Search results

The purpose of this paper was to study the corrosion control of B10 copper-nickel alloy using the LiOH-N₂H₄ compound inhibitors and to evaluate the feasibility of replacing the original inhibitors (NaNO₂-Na₂MoO₄) with the new ones (LiOH-N₂H₄) for the chilled water system in a nuclear unit.

The corrosion resistance performance of B10 copper-nickel alloy was evaluated during the whole replacement process of inhibiters using electrochemical tests and surface analysis techniques.

The results indicated that the corrosion of B10 copper-nickel alloy could be prevented effectively using LiOH to increase the pH value of solution higher than 10.0 and using N₂H₄ to consume dissolved oxygen. During the replacement process of inhibitors from NaNO₂-Na₂MoO₄ to LiOH-N₂H₄, the corrosion resistance performance of B10 copper-nickel alloy had not decreased greatly. The new LiOH-N₂H₄ inhibitor, which could enhance the compactness of rust, was able to reduce the corrosion rate of rusted B10 metal.

It is feasible and operable to replace the NaNO₂-Na₂MoO₄ inhibitors with the LiOH-N₂H₄ inhibitors for the corrosion prevention of B10 copper-nickel alloy. The research results can provide guidelines for the inhibitor selection of chilled water system in a nuclear unit.

For mitigating biocorrosion induced by sulfate-reducing bacteria (SRB) in seawater, the zwitterionic molecule layer (ZML) of poly (sulfobetaine methacrylate) is grafted onto B10 surface by chemical vapor deposition and surface-initiated atom transfer radical polymerization.

Energy-dispersive spectroscopy-attenuated total reflectance Fourier transform infrared spectroscopy and static contact angle measurements are used to characterize the as-formed layer.

After surface modification, B10 can significantly reduce SRB adhesion, demonstrating the good antifouling property. Further, the biocorrosion inhibition is investigated by potentiodynamic polarization and electrochemical impedance spectroscopy, indicating that ZML exhibits high resistance to biocorrosion with inhibition efficiency of approximately 90 per cent.

ZML performs a dual feature, i.e. antifouling film and corrosion inhibitor, for the biocorrosion inhibition.

The purpose of this paper was to investigate the lubricity of palm biodiesel (PB)–diesel fuel with plastic pyrolysis oil (PPO) and waste cooking biodiesel (WCB).

Three quaternary fuels were prepared by mechanical stirring. B10 (10% PB in diesel) fuel was blended with 5%, 10% and 15% of both PPO and WCB. The results were compared to B30 (30% PB in diesel) and B10. The lubricity of fuel samples was determined using high-frequency reciprocating rig in accordance with ASTM D6079. The tribological behavior of all fuels was assessed by using scanning electron microscopy on worn steel plates to determine wear scar diameter (WSD) and surface morphology. The reported WSD is the average of the major and minor axis of the wear scar.

The addition of PPO and WCB to B10 had improved its lubricity while lowering wear and friction coefficients. Among the quaternary fuels, B40 showed the greatest reduction in coefficient of friction and WSD, with 7.63% and 44.5%, respectively, when compared to B10. When compared to B30a, the quaternary fuel mixes (B40, B30b and B20) exhibited significant reduction in WSD by 49.66%, 42.84% and 40.24%, respectively. Among the quaternary fuels, B40 exhibited the best overall lubricating performance, which was supported by surface morphology analysis. The evaluation of B40 indicated a reduced adhesive wear and tribo-oxidation, as well as a smoother metal surface, as compared to B20 and B30b.

Incorporation of PPO and WCB in PB–diesel blend as a quaternary fuel blend in diesel engines has not been reported. Only a few researchers looked into the impact of PPO and WCB on the lubricity of the fuel.

Access to daily store level scanner data has been increasingly easier in recent years in Japan and time series analysis based on a sales response model is becoming realistic. Introduces a new method of combining time series analysis and regression analysis on the price promotion effect, which enables simultaneous decomposition of store level scanner sales into trend (including seasonality), day‐of‐the‐week effect and explanatory variable effect due to price promotion. The method was applied to daily store level scanner sales of milk, showing evidence of the existence of day‐of‐the‐week effect. Further, a method of incorporating several kinds of price‐cut variables in regression analysis and the analyzed results were presented.

Companies have been implementing lean manufacturing to improve their business performances. However, many of them have difficulties in the implementation because of various barriers, thus encountering failures. This paper aims to prioritize and analyze the lean barriers for better understanding and interpretation for successful lean implementation.

Extensive literature review has been carried out to identify the lean barriers. Subsequently, total interpretive structural modeling (TISM) has been adopted where lean experts’ inputs have been sought to obtain the self-interaction and reachability matrix. Further, driving power and dependence of lean barriers have been derived, and TISM-based lean barrier model has been developed.

Insufficient management time, insufficient supervisory skills and insufficient senior management skills are the significant barriers with highest driving power and lowest dependence. With low driving power, cost- and funding-related barriers such as cost of the investment, internal funding and external funding are found to be less important barriers.

This model provides a more realistic approach to the problems faced by practitioners during lean implementation. Thus, it provides a roadmap to implement lean by focusing on reducing or eliminating important barriers.

The paper not only provides a TISM-based model of contextual relationships among lean barriers but also describes the validation of this model.

The purpose of the study is to examine the influence of the corn biofuel on the Jet engine. Each tests were carried out in a small gas turbine setup. The performance characteristics of thrust, thrust-specific fuel consumption, exhaust gas temperature and emission characteristics of Carbon monoxide(CO), Carbon dioxide (CO₂), Oxygen (O₂), Unburned hydrocarbons (UHC) and Nitrogen of oxides (NO) emissions were measured and compared with Jet-A fuel to find the suitability of the biofuel used.

Upgrading and using biofuels in aviation sector have been emerging as a fruitful method to diminish the CO emission into the atmosphere. This research paper explores the possibility of using nanoparticles-enriched bio-oil as a fuel for jet engines. The biofuel taken is corn oil and the added nanoparticles are Al₂O₃.

The biofuel blends used are B0 (100% Jet-A fuel), B10 (10 % corn oil biofuel + 90% Jet-A fuel), B20 (20% corn oil biofuel + 80% Jet-A fuel) and B30 (30% corn oil biofuel + 70% Jet-A fuel). All fuel blends were mixed with the moderate dosage level of 30 ppm. All tests were conducted at different rpm as 50,000, 60,000, 70,000 and 80,000 rpm.

The results proved that within the lower limit, use of biofuel increased the performance characteristics and reduced the emission characteristics except the emission of NO. The moderate-level biofuel with Jet-A fuel showed the equally better performance to the neat Jet-A fuel.

The purpose of this study is to identify, analyse and model the post-processing barriers of 3D-printed medical models (3DPMM) printed by fused deposition modelling to overcome these barriers for improved operational efficiency in the Indian context.

The methodology used interpretive structural modelling (ISM), cross-impact matrix multiplication applied to classification (MICMAC) analysis and decision-making trial and evaluation laboratory (DEMATEL) to understand the hierarchical and contextual relations among the barriers of the post-processing.

A total of 11 post-processing barriers were identified in this study using ISM, literature review and experts’ input. The MICMAC analysis identified support material removal, surface finishing, cleaning, inspection and issues with quality consistency as significant driving barriers for post-processing. MICMAC also identified linkage barriers as well as dependent barriers. The ISM digraph model was developed using a final reachability matrix, which would help practitioners specifically tackle post-processing barriers. Further, the DEMATEL method allows practitioners to emphasize the causal effects of post-processing barriers and guides them in overcoming these barriers.

There may have been a few post-processing barriers that were overlooked by the Indian experts, which might have been important for other country’s perspective.

The presented ISM model and DEMATEL provide directions for operation managers in planning operational strategies for overcoming post-processing issues in the medical 3D-printing industry. Also, managers may formulate operational strategies based on the driving and dependence power of post-processing barriers as well as the causal effects relationships of the barriers.

This study contributes to identifying, analyzing and modelling the post-processing barriers of 3DPMM through a combined ISM and DEMATEL methodology, which has not yet been reviewed. This study also contributes to decision makers developing suitable strategies to overcome the post-processing barriers for improved operational efficiency.

The purpose of this paper is to assess the influence of blends of Jatropha methyl ester (JME) and its nano Al₂O₃ emulsion on variable compression ratio diesel engine. The oxygen in alumina contributed for the smooth burning and resulted in improved performance and emissions.

The biodiesel (methyl ester) is prepared from the raw Jatropha oil. The B10, B20 and B30 blends of and their nanoemulsions are prepared with the 25, 50, 75 and 100 ppm of nano Al₂O₃. The prepared JME blends and its nanoemulsions are tested in a variable compression ratio (VCR) diesel engine to evaluate the engine performance and emission characteristics.

The nanoemulsion B20 + 50 ppm has given maximum brake thermal efficiency (BTE), and with the increased proportion of nanoparticle, the BTE was reduced. Also, the specific fuel consumption is lowest (0.2826 kg/kWh) for B20 + 50 ppm at the compression ratio 16.5 and full load which is 4.10% lower than the diesel and 5.8% lower than the B20 blend. As the load increases, NOx emission increases owing to higher peak temperatures in the combustion chamber. The JME-nano Al₂O₃ emulsion reduces the HC and CO emission compared with all other fuels.

Novel nano emulsions are prepared, characterized and tested on VCR engine.

Discusses the efficiency of a cybernetic approach to non‐oscillatory luminescence processes, generated by perturbed biosystems, and applies it to oscillatory luminescence processes. Constructs multiplicative stochastic models of oscillatory bio‐ and chemiluminescence processes, generated by some perturbed/stimulated biosystems (a temperature‐stimulated soybean root system, light‐stimulated microporocytes of larch, antiviral drug‐treated vero cells infected by Herpes simplex virus). Determines a correlation structure for these models by analysing their transfer functions. Uses the memory function approach to compare and contrast the oscillatory processes with their non‐oscillatory analogs. Formulates a hypothesis about the dependence between the persistence and the oscillatory behaviour of biosystems and proposes stochastic perturbation measures founded on those multiplicative models.

This research paper aims to analyze the critical barriers to implementing digitalization in the Indian construction industry as Indian construction companies are lagging in the implementation of digital technologies in the work environment.

In this research paper, a qualitative research approach is adopted, and multiple detailed interviews are conducted with industry and academic experts. Further, multi-criteria decision-making (MCDM) techniques are used to finalize the prioritization among various alternatives. The fuzzy-decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) and interpretive structural modeling (ISM) techniques are employed to find the exact relationship among the identified alternatives.

This study identifies 14 critical barriers from an extensive literature review and multiple interviews with industry professionals, and further driving and critical barriers are identified.

In this research paper, an exploratory study with a limited number of respondents from a large Indian construction company is carried out. Further, a detailed longitudinal analysis can be done to assess the subjectivity of the participants with more advanced statistical tools. However, this research discusses several points pertaining to the implementation of digitalization in the construction industry. The research further identifies the critical barriers to digitalization in the Indian construction industry.

The finding of the study has two-pronged implications. First, it provides a road-map to the construction industry by highlighting the engagement of top management as the key focus area for successful digitalization. Second, the finding also shows similarity of the digitalization process to the adoption of process improvement techniques like lean and total quality management (TQM), wherein the top management plays a crucial role in ushering in the implementation of a disruptive change.

The research is unique in two ways. First, this is one of the very few attempts to understand digitalization in the Indian context. Second, the research also demonstrates that the combination of fuzzy DEMATEL and ISM techniques can be successfully employed in the emerging field of construction digitalization research.