Time-dependent Resistance Research Articles

Origin of the time-dependent corrosion behavior of biodegradable Mg-Si-Zn alloys in simulated body fluid

The corrosion behavior of Mg‐0.6%Si‐2%Zn alloys in simulated body fluid was studied to understand the time-dependent processes and interfacial phenomena. The alloy's microstructure includes Mg-rich dendrites within eutectic microconstituent. Electrochemical responses showed minimal dependence on dendritic-spacing. Initial immersion (12.2-hour) formed a protective layer, indicated by potential elevation, polarization resistance escalation, and changes in Nyquist and Bode plots. However, between 12.2- and 168.4-hour, the protective layer integrity decreased, with observable corrosion. The corrosion mechanism involved protective layer formation followed by cracking induced by Pilling-Bedworth ratio and high H2 evolution kinetics. This time-dependent corrosion resistance resembles both corrosion-resistant and corrosion-sensitive Mg alloys, showcasing challenges in accurate assessment.

Stable positive unipolar resistive switching in chemical solution-deposited nanocrystalline spinel ferrite ZnFe2O4

The chemical solution-deposited zinc ferrite (ZFO; ZnFe2O4) RRAM devices on Pt/Ti/SiO2/Si substrate are being reported. Fabricated devices show the positive as well as negative unipolar switching memory properties. Thickness of ZFO thin films in Au/ZFO/Pt structure was varied to explore the resistive switching behavior. It is reported that forming voltage and resistance of the device increase by increasing the number of ZFO layers. Our results reveal that ZFO thin film deposited by eight times spin coating with a thickness of eight layers illustrates stable resistive switching with the most steady Set (2[Formula: see text]V) and Reset voltages (0.5[Formula: see text]V) as compared to the devices with two, four, and six layers. It also demonstrates the enhanced endurance of greater than 300 switching cycles and stable time-dependent resistance greater than 104[Formula: see text]s. The current transport mechanism is Ohmic at low-resistance state, while it leads to Schottky emission at high-resistance state. The possible switching mechanism is also discussed for the possible application of ZFO-based memory for nonvolatile RRAM devices.

Simplified solution for large-strain consolidation considering the time-dependent well resistance

In this study, a simplified solution of the large-strain consolidation theory, which considers the time-dependent well resistance, has been presented. This solution is suitable for consolidation issues involving the influence of either the smear zone or the soil column. To confirm the proposed solution's accuracy, it was compared to fully nonlinear consolidation results calculated using the finite element method. Parametric analysis was conducted to examine the impact of the time-dependent well resistance in combination with the soil thickness, the ratio of the compression index to the radial and vertical permeability indices, and the initial void ratio at the soil surface. Finally, the proposed solution’s applicability was confirmed through a comparison of calculated results based on two case studies with both field measurements and numerical simulations.

The Homeodomain-Leucine Zipper Subfamily I Contributes to Leaf Age- and Time-Dependent Resistance to Pathogens in Arabidopsis thaliana.

In Arabidopsis thaliana (Arabidopsis), nonhost resistance (NHR) is influenced by both leaf age and the moment of inoculation. While the circadian clock and photoperiod have been linked to the time-dependent regulation of NHR in Arabidopsis, the mechanism underlying leaf age-dependent NHR remains unclear. In this study, we investigated leaf age-dependent NHR to Pyricularia oryzae in Arabidopsis. Our findings revealed that this NHR type is regulated by both miR156-dependent and miR156-independent pathways. To identify the key players, we utilized rice-FOX Arabidopsis lines and identified the rice HD-Zip I OsHOX6 gene. Notably, OsHOX6 expression confers robust NHR to P. oryzae and Colletotrichum nymphaeae in Arabidopsis, with its effect being contingent upon leaf age. Moreover, we explored the role of AtHB7 and AtHB12, the Arabidopsis closest homologues of OsHOX6, by studying mutants and overexpressors in Arabidopsis-C. higginsianum interaction. AtHB7 and AtHB12 were found to contribute to both penetration resistance and post-penetration resistance to C. higginsianum in a leaf age- and time-dependent manner. These findings highlight the involvement of HD-Zip I AtHB7 and AtHB12, well-known regulators of development and abiotic stress responses, in biotic stress responses in Arabidopsis.

Human Metal ESD: Design of a Full-Wave Model and an Improved Compact Generator

A full-size, full-wave human body model has been designed. Compared with a real human-metal electrostatic discharge (ESD), similar fields and currents are obtained from the numerical model. A resistive surface sheet is used in microwave studio to control the currents on the air-filled body. Its performance is verified by comparing it to the currents and fields from the real human ESD. A subcircuit models the time-dependent resistance of the spark using the well-known Rompe–Weizel spark resistance model. Real human metal ESD does not reveal the double hump shape as shown in the IEC standard. To create a generator that reproduces the real human metal ESD current waveform, a compact ESD generator was designed, which is based on matching the impedance of real human metal mode ESD with the impedance of the compact ESD generator. Furthermore, a circuit-based simulator is presented. It is based on a PCB implementation of the equivalent circuit of the human metal ESD.

Time-Dependent Seismic Reliability of Coastal Bridge Piers Subjected to Nonuniform Corrosion.

Coastal bridge piers suffer random performance deterioration owing to the presence of complex nonuniform corrosion characteristics and material uncertainties. Some of these piers will also be threatened by random earthquakes during a long-term service period, and therefore, structural safety needs to be probabilistically assessed by the seismic reliability method. To deal with this problem, we present a method to calculate the time-dependent reliability of the coastal bridge pier, comprehensively considering the randomness of a seismic event, nonuniform corrosion, and material uncertainty. First, the time-dependent M-N interaction diagrams are established by using the Monte Carlo simulation method. On the basis of the interaction diagrams, the moment resistance reduction function and time-dependent moment resistance distribution are determined. Subsequently, the moment demand under the seismic load is determined using the Poisson model and the response acceleration spectrum. Then, the formulas to calculate the time-dependent reliability of a nonuniform corroded pier are derived on the basis of the theorem of total probability. The proposed method is illustrated with a case study of a coastal bridge pier. It was found that the increase in corrosion damage would obviously increase time-dependent reliability. Furthermore, the increase in submerged zone height delayed the year when the failure section shifts from the pier bottom to the bottom of the splash and tidal zone, and it reduces the failure probability of the coastal pier. The research results presented herein show that the nonuniform corrosion manifestations influence the failure mode-related time-dependent seismic reliability of the coastal bridge pier.

Probing the stability of perovskite solar cell under working condition through an ultra-thin silver electrode: Beyond the halide ion diffusion and metal diffusion

Perovskite solar cells (PSCs) with an excellent optoelectronic performance have intrigued mushrooming research interests, and the undesirable intrinsic stability of halide perovskite materials still remains a severe constraint for their practical application. Fortunately, the ambiguous and complicated incentives for the degradation process of PSCs under working condition can be directly reflected on the corrosion of silver electrode by halogens. Here, a new perspective for evaluating the long-term stability of PSCs is presented by the time-dependent transverse resistance of the ultrathin silver electrode under different working conditions. Being anode or cathode, the stability of ultra-thin silver layer has been systematically investigated through adjusting the external operating conditions of devices, i.e. light illumination and bias voltage. Experimental results indicate that the gradual resistance increases of silver film can be attributed to the oxidation of I− existing on the top surface of perovskite layer by non-equilibrium holes generated from light illumination or electrical injection for producing corrosive I2 gas, which will diffuse through the carrier transporting layer and attack the thin silver layer. The interaction probability of I− and non-equilibrium holes at the interface plays a critical role on the generation of I2 gas and resistance variation of the top thin silver electrode. The stability study of electrode indicator will shed light on the ambiguous degradation mechanisms of PSC under working condition, paving a path for conquering the fatal problems of the practical application.

Comparison of time-dependent resistance isometric exercise and active range of motion exercise in alleviating the sensitization of postoperative axial pain after cervical laminoplasty

BackgroundPostoperative axial pain (PAP) is a significant complication after cervical laminoplasty. ObjectiveTo investigate pain sensitization in PAP patients and effects of time-dependent resistance isometric exercise compared to active range-of-motion exercise on PAP. Study designRetrospective cohort analysis. Methods211 patients undergoing postoperative 12-week exercises were evaluated for pressure pain threshold (PPT), temporal summation (TS) and both cross-sectional area and fatty infiltration of paraspinal muscles preoperatively and 3 months postoperatively. There patients underwent Numeric rating pain scale (NRS) and neck disability index (NDI) 3 and 6 months postoperatively. ResultsAt postoperative 3-month assessments, fewer patients undergoing isometric exercise showed PAP compared to range-of-motion exercise group (14/98 vs. 34/113; P = 0.006), and pain-related assessments in the former were lower than the latter (NRS at rest: 0.3 ± 0.8 vs. 0.7 ± 1.4, P = 0.014; NRS with movements: 0.4 ± 1.0 vs. 1.0 ± 1.7, P = 0.015; NDI: 2.4 ± 6.3 vs. 6.7 ± 10.9, P = 0.002). Postoperative cross-sectional area was smaller in isometric exercise group (603.5 ± 190.2) than in range-of-motion exercise group (678.7 ± 215.5) (P = 0.033), and the former showed higher local-area PPT and lower TS than the latter (PPT: 3.9 ± 1.8 vs. 3.1 ± 1.6, P = 0.002; TS: 1.8 ± 0.9 vs. 2.2 ± 1.0, P = 0.003). PAP patients showed lower local-area PPT and greater TS than those without PAP in both isometric (PPT: 2.8 ± 0.7 vs. 4.0 ± 1.9, P = 0.019; TS: 2.4 ± 0.6 vs. 1.7 ± 0.9, P = 0.011) and range-of-motion (PPT: 2.2 ± 0.9 vs. 3.6 ± 1.7, P < 0.001; TS: 2.8 ± 0.8 vs. 1.9 ± 0.9, P < 0.001) exercise groups. ConclusionsBoth peripheral and central sensitization are involved in PAP. Time-dependent isometric exercise has more positive effects on PAP than range-of-motion exercise because of its advantages in improving pain sensitization.

Corrosion behaviour of biomedical Ti under simulated inflammation: Exploring the relevance of grain refinement and crystallographic texture

This study provides an insight into the separate and combined effects of nanostructure and crystallographic texture on time-dependent Ti corrosion resistance under simulated inflammatory conditions. In order to achieve this objective, the following Ti products were fabricated by differential large plastic deformation methods: (i) nano Ti materials with virtually the same grain size but distinct crystallographic textures, and (ii) Ti materials with different microstructures but similar crystallographic textures. Overall, electrochemical and XPS studies revealed that the development of a basal texture component provides the most advantageous corrosion properties in terms of prolonged immersion in a simulated inflammatory environment.

Experimental Investigation on Corrosion Behavior of X80 Pipeline Steel under Carbon Dioxide Aqueous Conditions.

A combined steady-state and transient approach is employed to investigate the corrosion behavior of X80 pipeline steel in carbon dioxide-saturated brines. Continuous bubbling of carbon dioxide into a test vessel with 1 liter capacity is performed to simulate the flowing condition. The measurement of time-dependent open-circuit potential, polarization resistance, and electrochemical impedance spectroscopy (EIS) is conducted to interpret the evolution of dissolution processes at the corroding interface. Three distinguishing stages are observed at a temperature of 60 °C during a whole exposure of 144 h. Analyses mainly based on the consecutive mechanism show that after the first stage of the active-adsorption state, the anodic reaction is significantly retarded by the accumulation of (FeOH)ads on the iron surface, causing a sharp increase in the polarization resistance and the open-circuit potential, as well as the disappearance of the inductive loop in EIS. At the third stage, the formation of the corrosion product layer similarly reduces both the anodic and cathodic reactions, which arouses a linear increase in the polarization resistance with time and a capacitive loop in EIS but changes the open-circuit potential slightly. An increase in salinity in this study reduces the polarization resistance and enhances iron dissolution by promoting the formation and relaxation of (FeOH)ads; however, it brings little change to the developing time of the three stages obviously. At a low temperature of 20 °C, a protective product layer is not observed in carbon dioxide-saturated brine, and the dissolution of iron is mainly under activation control during the whole exposure. A notable enlarged polarization resistance and different interfacial processes are observed in an alkaline solution compared with those in acidic environments, which is deduced to be resulted from an impedance in the relaxation of (FeOH)ads by increasing pH. The observations in this study support well that the iron dissolution reaction at the initial stage exposed in carbon dioxide aqueous environments is dominant by water adsorption on the iron surface, and further investigation should be performed on the role that carbon dioxide plays in the evolution of corrosion products and the formation of a protective film on the steel surface by taking into account local water chemistry.

Assessment of time-dependent structural resistance of RC bridges in Barak Valley, Assam, India

Reinforced concrete (RC) bridges deteriorate due to strength loss induced by aging of the structure, extreme weathering conditions and unplanned increased service loads. These load variations and aging factors can compromise structural reliability and reduce the service life for continuous satisfactory operation of service bridges in the future. Accurate prediction of bridge functionality relies on reasonable models of bridge strength and applied loads, and time-dependent reliability assessments can be used to gain a reliable understanding of bridge conditions so that appropriate solutions can be found. In this work, the reliability of bridges under harsh conditions was studied using time-variant and time-invariant reliability models in which both load and resistance are considered as time-dependent parameters. Combinations of the condition rating and time-dependent load were used to gain accurate insights into the degradation of the structural resistance of existing bridges. The results of this study showed the significant impact of aging and the influence of traffic loads on the service life of both national highway bridges and rural road service bridges. These observations could be used to devise appropriate planning strategies and plan rational decisions to ensure bridge safety in the future.

Study on the Time‐dependent Reliability of Corroded Reinforced Concrete Bridge Structures due to Ship Impact

The cumulative damage caused by chloride ion erosion to coastal bridge structures reduces the ship impact resistance of channel bridge structures and leads to changes in reliability of bridge structures on ship impact. It is of great theoretical and practical significance to study the performance degradation change law of corroded bridge structures and to evaluate the ship impact time‐dependent reliability of in‐service corrosion‐damaged bridge structures. Based on the durability decay model of reinforced concrete structures in a chloride ion erosion environment, the time‐dependent resistance analysis of bridge structures is carried out considering the reduction of yield strength of longitudinal reinforcement and hoop reinforcement in pile sections and the decay of compressive strength of protective layer concrete. Based on the study of the probabilistic model and parameters of random variables affecting the time‐dependent reliability of ship‐bridge collision, the typical damage modes of bridge structures under ship impact are analyzed, the time‐dependent reliability analysis model of bridge structures under ship impact is established based on the structural damage criterion, the ship‐bridge crash limit state functional function is given, and the time‐dependent reliability analysis of ship‐bridge collision is carried out based on the response surface method.

Li-ion Battery Aging with Hybrid Physics-Informed Neural Networks and Fleet-wide Data

Lithium-ion batteries are commonly used to power electric unmanned aircraft vehicles (UAVs).Therefore, the ability to model both the state of charge as well as battery health is very important for reliable and affordable operation of UAV fleets.Even though models based on first principles are accurate and trustworthy, the complex electro-chemistry that governs battery discharge and aging makes it hard to build and use such models for in-time monitoring of battery conditions.Moreover, the careful tuning or estimation of high-fidelity model parameters hampers the straightforward deployment in the field.Alternatively, reduced order models have the advantage of capturing the overall behavior of battery discharge.&#x0D; Reduced-order principle-based models are built by carefully simplifying the physics/chemistry such that computational cost is dramatically reduced while the overall behavior of the system is still captured.These simplifications also lead to a number of parameters to be estimated based on data as well as residual discrepancy (model-form uncertainty).This approach can lead to a number of parameters to be estimated based on data as well as residual model-form uncertainty; a property shared with machine learning models. The latter are solely built on the basis of data, and can still capture unexpected nonlinearities.The drawback is that traditional machine learning tends to require large number of data points hard to retrieve in many scientific and engineering fields like, for example, the field of battery discharge and degradation prediction.&#x0D; In this paper, we will present a hybrid modeling approach for tracking and forecasting battery aging based on ``as-used'' conditions.Our approach directly implements a reduced-order model based on Nerst and Butler-Volmer equations within a deep neural network framework.While most of the input-output relationship is captured by reduced-order models, the data-driven kernels reduce the gap between predictions and observations.The hybrid model estimates the overall battery discharge, and a multilayer perceptron models the battery internal voltage.Battery aging is characterized by time-dependent internal resistance and the amount of available Li-ions.We address the difficult issue of building and updating the aging model by reducing the need for reference discharge cycles.This is beneficial to operators, since it reduces the need of taking the batteries out of commission.We compensate for lack of reference discharge cycles by using a probabilistic model that leverages previously available fleet-wide information.&#x0D; We validate our approach using data publicly available through the NASA Prognostics Center of Excellence website.Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.Moreover, the model can help optimizing battery operation by offering long-term forecast of battery capacity.

Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis

Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs). The ability to model and forecast remaining useful life of these batteries enables UAV reliability assurance. Building principled accurate models is challenging due to the complex electrochemistry that governs battery operation. Alternatively, reduced order models have the advantage of capturing the overall behavior of battery discharge, although they suffer from simplifications and residual discrepancy. This paper presents a hybrid modeling approach that directly implements physics within deep neural networks. While most of the input–output relationship is captured by reduced-order models, data-driven kernels reduce the gap between predictions and observations. A reduced-order model based on Nernst and Butler–Volmer equations represents the overall battery discharge, and a multilayer perceptron models the battery non-ideal voltage. Battery aging is characterized by time-dependent internal resistance and the amount of available Li-ions, which are modeled through an ensemble of variational Bayesian multilayer perceptrons. The approach is validated using data publicly available through the NASA Prognostics Center of Excellence website. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations. Moreover, the model can help optimizing battery operation by offering long-term forecast of battery capacity. • Physics-informed neural network implements physics into a deep learning framework. • Model capable of forecasting end-of-discharge while accounting for battery aging. • Aging prognostic uses information from a fleet of batteries via an ensemble model.

Hybridizing Neural Network with Trend-Adjusted Exponential Smoothing for Time-Dependent Resistance Forecast of Stabilized Fine Sands Under Rapid shearing

Hybridizing Neural Network with Trend-Adjusted Exponential Smoothing for Time-Dependent Resistance Forecast of Stabilized Fine Sands Under Rapid shearing

Multi-level phase-change memory with ultralow power consumption and resistance drift

By controlling the amorphous-to-crystalline relative volume, chalcogenide phase-change memory materials can provide multi-level data storage (MLS), which offers great potential for high-density storage-class memory and neuro-inspired computing. However, this type of MLS system suffers from high power consumption and a severe time-dependent resistance increase (“drift”) in the amorphous phase, which limits the number of attainable storage levels. Here, we report a new type of MLS system in yttrium-doped antimony telluride, utilizing reversible multi-level phase transitions between three states, i.e., amorphous, metastable cubic and stable hexagonal crystalline phases, with ultralow power consumption (0.6–4.3 pJ) and ultralow resistance drift for the lower two states (power-law exponent < 0.007). The metastable cubic phase is stabilized by yttrium, while the evident reversible cubic-to-hexagonal transition is attributed to the sequential and directional migration of Sb atoms. Finally, the decreased heat dissipation of the material and the increase in crystallinity contribute to the overall high performance. This study opens a new way to achieve advanced multi-level phase-change memory without the need for complicated manufacturing procedures or iterative programming operations.

Response modulation of silicon nanowires-based sensor to carbon number in petroleum vapor detection

To ensure high safety level in crude oil and its distillates storage tanks, petrochemical industry needs responsive and reliable hydrocarbon vapor sensing devices. We propose here a cost-effective petroleum vapor sensor that could be used effectively in oil tanks. The fabricated device is based on silicon nanowires (SiNWs) and has a good response to petroleum vapor concentration fluctuations. The chemiresistive sensitive device is a layer of SiNWs elaborated on a Cz-Si wafer with top planar Ag-Al electrical contacts. Petroleum vapors are obtained by heating crude oil. Detection measurements are performed at temperatures ranging from the ambient (18 °C) to 70 °C and for vapor concentrations varying between the Lower Explosion Limit (LEL) ~ 10000 ppmv and the Upper Explosion Limit (UEL) ~ 60000 ppmv.By measuring the time-dependent electrical resistance of the device at a fixed temperature, multiple cycles of response-recovery are obtained. As a main finding, we report on how the response of SiNWs to carbon number (nC) of petroleum vapor could be modulated by varying the device temperature.Therefore, at room temperature, when the petroleum vapor is rich of light hydrocarbon molecules (nC ≤ 7), adsorption–desorption cycles are quasi-reversible. However, at higher temperature, when vapors substantially contain heavier hydrocarbon molecules (nC > 7), we obtain a time dependent pronounced increasing drift in the chemiresistance of the device. Interestingly we found that the carbon number of molecules in the petroleum vapor plays a key-role in the response of the sensor.

The decreasing of the influence of parasitic inductance of tested object on the accuracy of its electrical capacitance measurement

This paper gives a description of measurement technique which can be used in practice of carrying out estimation of electrical capacitance of tested object with substantial stray inductance. Electrical capacitance is determined as a ratio of mean value of discharge current to the mean value of time derivative, taken from voltage on unknown capacitance. The decreasing of deleterious impact of stray inductance on accuracy of measurements is achieved by proper selection of the duration of analyzed signals. In proposed technique the duration is limited by instants of time that correspond to the maximum value of discharge current and to the termination of transient. The accuracy of described method for electrical capacitance estimation is affected by noisy components of obtained oscillograms. This deleterious impact can be alleviated by smoothing of time dependence by applying of least square method. Another reason for lost of accuracy is associated with possible influence of skin-effect in conductive elements of discharge circuit, which can cause time dependence of resistance and inner inductance of conductive parts of tested object and discharge circuit. Described technique, however, is based on taking into consideration independent on time parameters of equivalent lamped discharge circuit. Nevertheless, the example of practical implementation has shown that described approach allows to partially mitigate the influence of stray inductance on carried out measurements of electrical capacitance, as the value of relative error turned out to be equal to 2.04%

Tailoring bolometric properties of a TiOx/Ti/TiOx tri-layer film for integrated optical gas sensors.

In this paper, we systematically investigated tailoring bolometric properties of a proposed heat-sensitive TiOx/Ti/TiOx tri-layer film for a waveguide-based bolometer, which can play a significant role as an on-chip detector operating in the mid-infrared wavelength range for the integrated optical gas sensors on Ge-on-insulator (Ge-OI) platform. As a proof-of-concept, bolometric test devices with a TiOx single-layer and TiOx/Ti/TiOx tri-layer films were fabricated by varying the layer thickness and thermal treatment condition. Comprehensive characterization was examined by the scanning transmission electron microscopy (STEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) analyses in the prepared films to fully understand the microstructure and interfacial properties and the effects of thermal treatment. Quantitative measurements of the temperature- and time-dependent resistance variations were conducted to deduce the minimum detectable change in temperature (ΔTmin) of the prepared films. Furthermore, based on these experimentally obtained results, limit-of-detection (LoD) for the carbon dioxide gas sensing was estimated to demonstrate the feasibility of the proposed waveguide-based bolometer with the TiOx/Ti/TiOx tri-layer film as an on-chip detector on the Ge-OI platform. It was found that the LoD can reach ∼3.25 ppm and/or even lower with the ΔTmin of 11.64 mK in the device with the TiOx/Ti/TiOx (47/6/47 nm) tri-layer film vacuum-annealed at 400 °C for 15 min, which shows great enhancement of ∼7.7 times lower value compared to the best case of TiOx single-layer films. Our theoretical and experimental demonstration for tailoring bolometric properties of a TiOx/Ti/TiOx tri-layer film provides fairly useful insight on how to improve LoD in the integrated optical gas sensor with the bolometer as an on-chip detector.

Probabilistic sustainability design of structural concrete components under climate change

A probabilistic sustainability design method for quantifying the benefits from sustainable structural strategies under climate change is put forward in this study. To help curb the vicious circle of increasing structural and environmental degradation, the sustainable probability is defined as a conditional probability, and the interaction between structural reliability and environmental impacts is quantified. Global warming potential (GWP) is adopted as the key indicator for environmental impacts. By analyzing the trends of climate change, the GWP limit is set to match the prediction of structural resistance degradation. A new environmental impact allocation rule based on time-dependent resistance is put forward to characterize the environmental benefits of the reuse strategy. With help of the durability life prediction method for reusable components and the stochastic model for time-dependent resistance, the calculation method for sustainable probability is established, catering for both reusable and non-reusable structural components. With the Monte Carlo simulation, the proposed sustainability design process is implemented in a numerical example. Results show that the reusable structural concrete component design can simultaneously satisfy the current and future safety and environmental requirements, meeting the demand for sustainable development.