Behavior Of Materials Research Articles

Thermo-mechanical aging of carbon-black reinforced styrene-butadiene rubber under cyclic-loading

PurposeThe research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.Design/methodology/approachThis study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.FindingsThis study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.Originality/valueThis research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.

Numerical Study on Heat Transfer and Release Characteristics of Key Components in Electrically Heated Tobacco Products

Electrically heated tobacco products (EHTPs) could release effective aerosol components from tobacco materials at relatively low temperatures without a burning phenomenon. It is essential to grasp the temperature distribution and release mechanism of key components in heated tobacco materials. The existing experimental studies have provided initial insights into the thermodynamic behavior of tobacco materials under various conditions. However, current numerical models are still in their early stages of development, with the majority failing to correlate heat transfer with component release. Based on this, a coupled numerical model of gas flow, heat transfer, and the release of key components in the electrically heated tobacco product is established in this study, which exhibits improvements in revealing the internal heat and mass transfer characteristics in the porous media of tobacco and is capable of evaluating the influence of component contents and product design parameters. The release rates of water, glycerol, and nicotine components are quantitatively described by the first-order Arrhenius formula, and the transport of heat and gas flow is simulated using the Navier-Stokes equation. The accuracy of the model is validated through experiments, including temperature monitoring at multiple measurement points and determination of residual contents in the tobacco substrate after each puff. The simulation results suggest that an appropriate component ratio and tobacco filler mass can enhance both the release amount and release efficiency of key components, and reducing either the diameter or length of the tobacco section can help to improve the heat transfer performance. A slower heating rate matched with longer preheating times enables the complementary release of water and glycerol components, which helps to regulate the uniformity of component content in the aerosol to some extent. This study helps to provide suggestions for the design and optimization of electrically heated tobacco products.

Investigating Microstructure–Property Relationships of Nonwovens by Model-Based Virtual Material Testing

AbstractQuantifying the relationship between geometric descriptors of microstructure and effective properties like permeability is essential for understanding and improving the behavior of porous materials. In this paper, we employ a previously developed stochastic model to investigate microstructure–property relationships of nonwovens. First, we show the capability of the model to generate a wide variety of realistic nonwovens by varying the model parameters. By computing various geometric descriptors, we investigate the relationship between model parameters and microstructure morphology and, in this way, assess the range of structures which may be described by our model. In a second step, we perform virtual materials testing based on the simulation of a wide range of nonwovens. For these 3D structures, we compute geometric descriptors and perform numerical simulations to obtain values for permeability as an effective material property. We then examine and quantify the relationship between microstructure morphology and permeability by fitting parametric regression formulas to the obtained data set, including but not limited to formulas from the literature. We show that for structures which are captured by our model, predictive power may be improved by allowing for slightly more complex formulas.

Composite Coatings Applied to Fresh and Blanched Chayote (Sechium edule) and Modeling of the Drying Kinetics and Sorption Isotherms

Sustainable methods such as convective drying have regained interest in reducing the loss and waste of food produce. Combined with techniques like blanching and edible coatings, they could serve as useful tools in food processing development. Composite coatings comprising pectin, soy protein isolate, and xanthan gum were optimized using response surface methodology with the Box–Behnken design. This optimization aimed to investigate their effects on the moisture content, water activity, total color, and rehydration ratio of fresh and blanched chayote slices. Additionally, the study explored the modeling of the drying kinetics and sorption isotherms of chayote (Sechium edule) slices. Soy protein and xanthan gum were found to primarily influence the moisture content (ranging from 5.44% to 9.93%), and pectin influenced water activity (033 to 0.53) of the fresh-coated chayote, while pectin affected the aw (2.13–8.28) and rehydration of the blanch-coated chayote. The optimized formulations for both fresh and blanched chayote were utilized to assess the drying kinetics behavior and sorption isotherms. The best fit (R2: 0.996 to 0.999) was achieved with the parabolic model for thin-layer materials. Furthermore, the sorption isotherms of chayote displayed a Type IV behavior, with the BET model being the most suitable for describing the sorption behavior of materials with low water activity. The predicted values offer valuable data for optimizing processing conditions to enhance the quality and stability of dried chayote.

Numerical Simulation Study on Impact Initiation on Shielded Charge Using Hypervelocity Composite-Structure Reactive Fragments

In order to study the impact initiation process and mechanism of hypervelocity PTFE/Al composite structure reactive fragments on a shielded charge, first, an existing PTFE/Al reactive fragment hypervelocity collision experiment was numerically simulated using the SPH algorithm in ANSYS/AUTODYN 17.0 software. Then, the Lee–Tarver model was verified to describe the detonation reaction behavior and explosion damage effect of reactive materials. A numerical simulation analysis of the impact of two kinds of ultra-high-speed PTFE/Al composite-structure reactive fragments on a shielded charge was carried out using the SPH algorithm. These were steel-coated PTFE/Al and steel-semi-coated PTFE/Al fragments, and they were compared with the impact of steel fragments. The results indicate that the threshold velocities of the impact initiation of the two composite-structure reactive fragments on the shielded charge were both 2.6 km/s, while the threshold velocity of the steel fragment was 2.7 km/s. Under the threshold velocity condition, the two composite-structure reactive fragments increase the time and intensity of the compressed shock wave pulse in the explosive due to the impact energy release effect of the reactive materials, causing the shielded charge to detonate under the continuous long-term pulse loads. However, the mechanism of the steel fragment on the shielded charge belongs to the shock–detonation transition. The research results can provide scientific references for the design of hypervelocity reactive fragments and the study of their damage mechanism.

A machine learning constitutive model for plasticity and strain hardening of polycrystalline metals based on data from micromechanical simulations

Machine learning (ML) methods have emerged as promising tools for generating constitutive models directly from mechanical data. Constitutive models are fundamental in describing and predicting the mechanical behavior of materials under arbitrary loading conditions. In recent approaches, the yield function, central to constitutive models, has been formulated in a data-oriented manner using ML. Many ML approaches have primarily focused on initial yielding, and the effect of strain hardening has not been widely considered. However, taking strain hardening into account is crucial for accurately describing the deformation behavior of polycrystalline metals. To address this problem, the present study introduces an ML-based yield function formulated as a support vector classification model, which encompasses strain hardening. This function was trained using a 12-dimensional feature vector that includes stress and plastic strain components resulting from crystal plasticity finite element method (CPFEM) simulations on a 3-dimensional RVE with 343 grains with a random crystallographic texture. These simulations were carried out to mimic multi-axial mechanical testing of the polycrystal under proportional loading in 300 different directions, which were selected to ensure proper coverage of the full stress space. The training data were directly taken from the stress–strain results obtained for the 300 multi-axial load cases. It is shown that the ML yield function trained on these data describes not only the initial yield behavior but also the flow stresses in the plastic regime with a very high accuracy and robustness. The workflow introduced in this work to generate synthetic mechanical data based on realistic CPFEM simulations and to train an ML yield function, including strain hardening, will open new possibilities in microstructure-sensitive materials modeling and thus pave the way for obtaining digital material twins.

Exploring Pyroelectricity, Thermal and Photochemical Switching in a Hybrid Organic‐Inorganic Crystal by In Situ X‐Ray Diffraction

AbstractThe switching behavior of the novel hybrid material (FA)Na[Fe(CN)5(NO)].H2O (1) in response to temperature (T), light irradiation and electric field (E) is studied using in situ X‐ray diffraction (XRD). Crystals of 1 display piezoelectricity, pyroelectricity, second and third harmonic generation. XRD shows that the FA+ are disordered at room‐temperature, but stepwise cooling from 273–100 K induces gradual ordering, while cooling under an applied field (E=+40 kVcm−1) induces a sudden phase change at 140 K. Structural‐dynamics calculations suggest the field pushes the system into a region of the structural potential‐energy surface that is otherwise inaccessible, demonstrating that application of T and E offers an effective route to manipulating the crystal chemistry of these materials. Photocrystallography also reveals photoinduced linkage isomerism, which coexists with but is not correlated to other switching behaviors. These experiments highlight a new approach to in situ studies of hybrid materials, providing insight into the structure–property relationships that underpin their functionality.

Synergistic effects of different ionic surfactants and temperature on rheological behavior and air-void structure of cement mortar

The influence of air entrainment on rheological behavior of fresh cementitious materials has attracted a lot of attention in the past years, but the results are still in controversy. In this research, cement mortars were prepared with equivalent air contents using different air-entraining admixtures (AEAs) to measure their fresh-state performance and hardened air-void system at variable temperature conditions, which aimed to clarify and unveil the coupled effects of different surfactants and temperature for the first time. The adsorption amount of AEA, zeta potential of cement, along with hydration kinetics of mixtures were evaluated to characterize the interaction of air bubbles with cement grains. It was found that for mixture without superplasticizer (SP), the impact of air entrainment on rheological parameters was dependent on the interaction intensity of AEA molecules with cement. For SP-plasticized mixture, air entrainment tended to cause a shear-thinning behavior with decreased plastic viscosity, while its influence on yield stress was in accordance with the situation without SP. The hardened samples with anionic surfactant contained more small voids and lacked big voids, whereas the samples with cationic surfactant showed opposite outcomes. With temperature decreasing, both the average chord length and the spacing factor of air voids increased owing to the reduced yield stress of mixture. The results will provide in-depth illustrations for understanding how air bubbles change the rheological behavior of mixture, and more importantly it will explain the seemingly inconsistent findings reported by previous literatures.

Numerical Study of the Thermal Behavior of a Wall Containing Phase Change Material (PCM) in a Hot and Dry Climate

Current buildings in Burkina Faso, particularly in the Sahelian zone, built with local materials are energy-intensive and sources of discomfort for the occupants. However, the role of housing is to provide man with shelter which protects him from external climatic conditions and offers him thermal comfort.  In this work, we present a numerical study of the thermal behavior of a wall containing a phase change material (PCM) in the Sahelian zone. The MCP used in this study is RT27 paraffin with a melting temperature of 27°C and a latent heat of fusion of 179kJ/kg. The equations obtained were adimensionalized and discredited by the finite element method and solved using COMSOL Multiphysics software version 5.3. To this end, we were interested on the one hand in the study of the evolution of the flow of heat and the temperature at the level of the external and internal walls of the wall. On the other hand, we studied the effect of the location of a layer of PCM mortar, simple plaster or cement plaster on the temperature of the internal wall of the wall. The results show the magnitude of heat flux and temperature is greatly reduced by the incorporation of PCM into the wall.

Dynamic Behavior and Permanent Indentation in S2-Glass Woven Fabric Reinforced Polymer Composites under Impact: Experimentation and High-Fidelity Modeling

This paper studies the behavior of S2-glass woven fabric reinforced polymer composite under low-velocity impact at 18–110 J energy. A macro-homogeneous finite element model for the prediction of their response is implemented, considering the non-linear material behavior and intralaminar and interlaminar failure modes for the prediction of impact damage. The model accurately predicted the permanent indentation caused by impact. By applying the Ramberg-Osgood formulation, different initial stiffness values are examined to assess the post-impact unloading response. This approach reveals the significant role of initial stiffness in inelastic strain accumulation and its consequent effect on permanent indentation depth. A higher initial stiffness correlates with increased inelastic strain, influencing the impactor rebound and resulting in greater permanent indentation. By accurately predicting permanent indentation, and damage accumulation for different impact energies, this study contributes to a better understanding of the impact behavior of composite materials, thereby promoting their wider application.

Variability and loss of uniqueness of numerical solutions in FEM×DEM modeling with second gradient enhancement

AbstractIn the last decade, a new multi‐scale FEM×DEM approach has been developed using Finite Element Method (FEM) coupled with Discrete Element Method (DEM) as a constitutive law to account for the specificities of the mechanical behavior of granular materials. In FEM×DEM model, a DEM calculation is performed on a particle assembly (volume element—VE) at each Gauss point. Recent publications have demonstrated that FEM×DEM approach naturally captures the discrete and anisotropic nature of granular materials. Despite its advantages, FEM×DEM with classical FEM, suffers from mesh dependency, especially when material enters softening phase and exhibits strain localization. To overcome this limitation, FEM×DEM model has been enriched by incorporating a local second gradient model. Nevertheless, the existence of multiple possible solutions is observed. In this paper, we study the variability and loss of uniqueness of numerical solutions to a boundary value problem. Different VEs with equivalent mechanical properties are generated and used to model the pressuremeter tests by means of FEM×DEM. The modeling results show a great variability of the numerical results, both in shape of borehole and in different modes of shear bands. For the same VE, the loss of uniqueness of numerical solutions is evidenced by a slight modification of loading history at the level of the internal pressure applied to the borehole. Finally, we show that when a certain heterogeneity is introduced by using different VEs within the same BVP, even if the uniqueness of the solution is not guaranteed, the set of possible solutions seems more restrained.

Comparative Study on the Electrochemical Behaviors of Positive Electrode Materials of Lithium-ion Batteries during Overdischarge

Abstract As lithium-ion battery (LIB) use rises, recycling becomes imperative. Efficiently overdischarging LIBs for residual energy extraction is crucial for safe recycling. Our study analyzes the electrochemical behavior during overdischarge for positive electrode materials, including LiNi0.6Co0.2Mn0.2O2 (NCM622), LiNi0.8Co0.1Mn0.1O2 (NCM811), LiFePO4 (LFP), LiCoO2 (LCO), and LiMn2O4 (LMO). Electrochemical evaluations involve half cells and full cells subjected to constant current overdischarge beyond normal operating ranges. In positive electrode half-cells, a material-dependent conversion reaction was observed, while full cells exhibited similar behaviors during overdischarge to 0 V due to increasing voltage at the negative electrode. Distinct electrochemical variations emerged under forced discharge below 0 V, particularly in the NCM series, showing a gradual voltage decrease to -2 V followed by an internal short circuit. In contrast, LFP, LCO, and LMO swiftly stabilized near 0 V, attributed to the lower initial Coulombic efficiency of NCM materials leading to an early rise in negative electrode potential. To recycle used lithium-ion batteries (LIBs), it's crucial to optimize conditions that ensure both efficient and safe overdischarge, considering the characteristics of positive electrode materials.

Semantics-Enabled Data Federation: Bringing Materials Scientists Closer to FAIR Data

AbstractThe development and discovery of new materials can be significantly enhanced through the adoption of FAIR (Findable, Accessible, Interoperable, and Reusable) data principles and the establishment of a robust data infrastructure in support of materials informatics. A FAIR data infrastructure and associated best practices empower materials scientists to access and make the most of a wealth of information on materials properties, structures, and behaviors, allowing them to collaborate effectively, and enable data-driven approaches to material discovery. To make data findable, accessible, interoperable, and reusable to materials scientists, we developed and are in the process of expanding a materials data infrastructure to capture, store, and link data to enable a variety of analytics and visualizations. Our infrastructure follows three key architectural design philosophies: (i) capture data across a federated storage layer to minimize the storage footprint and maximize the query performance for each data type, (ii) use a knowledge graph-based data fusion layer to provide a single logical interface above the federated data repositories, and (iii) provide an ensemble of FAIR data access and reuse services atop the knowledge graph to make it easy for materials scientists and other domain experts to explore, use, and derive value from the data. This paper details our architectural approach, open-source technologies used to build the capabilities and services, and describes two applications through which we have successfully demonstrated its use. In the first use case, we created a system to enable additive manufacturing data storage and process parameter optimization with a range of user-friendly visualizations. In the second use case, we created a system for exploring data from cathodic arc deposition experiments to develop a new steam turbine coating material, fusing a combination of materials data with physics-based equations to enable advanced reasoning over the combined knowledge using a natural language chatbot-like user interface.

Enhancing Magnetic Material Data Analysis with Genetic Algorithm-Optimized Variational Mode Decomposition

As the application of machine learning technology in predicting and optimizing material performance continues to grow, handling the electromagnetic data of magnetic materials, especially in removing unavoidable data noise and accurately extracting resonance peaks in the imaginary part of electromagnetic information, has become a significant challenge. These steps are crucial for revealing the deep electromagnetic behavior of materials and optimizing their performance. In response to this challenge, this study introduces an innovative approach—Genetic Algorithm-Optimized Variational Mode Decomposition for Signal Enhancement (GAO-VMD-SE). This method, through the Variational Mode Decomposition (VMD) technique optimized by genetic algorithms, not only effectively reduces noise in the data, thereby improving the Signal-to-Noise Ratio (SNR) and reducing the Mean Absolute Error (MAE), but also significantly enhances the hidden resonance peak information in complex permittivity and permeability data to achieve a comprehensive improvement in key performance indicators. Experimental results prove that this method surpasses traditional analysis techniques in key performance metrics such as the peak width ratio, peak overlap ratio, and the number of peaks. Especially in identifying characteristic peaks related to the Snoek limit, GAO-VMD-SE can effectively reveal the peak features hidden in complex data, thus providing important insights for evaluating the performance of materials at specific frequencies. Moreover, the effectiveness of this method in denoising not only enhances the quality and accuracy of material data analysis but also achieves a 1% to 10% enhancement in peak information extraction. This optimized data processing capability and versatility make GAO-VMD-SE not only suitable for evaluating the performance of magnetic materials but also show significant practical application value in processing spectral data and other time series signal data applications.

Fabrication and Characterization of a Magnetic 3D‐printed Microactuator

AbstractConventional MEMS microactuators have, in recent years, been complemented by 3D‐printed actuatable microstructures fabricated via two‐Photon‐Polymerization (2PP). Herein, a novel compact 3D‐printed magnetically actuatable microactuator with a diameter of 500µm is demonstrated, originally designed for micro‐optical systems. It is fabricated by incorporating a composite of NdFeB microparticles and epoxy resin into a designated reservoir of the printed mechanical structure within a simple post‐processing step. The microactuator structure features mechanical springs, allowing for continuous positioning with large displacement. Mechanical studies by nanoindentation of IP‐S bulk structures reveal a viscoelastic material behavior, described by a two‐element General Kelvin‐Voigt viscoelasticity model. The obtained material parameters are then used to simulate and characterize the spring behavior of the microactuator. Actuation experiments are conducted using an external microcoil. The actuator displacement is measured for triangular current pulses with a peak current of 106 mA and durations of 1 to 100 s, resulting in displacements of 69.1 to 88.9 µm. Hysteretic behavior of the actuator is observed, attributable to viscoelasticity and magnetic properties of the core material. Numerical simulations of the experiment demonstrate this behavior as well. On‐the‐fly demagnetization and the implementation of closed‐loop control allow for both high repeatability and precise positioning.

Analysis of Plastic Deformation of Pipes Due to Deflagration to Detonation Transition Using Static Equivalent Pressure

Abstract Explosions of premixed gases with deflagration to detonation transition (DDT) are a risk in the process industry with potentially catastrophic consequences. Robust and simple design methods are required for industrial use. Such a simplified design method based on finite element analysis is proposed to model the dynamic behavior of pipes loaded by gas explosions of premixed gases including DDT. The focus is on so-called long pipes, where the DDT is not affected by reflections at blind flanges. First, it is reviewed how the pressure load of the gas explosion and the resulting material behavior has been modeled in previous publications. The analytical equations are then extended for describing the pressure load as a function of time and location by considering the leading compression wave as it affects the pressure load of the overdriven detonation. The extended analytical equations are parameterized using Chapman-Jouguet conditions and experimental results from publications for both static equivalent pressure and the location of the DDT. To describe the plastic material behavior at high strain rates, the well-known Johnson-Cook plasticity model is used. The material parameters of the model are derived from simple experiments, which are available in an industrial environment. The comparison of a finite element simulation with experimental data shows that the concept of equivalent static pressure can be extended to an finite element analysis, which in the future will allow the sizing of complete pipe systems including tees, bends, and flanges while considering plastic deformation.

Adaptiveand RobustVitrimers Fabricated by Synergy of Traditional and Supramolecular Polymers.

Vitrimers offer a unique combination of mechanical performance, reprocessability, and recyclability that makes them highly promising for a wide range of applications. However, achieving dynamic behavior in vitrimeric materials at their intended usage temperatures, thus combining reprocessability with adaptivity through associative dynamic covalent bonds, represents an attractive but formidable objective. Herein, we couple boron-nitrogen(B-N) dative bonds and B-O covalent bonds to generate a new class of vitrimers, boron-nitrogen vitrimers (BNVs), to endow them with dynamic features at usage temperatures. Compared with boron-ester vitrimers (BEVs) without B-N dative bonds, the BNVs with B-N dative bonds showcase enhanced mechanical performance. The excellent mechanical properties come from the synergistic effect of the dative B-N supramolecular polymer and covalent boron‒ester networks.Moreover, benefiting from the associative exchange of B-O dynamic covalent bonds above their topological freezing temperature (Tv), the resultant BNVs also possess the processability. This study leveraged the structural characteristics of a boron-based vitrimer to achieve material reinforcement and toughness enhancement, simultaneously providing novel design concepts for the construction of new vitrimeric materials.

Adaptive and Robust Vitrimers Fabricated by Synergy of Traditional and Supramolecular Polymers

Vitrimers offer a unique combination of mechanical performance, reprocessability, and recyclability that makes them highly promising for a wide range of applications. However, achieving dynamic behavior in vitrimeric materials at their intended usage temperatures, thus combining reprocessability with adaptivity through associative dynamic covalent bonds, represents an attractive but formidable objective. Herein, we couple boron–nitrogen (B−N) dative bonds and B−O covalent bonds to generate a new class of vitrimers, boron–nitrogen vitrimers (BNVs), to endow them with dynamic features at usage temperatures. Compared with boron−ester vitrimers (BEVs) without B−N dative bonds, the BNVs with B−N dative bonds showcase enhanced mechanical performance. The excellent mechanical properties come from the synergistic effect of the dative B−N supramolecular polymer and covalent boron‒ester networks. Moreover, benefiting from the associative exchange of B−O dynamic covalent bonds above their topological freezing temperature (Tv), the resultant BNVs also possess the processability. This study leveraged the structural characteristics of a boron‐based vitrimer to achieve material reinforcement and toughness enhancement, simultaneously providing novel design concepts for the construction of new vitrimeric materials.

Tensile assessment of woven CFRP using finite element method: A benchmarking and preliminary study for thin-walled structure application

Abstract Carbon-fiber-reinforced polymers (CFRPs) are a composite material popular for thin-walled structure applications because of their advantages over other materials. In this study, numerical simulation analysis based on the finite-element method to identify the tensile behavior of CFRP woven material has been carried out. The method used has been verified and validated using a benchmarking procedure with the results of previous research. Errors in the simulation results are less than 10%, indicating a valid method that can be used for further research. The stress–strain distribution of each layer, the effect of ply orientation on tensile strength, the comparison of failure criteria used, and the comparison of several types of reinforcements often used have been investigated. The results showed that the characteristics of each inner layer received tensile loading visualized in the form of stress strains. Choosing the right layer angle on CFRP woven can affect the performance and strength of the material. Failure criteria that are appropriate to specific application conditions are important. Puck criteria can be used for simple applications, which require only the analysis of the main stresses in the material. Tsai–Hill and Tsai–Wu criteria can provide more accurate predictions and are better suited for loading conditions and more complex material types. Carbon fiber has better characteristics when compared to S-glass and E-glass.

Insight into single-helix intelligent shape memory polymer cables: Modeling and optimization under finite sliding contact

Abstract Proposing shape memory polymer (SMP) materials for lifting and rigging equipment can foster unparalleled advancements and several potential applications in various industries. This pioneering study focuses on the thermomechanical properties of SMP wire ropes and their components during programming steps for small- and finite-sliding contact deformation. Employing existing experimental data and numerical results, we validate our finite element analysis (FEA) for both geometric modeling and non-linear material behavior. Owing to intricate geometry, as well as excessive wire interactions, the former is studied by simulating a 1×37 steel wire rope, and the thermomechanical property of an SMP rectangular bar under a uniaxial test is modeled to verify both constrained and unconstrained recovery behavior. After rigorous validation, two configurations of 1×7 and 1×27 SMP cables are modeled based on the thermo-visco-hyperelastic constitutive framework. Exerting an axial load on these wire ropes, the response of force and shape recovery, as well as the normal and shear stress distributions, are measured under constrained and unconstrained conditions. For a deeper physical understanding, we also conduct parametric studies to elucidate the influences of temperature rate, frictional coefficient, and multiple-shape programming on the performance of SMP cables. Furthermore, to propose a comprehensive discussion on these newly developed instruments, the specific energy of a 1×6 SMP cable is maximized using the design of experiments based on optimizing two cable factors of diameter and helix angle. This study tries to cast light on the remarkable features and possible potential of SMP cables in applications under different thermomechanical loadings.