-on-disc contact lubricant film measurement system, and the effect of the adsorption of GMS on the friction behavior of lubricant was studied. Contact angle hysteresis (CAH) was used to evaluate the wettability of the solid–liquid interface, and its correlation with the coefficient of friction was analyzed. The results show that CAH is in good agreement with the wettability of the solid–liquid interface. Compared with the base oil, the wettability of POA10G is weak, which can effectively reduce the coefficient of friction. However, different from the classical lubrication theory, the film thickness of PAO10G is higher than that of PAO10; this unusual phenomenon is preliminarily explained by the interface slippage in this paper.

Extended Field Interactions in Poisson’s Equation Revision

This investigation introduces a new variational approach to refining Poisson’s equation, enabling the inclusion of a broader spectrum of physical phenomena, particularly in the emerging fields of spintronics and the analysis of resonant structures. The innovative formulation extends the traditional capabilities of Poisson’s equation, offering a nonlocal extension to classical theories of gravitation and opening new directions for energy conversion and enhanced communication technologies. By introducing a novel geometric structure, ω˜, into the equation, a deeper understanding of electrostatic potentials is achieved, and the intricate dynamics of the gravitational potential in systems characterized by radial vorticity fluctuations are illuminated. Furthermore, the research elucidates the generation of longitudinal electromagnetic waves and resonant phenomena within dusty plasma media, thereby contributing to the methodological advances in the study of nonequilibrium systems. These theoretical advances have the potential to transform the understanding of complex physical systems and open up opportunities for significant technological achievements across a range of scientific sectors.

Generating Daily Activities with Need Dynamics

Daily activity data recording individuals’ various activities in daily life are widely used in many applications such as activity scheduling, activity recommendation, and policymaking. Though with high value, its accessibility is limited due to high collection costs and potential privacy issues. Therefore, simulating human activities to produce massive high-quality data is of great importance. However, existing solutions, including rule-based methods with simplified behavior assumptions and data-driven methods directly fitting real-world data, both cannot fully qualify for matching reality. In this article, motivated by the classic psychological theory, Maslow’s need theory describing human motivation, we propose a knowledge-driven simulation framework based on generative adversarial imitation learning. Our core idea is to model the evolution of human needs as the underlying mechanism that drives activity generation in the simulation model. Specifically, a hierarchical model structure that disentangles different need levels and the use of neural stochastic differential equations successfully capture the piecewise-continuous characteristics of need dynamics. Extensive experiments demonstrate that our framework outperforms the state-of-the-art baselines regarding data fidelity and utility. We also present the insightful interpretability of the need modeling. Moreover, privacy preservation evaluations validate that the generated data does not leak individual privacy. The code is available at https://github.com/tsinghua-fib-lab/Activity-Simulation-SAND .

PeerG: A P2P botnet detection method based on representation learning and graph contrastive learning

P2P botnets are distributed with complex topology and communication behavior, making them harder to detect and remove. Individuals or organizations can effectively detect P2P botnets by analyzing abnormal behaviors in network traffic. Existing works focus on extracting deterministic traffic interaction features, which are highly dependent on statistical features. Moreover, these methods are mainly aimed at generalized botnet detection and lack specificity for detecting P2P botnets. They ignore the topological information of P2P botnets, resulting in unsatisfactory detection accuracy. Among the few existing methods targeting P2P botnets, they consider the topological information but mainly rely on classical graph theory statistical features, such as degree, feature vector centrality, etc. This limits the generalization ability of the detection model. In this paper, we delve into the topological features of P2P botnets from the perspective of complex graph theory. We propose a P2P botnet detection method that combines representation learning and graph contrastive learning, dubbed PeerG. Specifically, we construct the communication graphs based on the flow interaction behavior between components of the P2P botnets. The Line algorithm is employed to embed the nodes of the communication graph into a low-dimensional representation vector space. Subsequently, the graph contrastive learning approach is utilized to optimize the feature extractor, enabling it to capture more representative node features. PeerG serves as a benchmark detection model for identifying P2P botnet nodes. Additionally, we devise two optimized contrastive detection strategies (PeerG-PreG and PeerG-PreF) based on graph-level and feature-level to boost the performance of PeerG. Extensive experiments demonstrate that PeerG brings significant improvements in detection accuracy over state-of-art detection methods. Furthermore, compared with PeerG, the detection strategies PeerG-PreG and PeerG-PreF have further improved detection performance, and achieve the best detection accuracy among multiple filtered P2P botnet types.

Optimizing the Value of a CO2 Water-Alternating-Gas Injection Project under Geological and Economic Uncertainties

Summary The numerical simulations required for the robust optimization (RO) of the alternating injection of water and CO2 in hydrocarbon reservoirs are computationally expensive due to engineering, geological, and economic uncertainties. Using approximation models of the desired objective function(s) can significantly decrease the cost associated with the optimization routines while providing an adequate sampling of the input variables or uncertainties. In this study, we optimized the value of a water-alternating-gas (WAG) injection project in a Niger-Delta oil reservoir by applying the Markowitz classical theory to a suitable approximation model of the objective function. Our RO methodology incorporated significant geological and economic uncertainties—such as uncertainties due to the upscaling of the coarse-scale reservoir model and those due to the lack of other relevant geological and economic data—to the optimization routine to create better operating strategies for the projects that are risk-quantified. To compute the objective function, a novel economic model for the CO2 sequestration processes in the Niger-Delta hydrocarbon basin was applied. The result obtained in the presented case showed that a net present value (NPV) of at least USD 65.98 million was derived from the project depending on the engineer’s or user’s confidence level. Overall, the applicability of proxy models to RO routines was demonstrated. As a result, investment decisions that accounted for uncertainties and any potential variation in the field’s operation and development were made.

On a mathematical theory for the crystallography of shear transformations in metals: Unification of mechanisms

A theory for shear transformations in crystalline materials linking their Crystallography, atomic-scale mechanisms and Thermodynamics is introduced. The lattice and transformation function are treated as vector space and functions respectively to overcome shortcomings of classical matrix-based theories for martensite crystallography. The extremum principle is used to obtain the atomic paths minimising and maximising the energy from all possible solutions, therefore explaining which sequences are more Thermodynamically feasible. The face-centred cubic (FCC)→body-centred cubic (BCC) transformation in Fe is used as case study. The theory predicts that the average values of the extrema correspond to the crystallography, shear magnitude, interface defects and habit planes of main transformations in Fe, i.e. Widmanstätten Ferrite, Bainite, lath martensite, plate and lenticular martensite. Bainite represents the macroscopic average minimum energy configuration, whereas Widmanstätten Ferrite corresponds to a local and discrete minimum energy configuration. Lath martensite corresponds to the average shear configurations minimising atomic displacements when there is no other driving force, e.g. diffusion, whereas the maximum energy configurations correspond to plate and lenticular martensite forming twin pairs. Targeted results for the FCC→hexagonal close-packed lattice transformation are presented to demonstrate the robustness of the theory. The predictions are combined with elasticity theory to compute the Driving Force and predict the start temperatures – therefore connecting for the first time – local and macroscopic crystallographic features with the Thermodynamics of shear-controlled structures in Fe. This work presents new results towards addressing longstanding challenges in Materials Science such as theoretically demonstrating that Bainite is a shear transformation.

Multi-objective optimization of composite sandwich structures using Artificial Neural Networks and Genetic Algorithm

Sandwich structures offer significant opportunities to improve the performance of many industrial applications such as aerospace, automotive, and marine. The design of a composite sandwich structure is often challenging because it is driven by the balance between the weight and cost of these structures. In this paper, a multi-objective optimization model using a Genetic Algorithm (GA) and an Artificial Neural Network (ANN) is presented to evaluate a new optimization approach in terms of weight and cost minimization for the composite sandwich structures. Classical lamination and beam bending theories were used, along with Monte Carlo simulation, to generate the design data for the proposed composite sandwich structure, which is applied as a floor panel for a high-speed train. Multilayer feedforward neural networks were used for predicting safety factors, cost, and weight of the designed structure based on the following inputs: core density, core thickness, face sheet materials’ combinations, and applied load. The trained Neural Network model was able to predict the considered results with a good performance metric, namely the coefficient of determination (R2 = 0.99) and the Mean Square Error (MSE = 1.3·10−5).Multi-objective optimization for cost and weight minimization was performed with a Genetic Algorithm using the derived ANN model. The obtained Pareto front provided several non-dominated optimal points leading to insights on the optimization process. The Finite Element Method (FEM) was used to model the key points of the optimal designs (i.e. the design with the lowest cost, weight, and Pareto optimal points). The FEM and optimization results had a maximum deviation of about 8.9%, indicating a good agreement between the two techniques.The newly elaborated methodology demonstrates a new approach for obtaining the optimum design of the investigated composite sandwich structure constructed from honeycomb core and laminated face sheets in terms the cost and weight. The study concluded that the use of Carbon Fiber-Reinforced Plastic (CFRP) or Fiber-Metal Laminate (FML) face sheets results in significant weight savings of about 59.5% and 48.6%, respectively, compared to an all-aluminum sandwich structure.

Beam theory of cellular microfilaments based on coarse-grained molecular force field

Microfilaments are the main component of the cell cytoskeleton and have a crucial influence on the morphology of living cells. The microfilaments provide mechanical support against applied loads and overcome competing forces that arise from various mechanisms, such as the elasticity of the cell membrane, binding reactions, and surface tension. However, modeling the mechanical properties of microfilaments is an open problem. In the present paper, we proposed a new continuum deformation energy density of microfilaments using the coarse-grained molecular force field and the local differential geometry of curves. In the new theory, the deformation energy density is a function of the microfilament’s strain and the curvature. This theory also unfolded the connections between the mechanical parameters and the coarse-grained force field. We found that the stretching stiffness and the bending stiffness are independent of the section of microfilaments. Microfilaments have a nonlinear stretching-bending term different from the classical beam theory. This means the classical beam theory cannot be directly applied to microfilaments with large deformations. Our theory provides the basis that the modified classical beam theory applies to the nonlinear mechanical behavior of cellular microfilaments.