Steady-state Behavior Research Articles

Solving for the Thermal Vibration Behaviors of Functionally Graded Stepped Conical Curved Plates with Point Connection Conditions

This paper proposed a degree-of-freedom reduction model for the rapid and unified solution of the modal and steady-state response behavior of functionally graded stepped conical curved plates with point connections under thermal environments. Within the framework of the first-order shear deformation theory, the two-dimensional spectral Chebyshev method and the fixed interface modal synthesis method were combined to derive the degree-of-freedom reduction model for functionally graded conical curved plates under thermal environments. Each reduction model was assembled considering external load excitations. Virtual springs were used to equivalently handle the coupling interface forces and point connection interface forces, further establishing a thermal vibration response analysis model for functionally graded stepped conical curved plates with point connections. In numerical examples, this degree-of-freedom reduction model was compared with experimental results and overall finite element results, validating the accuracy of the model and the advantages of rapid solution. Additionally, this degree-of-freedom reduction model was applied to quickly analyze the effects of material parameters and point connection parameters on the thermal steady-state response of the structure, providing a theoretical basis for the environmental adaptability design, verification, and evaluation of such structures.

Analytical prediction for the steady-state behavior of a confined drop with interface viscosity under shear flow

Analytical prediction for the steady-state behavior of a confined drop with interface viscosity under shear flow

Mathematical Modelling and Chemical Analysis to Characterise Anthocyanin Self-association Interactions Influencing Colour Expression and Stability in Young Red Wines

AbstractAnthocyanins are phenolic compounds that provide colour to young red wines following extraction from grape skins, and their reaction kinetics are not well understood as they exist within a complex pH-dependent multistate system. For commercial wineries to best control anthocyanin colour expression that is a major determinant for red wine quality, there is a critical need for behaviours of all pH-dependent monomeric and self-associated anthocyanins to be considered together. In response, the current study employed mathematical and experimental techniques to reveal kinetic and steady-state behaviours of all species of a model anthocyanin, malvidin-3-O-β-D-glucopyranoside (M3G), within three Shiraz red wines throughout fermentation. Investigator-developed models represented the following: (i) acid–base reactions that form red, purple, and blue anthocyanin monomers; (ii) hydration reactions that result in monomeric colour loss; and (iii.) physical self-association interactions that temporally stabilise anthocyanin colour. Simulations were validated experimentally using high-performance liquid chromatography with diode array detector (HPLC–DAD) and colourimetric analysis of wine samples. Moreover, a unique predictive modelling framework was developed that takes in measured values for anthocyanin concentration, pH, and temperature at the onset of fermentation, and output data describing corresponding wine colour expression and stability characteristics that would arise after fermentation has progressed. Results of the current study elucidate complex reaction kinetics occurring between anthocyanin species under dynamic red wine conditions and provide meaningful predictions for future wine colour and shelf-life characteristics. Outputs may be used to inform key winemaking decisions influencing red wine quality and to optimise the use of winery resources throughout the fermentation process.

Nonlinear Adaptive Neural Control of Power Converter‐Driven DC Motor System: Design and Experimental Validation

ABSTRACTThis article presents an intelligent adaptive neural control scheme to track the output speed trajectory in power converter‐driven DC motor system. The proposed technique integrates an adaptive polynomial‐neural network with a backstepping strategy to yield a robust control system for output tracking in DC motor. Such a unification of online neural network‐based estimation and adaptive control, results in effective regulation of the output across a wide load torque uncertainties, besides yielding a promising transient and steady‐state performance. The stability of the entire closed‐loop system is ensured through Lyapunov stability criterion. The efficacy of the proposed strategy is revealed through an extensive experimental investigation under various operating points during start‐up, step‐reference tracking, and external step‐load torque disturbances. The real‐time experimentation is conducted on a laboratory prototype of power converter‐driven DC motor of 200 W, using dspace DS1104 control board with MPC8240 processor. The results obtained confirm an improvement in the transient response of the output speed by significantly reducing the settling time to and yielding a steady state behavior with no peak over/undershoots during load disturbances, in contrast to other similar works presented in the literature intended for same the application.

Exploring Non-linear Dynamics: Constructing the Bifurcation Diagram of a Damped Driven Pendulum using Python

In this paper, we present a detailed analysis and construction of the bifurcation diagram for the damped-driven pendulum system. The bifurcation diagram in general presents the qualitative changes of the steady-state behavior for the pendulum. For this purpose, we implement the use of the Python programming language with the inclusion of scientific libraries. This nonlinear dynamical system is an example of a system that exhibits a chaotic regime, which is the sensitivity of its behavior to the initial conditions and the parameters of the system. We investigate the response of the system to a range of drive strengths γ applied. By changing the driving strength, the system reveals patterns of periodicity, quasi-periodic, and chaotic regimes. The critical values where it goes from regular motion to chaotic one are highlighted, offering further understanding of the mechanisms of the transitions. This study presents the use of the Python programming language for the modeling and visualization of non-dynamic systems and contributes to a deeper understanding of nonlinear oscillator dynamics.

Characterize the high-temperature steady-state rheological behavior and Arrhenius activation of PEEK via strain rate jump tensile tests

Polyetheretherketone (PEEK) is a high-performance thermoplastic polymer with diverse industrial applications, such as aerospace, automotive, electronics, and medical devices. However, systematic research on its high-temperature rheological characteristics is inadequate. In this study, strain rate jump tensile tests were introduced to examine the steady-state rheology phenomena and strain rate sensitivity of PEEK at four different temperatures and nine different strain rates. Theoretical analysis based on the free volume theory and the Arrhenius law was also carried out to further analyze the transition of PEEK from Newtonian flow to non-Newtonian flow. Results indicate that PEEK materials exhibit a transition from Newtonian flow to non-Newtonian flow similar to metal materials at high temperatures. The transition point from Newtonian flow to non-Newtonian flow is marked by the emergence of steady-state rheology and its characteristic stress. Theoretical analysis demonstrates that the transition of PEEK is in accordance with the Arrhenius low. Moreover, its apparent activation energy (1.42 eV) is significantly lower than that of metal materials (5.28 eV), indicating a lower energy barrier and an easier transition. The strain rate sensitivity index correlates negatively with rising temperatures, especially at lower rates. This study enhances understanding of PEEK's rheological characteristics at high temperatures, aiding the development and application of high-performance thermoplastic materials.

Quantifying Creep on the Laohushan Fault Using Dense Continuous GNSS

The interseismic behavior of faults (whether they are locked or creeping) and their quantitative kinematic constraints are critical for assessing the seismic hazards of faults and their surrounding areas. Currently, the creep of the eastern segment of the Laohushan Fault in the Haiyuan Fault Zone at the northeastern margin of the Tibetan Plateau, as revealed by InSAR observations, lacks confirmation from other observational methods, particularly high-precision GNSS studies. In this study, we utilized nearly seven years of observation data from a dense GNSS continuous monitoring profile (with a minimum station spacing of 2 km) that crosses the eastern segment of the Laohushan Fault. This dataset was integrated with GNSS data from regional continuous stations, such as those from the Crustal Movement Observation Network of China, and multiple campaign measurements to calculate GNSS baseline change time series across the Laohushan Fault and to obtain a high spatial resolution horizontal crustal velocity field for the region. A comprehensive analysis of this primary dataset indicates that the Laohushan Fault is currently experiencing left-lateral creep, characterized by a partially locked shallow segment and a deeper locked segment. The fault creep is predominantly concentrated in the shallow crustal region, within a depth range of 0–5.7 ± 3.4 km, exhibiting a creep rate of 1.5 ± 0.7 mm/yr. Conversely, at depths of 5.7 ± 3.4 km to 16.8 ± 4.2 km, the fault remains locked, with a loading rate of 3.9 ± 1.1 mm/yr. The shallow creep is primarily confined within 3 km on either side of the fault. Over the nearly seven-year observation period, the creep movement within approximately 5 km of the fault’s near field has shown no significant time-dependent variation, instead demonstrating a steady-state behavior. This steady-state creep appears unaffected by postseismic effects from historical large earthquakes in the adjacent region, although the deeper (far-field) tectonic deformation of the Laohushan Fault may have been influenced by the postseismic effects of the 1920 Haiyuan M8.5 earthquake.

Ultra-high voltage gain achieved with quadratic DC/DC converter design

This work introduces a novel DC/DC converter with an incredibly high voltage gain, specifically designed for renewable energy generating systems. The proposed circuit features a coupled inductor integrated with a quadratic boost circuit and a voltage multiplier cell to achieve a substantial step-up in voltage gain. Ultra-high voltage gain, minimum reverse recovery in diodes, low voltage stress on switching devices, continuous input current, and a shared ground between the input source and output load are some of this topology’s key features. The coupled inductor design reduces power dissipation in magnetic components by distributing the high DC source current with an additional input inductor. Additionally, regenerative clamp circuits alleviate voltage stresses on power switches during simultaneous switching. Theoretical analysis covering the operating principle, steady-state behavior, and efficiency is discussed in detail. An evaluation of the suggested topology’s performance is conducted using a 250-W, 25-V/400-V lab prototype.

Dynamics of two feed forward genetic motifs in the presence of molecular noise

Understanding the function of common motifs in gene regulatory networks is an important goal of systems biology. Feed forward loops (FFLs) are an example of such a motif. In FFLs, a gene (X) regulates another gene (Z) both directly and via an intermediary gene (Y). Previous theoretical studies have suggested several possible functions for FFLs, based on their transient responses to changes in input signals (using deterministic models) and their fluctuations around steady state (using stochastic models). In this paper we study stochastic models of the two most common FFLs, “coherent type 1” and “incoherent type 1”. We incorporate molecular noise by treating DNA binding, transcription, translation, and decay as stochastic processes. By comparing the dynamics of these loops with models of alternative networks (in which X does not regulate Y), we explore how FFLs act to process information in the presence of noise. This work highlights the importance of incorporating realistic molecular noise in studying both the transient and steady-state behavior of gene regulatory networks.

Analyzing steady-state equilibria and bifurcations in a time-delayed SIR epidemic model featuring Crowley-Martin incidence and Holling type II treatment rates

This article presents a time-delayed SIR epidemiological model that has been quantitatively examined. The model incorporates a logistic growth function for the susceptible population, a Crowley-Martin type incidence, and Holling type II treatment rates. We investigated two separate time delays. The first delay refers to the rate at which new infections occur, allowing us to evaluate the impact of the latent period. The second delay relates to the rate of treatment for those who have contracted the infection, which allows us to examine the consequences of postponed access to therapy. The investigation of the steady-state behavior of the model emphasizes two equilibria, namely, the infection-free equilibrium and the endemic equilibrium. The determination of critical values involves the use of the fundamental reproduction number, denoted R0, which serves as a predictive measure to determine the potential elimination of a disease within a specific population. Using the fundamental reproduction number, it can be shown that infection-free equilibrium exhibits local asymptotic stability when the value of R0 is less than 1. In contrast, when R0 exceeds 1, the infection-free equilibrium becomes unstable in the context of the time-delayed system. Furthermore, an analysis of the steady-state dynamics of the endemic equilibrium indicates the appearance of oscillations and periodic solutions with the Hopf bifurcation for all feasible combinations of two-time delays as the bifurcated parameter. In sensitivity analysis, a sensitivity index is utilized to evaluate the relative modification in the fundamental reproduction number caused by each parameter. In summary, numerical simulations are employed to offer empirical evidence for the theoretical findings.

Performance of Organic Electrochemical Transistors with Ionic Liquid Crystal Elastomers as Solid Electrolytes.

Organic electrochemical transistors (OECTs) have emerged as attractive devices for bioelectronics, wearable electronics, soft robotics, and energy storage devices. The electrolyte, being a fundamental component of OECTs, plays a crucial role in their performance. Recently, it has been demonstrated that ionic liquid crystal elastomers (iLCEs) can be used as a solid electrolyte for OECTs. Their capabilities, however, have only been shown for relatively large size substrate-free OECTs. Here, we study the influence of the different alignments of iLCEs on steady state and transient behavior of OECTs using a lateral geometry with source, drain, and gate in the same plane. We achieve excellent electrical response with an ON/OFF switching ratio of >105 and minimal leakage current. The normalized maximum transconductance gm/w of the most sensitive iLCE was found to be 33 S m-1, which is one of the highest among all solid-state-based OECTs reported so far. Additionally, iLCEs show high stability and can be removed and reattached multiple times to the same OECT device without decreasing performance.

The effect of weak proton donors on the steady-state behavior of hydrogen evolution in mildly acidic media

The influence of anionic and cationic electro-inactive species on the steady-state current of the Hydrogen Evolution Reaction (HER) is often not considered. Here, the effects of these widely-used electrolyte species on the steady-state behavior of HER are investigated on a Au RDE at a bulk pH of 4. A current enhancement is observed from the coupling of proton reduction with homogeneous acid-base equilibria, with HSO4− having the largest influence despite the electrolyte condition being far beyond its typical buffering range, while the cations, specifically K+ and Cs+, serve as weak buffers with limited buffer capacity. Further quantitative analysis illustrates that from the steady-state current of HER the thermodynamic parameters of the homogeneous reactions can be evaluated, taking advantage of the linear dependence of the Koutecký-Levich Slope on the concentration of the electro-inactive species. Based on this evaluation, the pKa‘s of HSO4−, K+ and Cs+ were determined to be 2.06, 2.52 and 2.48, respectively. These results confirm the previously postulated proton-donating capability of certain (alkali) cations and show that these effects influence the HER current in mildly acidic media.

A Generalized Method for Deriving Steady-State Behavior of Consistent Fuzzy Priority for Interdependent Criteria

Interdependent criteria play a crucial role in complex decision-making across various domains. Traditional methods often struggle to evaluate and prioritize criteria with intricate dependencies. This paper introduces a generalized method integrating the analytic network process (ANP), the decision-making trial and evaluation laboratory (DEMATEL), and the consistent fuzzy analytic hierarchy process (CFAHP) in a fuzzy environment. The Drazin inverse technique is applied to derive a fuzzy total priority matrix, and we normalize the row sum to achieve the steady-state fuzzy priorities. A numerical example in the information systems (IS) industry demonstrates the approach’s real-world applications. The proposed method derives narrower fuzzy spreads compared to the past fuzzy analytic network process (FANP) approaches, minimizing objective uncertainty. Total priority interdependent maps provide insights into complex technical and usability criteria relationships. Comparative analysis highlights innovations, including non-iterative convergence of the total priority matrix and the ability to understand interdependencies between criteria. The integration of the FANP’s network structure with the fuzzy DEMATEL’s influence analysis transcends the capabilities of either method in isolation, marking a significant methodological advancement. By addressing challenges such as parameter selection and mathematical complexity, this research offers new perspectives for future research and application in multi-attribute decision-making (MADM).

Stress and temperature dependence of irradiation creep in zircaloy-4 studied using proton irradiation

This paper describes a series of experiments conducted to investigate the in-situ irradiation creep behavior of Zircaloy-4 using proton irradiations as a surrogate to neutrons. The first series of experiments investigated the impact of the initial irradiation-induced defect evolution during the 0 – 0.1 dpa regime on the subsequent in-situ steady-state behavior derived from experimentation. These experiments were conducted at a constant applied load of 85 MPa, a constant damage rate of 1.58 × 10−6 dpa/s, and were repeated at both 250 °C and 350 °C. We also examined the use of a ‘conditioning-irradiation’ step prior to the creep tests on the results derived from subsequent in-situ proton irradiation creep experiments. By extension, we aimed to further develop and refine optimum testing procedures when using proton irradiations to investigate the in-situ creep behavior of nuclear materials. The second series of in-situ proton irradiation experiments were conducted on two Recrystallized (RX) Zircaloy-4 samples in order to investigate the temperature and stress dependence of irradiation creep. One sample was held at a constant load while the temperature was varied in the range of 275 – 350 °C, and the other was held at a constant temperature while stress was varied in the range of 65 – 105 MPa. The associated strains and creep rates were measured at each interval and used to determine an activation temperature of 5000 ± 1700 K and a stress sensitivity exponent of 4.3 ± 0.8 for RX Zr-4 over the given temperature and stress ranges. A discussion of potential deformation mechanisms based on competition between bulk diffusion through the lattice and point defect diffusion enabling dislocation climb and glide is given: the relatively high stress dependence suggested the latter is more likely however further investigations will be required to improve the mechanistic understanding. The results presented in this manuscript, including activation temperature, stress sensitivity, and associated creep rates, determined through proton irradiation investigations are closely comparable to those determined from neutron irradiation experiments found in the literature for similar zirconium alloys at similar temperatures and stresses. Coupled with the primary-secondary creep behavior investigations presented, this demonstrates the usefulness of this approach to estimate neutron-irradiation equivalent creep behavior using in-situ proton irradiation.

Performance analysis of unconstrained partitioned-block frequency-domain adaptive filters in under-modeling scenarios

The unconstrained partitioned-block frequency-domain adaptive filter (PBFDAF) offers superior computational efficiency over its constrained counterpart. However, the correlation matrix governing the natural modes of the unconstrained PBFDAF is not full rank. Consequently, the mean coefficient behavior of the algorithm depends on the initialization of adaptive coefficients and the Wiener solution is non-unique. To address the above problems, a new theoretical model for the deficient-length unconstrained PBFDAF is proposed by constructing a modified filter weight vector within a system identification framework. Specifically, we analyze the transient and steady-state convergence behavior. Our analysis reveals that modified weight vector is independent of its initialization in the steady state. The deficient-length unconstrained PBFDAF converges to a unique Wiener solution, which does not match the true impulse response of the unknown plant. However, the unconstrained PBFDAF can recover more coefficients of the parameter vector of the unknown system than the constrained PBFDAF in certain cases. Also, the modified filter coefficient yields better mean square deviation (MSD) performance than previously assumed. The presented alternative performance analysis provides new insight into convergence properties of the deficient-length unconstrained PBFDAF. Simulations validate the analysis based on the proposed theoretical model.

Effects of Carbon Fiber Content on the Crystallization and Rheological Properties of Carbon Fiber-Reinforced Polyamide 6.

Carbon fiber (CF)-reinforced polyamide 6 (PA6) composites have an excellent performance, attributed to properties such as light quality, high strength, and vibration reduction, and they are widely used in fields such as aerospace and transportation. Four kinds of carbon fiber-reinforced polyamide 6 (CF/PA6) composite pellets with carbon fiber contents of 20, 30, 40, and 50 wt.% were prepared using twin screw extrusion. The results were characterized using a simultaneous thermal analyzer, capillary rheometer, electronic universal material testing machine, and scanning electron microscope (SEM); their crystallization, rheological behavior, mechanical properties, surface structure, etc., were studied. DSC results indicate that an increase in carbon fiber content enhances the thermal stability of CF/PA6 and narrows the crystallization window but has a minor effect on the molecular chain diffusion time. The crystallinity reaches its maximum at a carbon fiber content of 40 wt.%, reaching 55.16%. The steady-state rheological behavior reveals that CF/PA6 behaves as a pseudoplastic fluid, exhibiting shear-thinning behavior. When the carbon fiber content is 40 wt.%, the power law exponent (n) reaches its maximum, and the consistency coefficient (K) decreases by 300 Pa⋅sn compared to the 30 wt.% content. With increasing temperature, n increases while K decreases. SEM observations reveal that samples with carbon fiber contents of 20 wt.% and 40 wt.% exhibit better fiber dispersion and orientation. However, the interfacial bonding strength is superior in the 40 wt.% sample. When the carbon fiber content reaches 50 wt.%, significant injection molding defects occur at the clamping end, leading to extensive matrix tearing during tension testing.

Performance comparison between PID and Fuzzy logic controllers for the hardware implementation of traditional high voltage DC-DC boost converter

This research introduces a hardware implementation of DC-DC boost converter designed to elevate the DC voltage generated by renewable sources while effectively regulating it against line and load fluctuations for inverter application. The main objective is to boost the DC link voltage to the level of Vmax in the output AC voltage obtained from inverter circuits. This enables the inverters for transformer-less power conversion from DC to AC to reduce magnetic losses, size and weight of the inverter circuits used in the utility application. The proposed converter's topology and switching sequences play a crucial role in enhancing overall performance. Utilizing a Zero Current Switching (ZCS) technique, the converter efficiently recovers stored energy from the magnetics. The proposed converter attained the output voltage of 350 V at its current of 1A from the input voltage of 20 V at its current of 19 A. The ZCS technique and the topology of the converter enhances the efficiency to 92 %. The study employs traditional Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers for effective voltage regulation, analysing time domain specifications. Additionally, a Fuzzy logic controller is introduced as an alternative to PID controllers to compare their performance metrics, evaluating the optimization of the converter's transient and steady-state behaviours. The proposed converter is designed, simulated and their performance metrics are analysed using MATLAB for both with and without controllers. The step-time characteristics of the proposed converter with load resistance of RL = 500 Ω and an input voltage of Vi = 20 V has been determined and analysed. The PID system attained a rise time of 88.781 ms, an overshoot value of 9.341 %, and a steady-state error of 0.00043. The fuzzy system achieved a low-rise time of 10.624 ms, a low overshoot of 0.55 %, and a steady-state error of 0.0584. The hardware prototype of the proposed converter is implemented with a FPGA based PID and Fuzzy logic controllers for providing better voltage regulation and to improve the performance metrics of the converter. The simulation and experimental findings are contrasted, examined, and confirmed to ensure improved consistency in performance measures.

Photometry, rotation period determination and dust coma numerical study of comet C/2017 K2 (PanStarrs)

C/2017 K2 (Pan-STARRS) is an Oort cloud comet discovered in May 2017. Ground observations have revealed that this long-period comet was active at a heliocentric distance beyond 20 au. Several studies observed this object when it was far from the Sun and proposed that, at such a distance, its activity is primarily driven by the sublimation of super-volatile ices such as CO and CO2.The aim of this paper is to analyze the comet’s dust behavior when it was much closer to the Sun. A series of images were taken on different observation routines between July and August 2022 with the 0.6 m Helen Sawyer Hogg (HSH) telescope at the Complejo Astronómico El Leoncito (CASLEO), using broadband V and R filters. The objective was to conduct a morphological, photometric, and numerical analysis of this comet.Digital filters were applied to enhance contrast in the cometary images, revealing an active region embedded within an isotropic coma. Analysis of the magnitudes and dust production rate from the A(0°)fρ parameter suggests a steady-state dust behavior, consistent with findings from other authors.Moreover, thanks to the images covering a significant time span, it was possible to determine the comet’s rotation period using a periodogram analysis with the Phase Dispersion Minimization method (PDM) and to calculate the coordinates of the rotation axis, yielding a rotation period of 14.24 h with a pole situated at the ecliptic longitude and latitude of (244°,−20°).Finally, to gain deeper insights into C/2017 K2’s dust behavior, observations were fitted to a newly developed theoretical model for studying dust comas. The analysis suggests that the comet’s dust coma was principally formed by large dust particles emitted at a velocity of 180ms−1.

Frequency-domain diffusion adaptation over networks with missing input data

Recently, a modified adapt-then-combine diffusion (mATC) strategy has been developed to handle distributed estimation problem with missing regressions (inputs). However, the mATC algorithm only considers the white input scenario and suffers from high complexity for long model filter lengths. To overcome these shortcomings, this paper proposes novel regularization-based frequency-domain diffusion algorithms for networks with missing input data. First, bias-eliminating cost function based on regularization is established by using the frequency-domain diagonal approximation. Then, with stochastic gradient descent, periodic update, and power normalization schemes, we design the regularization-based frequency-domain least mean square (R-FDLMS) algorithm as well as its normalized variant (R-FDNLMS). The latter converges faster than the former under colored inputs. The stability and steady-state behavior of the R-FDNLMS algorithm are also analyzed. Moreover, two effective power estimation methods are presented for both situations without and with the power ratio between the input signal and perturbation noise, along with a reset mechanism in the first case to enhance tracking performance. Finally, simulations are conducted to illustrate the superiority of the proposed algorithms and the validity of theoretical findings.

Investigate the influence of GO as an additive in the silica-based polyethylene glycol shear thickening fluid on the rheological properties

Abstract Shear thickening fluids (STF) represent stabilized and concentrated colloidal suspensions, wherein hard nanoparticles are dispersed within a liquid medium (polymer). Under the influence of impact forces, they exhibit non-Newtonian behavior, effectively dissipating energy through shear thickening. The optimization of the dispersion medium’s viscosity is critical, as it not only fosters shear thickening but also facilitates proper particle dispersion. This study investigates the impact of graphene oxide (GO) as an additive in STFs, analyzing both static and dynamic rheological properties. STFs were formulated using colloidal silica particles (600 nm) and polyethylene glycol (PEG-200), with varied concentrations of GO particles (0.12–0.5 % w/W). The systems underwent comprehensive analysis concerning steady-state and dynamic-state rheological behavior under diverse conditions. The findings reveal that the inclusion of GO augments both static and dynamic rheological properties, reaching an apex at an optimal concentration of 0.36 % w/W. GO functions as a network builder within the STF, interacting with the existing particle network to create a more robust and interconnected structure. These enhanced properties underscore the potential of the synthesized STF for applications requiring impact resistance.