Search results

The purpose of this paper is to investigate the effect of thermal treatment at low partial pressure of oxygen on electrochemical corrosion resistance of Ti‐47Al‐2Cr (at %) intermetallic, known as γ‐TiAl alloy.

The surfaces of the samples were modified by thermal treatment at different temperatures in N₂ gas flow for an hour. Characterization of the modified surface layers was carried out by microscopic examinations, hardness and roughness tests, and X‐ray diffraction analyses. Potentiodynamic polarization was used to evaluate the corrosion performance of γ‐TiAl in Ringer's solution.

The results indicated that the alloy treated at 950 °C had the optimum corrosion resistance, which can be attributed to the formation of an oxide layer by the surface thermal treatment and increase of the passive layer thickness.

Low corrosion rate (CR), high pitting potential (Epit), and more noble corrosion potential (Ecorr) make it possible for γ‐TiAl to be considered as a candidate for biomedical applications.

The treatment described in the paper is a novel method for surface modification of this type of alloy and results showed that it was an effective treatment and that the corrosion resistance improved remarkably.

This paper aims to estimate the corrosion rate of the carbon steel in crude oil using the electrochemical noise (EN) analysis technique.

EN measurements and electrochemical impedance (EIS) spectroscopy were employed to study the corrosion behaviour of carbon steel in crude oil and the optimum conditions of the noise analysis for estimating corrosion rate of the carbon steel are discussed. The time series noise patterns were transformed into frequency domains by fast Fourier transformation, and then their power spectrum densities (PSDs) at a frequency were determined to be compared with the corrosion rate.

The PSDs of the potential and of the current varied with changing of rotation rate of electrode and immersion time. Square roots of the PSDs for the potential difference and for the currents were in positive and almost linear correlation with the corrosion rate obtained from EIS plots. In addition, the spectral noise was negatively and linearly correlated with the corrosion rate. The relationship between the corrosion rate and the spectral noise resistance was better at lower frequencies.

It is suggested that this research is carried out for crude oils with other physical and chemical characteristics.

The PSD value at 3 mHz from the noise of the current and the spectral noise resistance at the same frequency are the optimum conditions for estimating corrosion rate in this research.

This paper arguably fills a gap in the current understanding of the interactions between corrosive species commonly found in crude feedstocks and process streams.

The purpose of this paper was to investigate the anti-corrosion behavior of polypyrrole (PPy) films in different states and presence of alumina nanoparticles synthesized by galvanostatic electropolymerization on stainless steel (SS) electrodes in an artificial seawater solution using potentiodynamic polarization and electrochemical impedance spectroscopy (EIS).

The electrochemical measurements were used to examine the effects of PPy and its nanocomposite on the corrosion behavior of SS type 316L in artificial seawater. A standard electrochemical cell with three electrodes was used for the measurements. The electrochemical response of the coated electrodes in the doped and the undoped state was compared with that of a bare electrode. Corrosion rate information was obtained by the Tafel extrapolation method, where the intersection point of a cathodic and an anodic polarization curve provides both the corrosion potential and the corrosion current. EIS measurements confirmed the potentiodynamic and open circuit potential (OCP) results. The microstructure of the obtained films was investigated by scanning electron microscopy.

The results showed that the coated polymer films shifted the electrode potential toward more positive potentials, but this shift did not lead to passivation. However, a notable synergy was observed between PPy undoped film, oxygen reduction and iron dissolution. The potential of the SS remained in the active dissolution region, and it was not possible to produce a passive oxide layer in this region. PPy separates the metal dissolution process from the oxygen reduction process. This would prevent the local pH increase at the metal surface and subsequent delamination. The polarization curves, EOCP and impedance measurements showed that PPy undoped/Al₂O₃ layers show promise as good candidates for the corrosion protection of reactive metals.

This paper presents that electrodes coated with undoped PPy synthesized in the presence of dodecyl sulfate anions and Al₂O₃ nanoparticles offered a noticeable enhancement of protection against corrosion processes.

The purpose of this paper is to investigate the effects of inorganic inhibitors on the corrosion rate of aluminum alloy using the electrochemical noise (EN) analysis and electrochemical impedance spectroscopy (EIS) techniques.

EN and EIS measurements were employed to study the corrosion behavior of aluminum alloy in Na₂SO₄(0.50 M)/NaCl(0.20 M) solution in presence of inorganic inhibitors. The time‐series noise patterns were transformed into the frequency domain using fast Fourier transformation, and then their power spectrum densities (PSDs) at specified frequencies were determined and compared with the EIS and polarization results.

The EN, EIS and polarization results were in agreement. The inhibitive effect of the anions decreased in the order: CrO₄²⁻>Cr₂O₇²⁻>NO₃⁻>WO₄²⁻>MoO₄²⁻>NO₂⁻. The results showed that the slope of PSD of the current (i.e. the “roll off”) was less where inhibition efficiency was greater. The spectral noise impedance and the modulus of the impedance recorded using impedance spectroscopy showed good agreement.

This paper provides useful information relative to corrosion inhibition efficiency of the sodium and potassium salts using EN analysis technique.

This paper aims to investigate the galvanic corrosion of titanium/L 316 stainless steel, by electrochemical noise (EN), electrochemical impedance spectroscopy (EIS), and anode/cathode area ratio effect on the galvanic behavior of the couple.

The EN measurement was employed to examine effects of anode to cathode area ratio on the galvanic corrosion behavior between stainless steel L 316 and titanium in artificial seawater. Current noise and potential noise were monitored simultaneously using a three‐electrode configuration under open‐circuit condition. The noise resistance was evaluated as the ratio of the standard deviation of the potential to that of the current noise after removing the DC component. The time‐series noise patterns were transformed into frequency domain by fast Fourier transformation and then their power spectrum densities (PSDs) at specified frequency were determined and compared with the EIS and polarization results.

The EN, EIS and polarization results were in agreement. Galvanic corrosion density increase and galvanic potential moved slowly to negative direction with decrease in anode/cathode area ratio. The results showed that the slope of PSD of the current (i.e the “roll off”) was rising slowly where the anode/cathode area ratio was declined. The relationship between polarization resistance (Rp) and noise resistance (Rn) was investigated. Rt was determined by EIS for samples, and its value compared with Rp and Rn. The result indicates that galvanic corrosion has an inversely relation with anode/cathode area ratio that exposed to aggressive environment.

This paper presents the application of noise analysis to demonstrate galvanic corrosion and the effect of area ratio anode/cathode on current density and galvanic potential.

Ordinary differential equations (ODEs) are widely used in the engineering curriculum. They model a spectrum of interesting physical problems that arise in engineering disciplines. Studies of different types of ODEs are determined by engineering applications. Various techniques are used to solve practical differential equations problems. This paper aims to present a computational tool or a computer-assisted technique aimed at tackling ODEs. This method is usually not taught and/or not accessible to undergraduate students. The aim of this strategy is to help the readers to develop an effective and relatively novel problem-solving skill. Because of the drudgery of hand computations involved, the method requires the need to use computers packages. In this work, the successive differentiation method (SDM) for solving linear and nonlinear and homogeneous or non-homogeneous ODEs is presented. The algorithm uses the successive differentiation of any given ODE to determine the values of the function’s derivatives at a single point, mostly x = 0. The obtained values are used to construct the Taylor series of the solution of the examined ODE. The algorithm does not require any new assumption, hence handles the problem in a direct manner. The power of the method is emphasized by testing a variety of models with distinct orders, with constant and variable coefficients. Most of the symbolic and numerical computations can be carried out using computer algebra systems.

This study presents a computational tool or a computer-assisted technique aimed at tackling ODEs. This method is usually not taught and/or not accessible to undergraduate students. The aim of this strategy is to help the readers to develop an effective and relatively novel problem-solving skill. Because of the drudgery of hand computations involved, the method requires the need to use computers packages.

This method is applied to a variety of well-known equations, such as the Bernoulli equation, the Riccati equation, the Abel equation and the second-order Euler equation, some with constant and variable coefficients. SDM handles linear and nonlinear and homogeneous or nonhomogeneous ODEs in a direct manner without any need to restrictive conditions. The method works effectively to the Volterra integral equations, as will be discussed in a coming work.

The method can be extended to a wide range of engineering problems that are modeled by differential equations. The method is simple and novel and highly accurate.

This paper aims to introduce a novel algorithm to solve initial/boundary value problems of high-order ordinary differential equations (ODEs) and high-order system of ordinary differential equations (SODEs).

The proposed method is based on Hermite polynomials and extreme learning machine (ELM) algorithm. The Hermite polynomials are chosen as basis function of hidden neurons. The approximate solution and its derivatives are expressed by utilizing Hermite network. The model function is designed to automatically meet the initial or boundary conditions. The network parameters are obtained by solving a system of linear equations using the ELM algorithm.

To demonstrate the effectiveness of the proposed method, a variety of differential equations are selected and their numerical solutions are obtained by utilizing the Hermite extreme learning machine (H-ELM) algorithm. Experiments on the common and random data sets indicate that the H-ELM model achieves much higher accuracy, lower complexity but stronger generalization ability than existed methods. The proposed H-ELM algorithm could be a good tool to solve higher order linear ODEs and higher order linear SODEs.

The H-ELM algorithm is developed for solving higher order linear ODEs and higher order linear SODEs; this method has higher numerical accuracy and stronger superiority compared with other existing methods.

The instrumental-normative divide that has historically characterized approaches to societal sustainability has also resulted in a rift between underlying mental models and methods destined to address the issue. This separation makes our understanding and tackling of the present global ecological problems only limited and ineffective. The present work aims to draw on theoretical background to develop a conceptual framework for transitioning to integrated corporate sustainability.

Drawing inspiration from Luhmann’s (1995) theory of social systems, we consider the instrumental (hard) and normative (soft) methods (Jackson 2019) for corporate sustainability as “conceptual systems” that derive much of traditional social systems’ attributes. These systems are autopoietic, complexity-reducing and functionally differentiated. Following Luhmann’s philosophical grounding, we suggest that integrating the two systems of hard and soft methods boils down to constraining both systems’ internal complexity by imposing limitations on their operational structures. This translates into a decodification–recodification process whereby new methods emerge as a combination of initially disconnected structures.

The proposed conceptual integration framework is applied to the case of the Sustainability Balanced Scorecard (SBSC) which has been recently subject to inconclusive controversy. Our work demonstrates that redesigning the SBSC’s architecture following the presented framework leads to embracing complexity, tensions and conflict all the while offering a systematic approach for properly identifying and quantifying cause–effect relationships. Moreover, the proposed framework scores high in Complexity and Systemicity measures, making it both durable and practically useful. More generally, this work drives home the point that an integrated approach to sustainability management is not only important but also feasible and theoretically durable.

Theoretically, the present work underscores the contribution of systems theory, and particularly the Luhmannian perspective, to transcending some of the most salient “divides” in approaches to societal sustainability. The decodification–recodification process not only enables integrating two distinct conceptual systems, but it also transforms the divide into an opportunity to gain a fresher perspective on one of the most challenging issues of our time. This process may demand, however, some adjustments as we move across various function systems, which requires solid knowledge and understanding of the underlying “codes” that define the systems subject to integration.

This work implies that integration of varied and sometimes outwardly opposed function systems can and must be carried out to achieve larger societal impact. With respect to the illustrated case, the emerging dynamic SBSC offers a viable strategic planning platform whereby managers and stakeholders can concurrently define, forecast and adjust the societal strategy that maximizes triple bottom-line indicators and sustainable development impact.

Providing decision and policymakers with integrated sustainability management approaches and instruments will have a direct benefit on enhancing the way systems, and large corporations in particular, treat and deal with nature and human beings.

We propose that proper integration of multiple function systems, employing integrative, unbiased and structured methodologies, can be decisive in challenging current practices in sustainability management and in providing informed guidance for making the high-stake decisions needed in the transition towards sustainable development of business and society.

This paper aims to minimize the total carbon emissions and costs and also maximize the total social benefits.

The present study develops a mathematical model for a closed-loop supply chain network of perishable products so that considers the vital aspects of sustainability across the life cycle of the supply chain network. To evaluate carbon emissions, two different regulating policies are studied.

According to the obtained results, increasing the lifetime of the perishable products improves the incorporated objective function (IOF) in both the carbon cap-and-trade model and the model with a strict cap on carbon emission while the solving time increases in both models. Moreover, the computational efficiency of the carbon cap-and-trade model is higher than that of the model with a strict cap, but its value of the IOF is worse. Results indicate that efficient policies for carbon management will support planners to achieve sustainability in a cost-effectively manner.

This research proposes a mathematical model for the sustainable closed-loop supply chain of perishable products that applies the significant aspects of sustainability across the life cycle of the supply chain network. Regional economic value, regional development, unemployment rate and the number of job opportunities created in the regions are considered as the social dimension.

One of the most important issues in supply chain (SC) management is the identification and management of the risk involved in it. The purpose of this paper is to propose a comprehensive model of supply chain risk management (SCRM) in the product life cycle (PLC) and the operational process cycle (OPC). To decrease the risks in a fuzzy environment, the model considers the organizational performance factors (OPF) and the risk operational practices (ROP).

Fuzzy analytic hierarchy process is used to determine the weights of the relationships between the PLC, OPC and OPF in the hierarchical structure of the decision problem. In addition, the fuzzy technique for order preference by similarity to ideal solution is employed to recognize the priority of ROPs in dealing with the performance factors. The integrated framework is evaluated using the case study of an automotive company in Iran.

The results demonstrated that the proposed model can be used to formulate an appropriate method for prioritizing defined alternatives to decrease risk and improve the organizational performance in SCRM under fuzzy conditions.

A major limitation of the study is that a few of the selected criteria for risk assessment are focused only on economic factors. Another limitation of the current study is related to the PLC, OPC and OPF being based on the work of Xia and Chen (2011).

The current study identified the more important stage in the PLC. More significant process in each stage of the PLC and weightier risk factors in each process of the OPC were determined. Some strategies for reducing risk in each stage of the PLC were presented. The best alternatives for reducing risks in SC were indicated.

It is worth mentioning that previous studies have not applied multiple criteria and alternatives to decrease the risks involved in the PLC and OPC parts of the SC under fuzzy conditions. However, it should be stated that some academics have used these techniques separately, in other specialized areas of the SC.