Search results

The aim of this paper is to study the effect of laser shock peening (LSP) on mechanical behaviour of the laser-directed energy deposition (LDED)-based printed 15-5 PH stainless steel with U and V notches. The study specifically concentrates on the evaluation of effect of scan strategy, machining and LSP processing on microstructural, texture evolution and fatigue behaviour of LDED-printed 15-5 PH steel.

For LSP treatment, 15-5 PH steel was printed using LDED process with bidirectional scanning strategy (XX [θ = 0°) and XY [θ = 90°]) at optimised laser power of 600 W with a scanning speed of 300 mm/min and a powder feed rate of 3 g/min. Furthermore, LSP treatment was conducted on the V- and U-notched fatigue specimens extracted from LDED-built samples at laser energy of 3.5 J with a pulse width of 10 ns using laser spot diameter of 3 mm. Post to the LSP treatment, the surface roughness, fatigue life assessment and microstructural evolution analysis is performed. For this, different advanced characterisation techniques are used, such as scanning electron microscopy attached with electron backscatter diffraction for microstructure and texture, X-ray diffraction for residual stress (RS) and structure information, Vicker’s hardness tester for microhardness and universal testing machine for low-cycle fatigue.

It is observed that both scanning strategies during the LDED printing of 15-5 PH steel and laser peening have played significant role in fatigue life. Specimens with the XY printing strategy shows higher fatigue life as compared to XX with both U- and V-notched conditions. Furthermore, machining and LSP treatment led to a significant improvement of fatigue life for both scanning strategies with U and V notches. The extent of increase in fatigue life for both XX and XY scanning strategy with V notch is found to be higher than U notch after LSP treatment, though without LSP samples with U notch have a higher fatigue life. As fabricated sample is found to have the lowest fatigue life as compared to machines and laser peened with both scan strategies.

This study presents an innovative method to improve the fatigue life of 15-5 PH stainless steel by changing the microstructure, texture and RS with the adoption of a suitable scanning strategy, machining and LSP treatment as post-processing. The combination of preferred microstructure and compressive RS in LDED-printed 15-5 PH stainless steel achieved with a synergy between microstructure and RS, which is responsible to improve the fatigue life. This can be adopted for the futuristic application of LDED-printed 15-5 PH stainless steel for different applications in aerospace and other industries.

The purpose of this study was to introduce three-dimensional printing (3DP) of functionally graded sandwich foams (FGSFs). This work was continued by predicting the mechanical buckling and free vibration behavior of 3DP FGSFs using experimental and numerical analyses.

Initially, hollow glass microballoon-reinforced high-density polyethylene-based polymer composite foams were developed, and these materials were extruded into their respective filaments. These filaments are used as feedstock materials in fused filament fabrication based 3DP for the development of FGSFs. Scanning electron microscopy analysis was performed on the freeze-dried samples to observe filler sustainability. Furthermore, the density, critical buckling load (P_cr), natural frequency (f_n) and damping factor of FGSFs were evaluated. The critical buckling load (P_cr) of the FGSFs was estimated using the double-tangent method and modified Budiansky criteria.

The density of FGSFs decreased with increasing filler percentage. The mechanical buckling load increased with the filler percentage. The natural frequency corresponding to the first mode of the FGSFs exhibited a decreasing trend with an increasing load in the pre-buckling regime and an increase in post-buckled zone, whereas the damping factor exhibited the opposite trend.

The current research work is valuable for the area of 3D printing by developing the functionally graded foam based sandwich beams. Furthermore, it intended to present the buckling behavior of 3D printed FGSFs, variation of frequency and damping factor corresponding to first three modes with increase in load.

The purpose of this paper is to investigate the impact of cloud computing (CC) on supply chain management (SCM).

The paper is conceptual and based on a literature review and conceptual analysis.

Today, digital technology is the primary enabler of supply chain (SC) competitiveness. CC capabilities support competitive SC challenges through structural flexibility and responsiveness. An Internet platform based on CC and a digital ecosystem can serve as “information cross-docking” between SC stakeholders. In this way, the SC model is transformed from a traditional, linear model to a platform model with the simultaneous cooperation of all partners. Platform-based SCs will be a milestone in the evolution of SCM – here conceptualised as Supply Chain 3.0.

Currently, SCs managed holistically in cyberspace are rare in practice, and therefore empirical evidence on how digital technologies impact SC competitiveness is required in future research.

This research generates insights that can help managers understand and develop the next generation of SCM with the use of CC, a modern and commonly available Information and Communication Technologies (ICT) tool.

The paper presents a conceptual basis of how CC enables structural flexibility of SCs through easy, real-time resource and capacity reconfiguration. CC not only reduces cost and increases flexibility but also offers an effective solution for disruptive new business models with the potential to revolutionise current SCM thinking.

This paper aims to identify the current situation of higher education institutions in Spain regarding the introduction of the Sustainable Development Goals in the classroom, and what is the role of mathematics in this task.

A review is made of how the concept of sustainability has evolved in higher education, its gradual introduction in the University and the way in which this subject is approached in the field of mathematics.

The study concludes that higher education has a key role to play in designing strategies that lead to the global sustainability of the planet. This implies major changes in degree curricula, assessment, competences and teacher training. Cross-disciplinarity and interdisciplinarity between different subjects within the same degree is a strategy for students to analyse the Sustainable Development Goals using mathematical techniques.

The University as an institution must train socially responsible professionals who are aware of the importance of promoting a sustainable world. Changes should be made to introduce values in the classroom that promote and encourage sustainability. Training should be seen as a continuous process that leads to the preparation of professionals committed to society and nature and who develop strategies aimed at improving the planet through values.

Through practical activities, the Sustainable Development objectives can be analysed from several subjects of the same degree, emphasising the interdisciplinary and transversal nature that should be the central axis of higher education. Each subject can develop a strategy for change in favour of sustainability that will be reinforced and increased by working together on the proposed teaching practice. In this way, the contents of the different subjects are not isolated, but rather the student can see how there is an interrelationship between them and with real life.

The main purpose of this paper is to discuss the suitability of moral and ordre public clauses, and to advance the view that ethical reflection within patent systems is valuable.

This is a conceptual paper that draws upon the present situation in Europe to illuminate a discussion of the different views about the morality patents, with particular emphasis on criticism of authors who have espoused a narrow interpretation of moral clauses, such as that adopted by the European Patent Office.

This research found that the claim that patent systems are not appropriate places in which to evaluate moral matters and, therefore, they cannot inform us about morality is false. This is because inventors do not need to wait for authorizing legislation prior to making use of their technology. Hence, moral implications can be evaluated.

These ideas also lead to important theoretical consequences, especially regarding the debate on value-laden science and technology. However, further efforts are needed to address other patent regimes, such as the non-European.

It is shown how the bioethicist community can be incorporated into patent offices. The responsibilities of examiners and businesses in the process are also discussed.

There have been a limited number of studies that examine the value of ethical considerations within the patent system. This paper provides a thought-provoking discussion of moral clauses in Europe. The author also suggests new ways of incorporating ethical scrutiny into patent systems.

The purpose of this study is to explore Generation Z (Gen Z) consumers’ sustainable consumption behaviors at a university campus by examining various antecedent and moderating influencers of their sustainable consumption behaviors.

A quantitative research methodology is used in this study. A structured questionnaire was administered (n = 279) to young college students (Gen Z consumers in the context of this study) enrolled at a large state university in the USA. The structural equation model was used to test the hypothesized relationships in the conceptualized model.

Study findings show that social responsibility (feelings, engagement and expectations) and external incentives (material and social) positively influence Gen Z consumers’ sustainability interests, which in turn influences their sustainable consumption behaviors (actions). Collectivist cultural values did not appear to have any statistically significant effect on Gen Z consumers’ sustainable consumption interests. Moreover, learned helplessness, perceived barriers and the awareness of the consequences of sustainability consumption actions did not have any significant moderating effect on Gen Z consumers’ sustainable consumption behavior.

The questionnaire was only sent to students majoring in business degrees, which may limit the generalizability of this study to broader Gen Z consumer populations. Expanding this study to include non-business students may be valuable as a next step. Replicating this study in different cultural environments of international countries could enhance the relationships identified in this study.

Consumer social responsibility education along with material and social incentives will encourage Gen Z consumers’ participation in sustainable behaviors at college campuses.

This research provides valuable insights into understanding the importance of consumer social responsibility and external incentives in influencing Gen Z consumers’ sustainable consumption intentions and behaviors. Accordingly, consumer social responsibility education and incentive programs need to be developed to encourage the participation of Gen Z consumers in sustainable consumption.

The purpose of this paper is to address the need for new approaches in locating items that closely match user preference criteria due to the rise in data volume of knowledge bases resulting from Open Data initiatives. Specifically, the paper focuses on evaluating SPARQL qualitative preference queries over user preferences in SPARQL.

The paper outlines a novel approach for handling SPARQL preference queries by representing preferences through symbolic weights using the possibilistic logic (PL) framework. This approach allows for the management of symbolic weights without relying on numerical values, using a partial ordering system instead. The paper compares this approach with numerous other approaches, including those based on skylines, fuzzy sets and conditional preference networks.

The paper highlights the advantages of the proposed approach, which enables the representation of preference criteria through symbolic weights and qualitative considerations. This approach offers a more intuitive way to convey preferences and manage rankings.

The paper demonstrates the usefulness and originality of the proposed SPARQL language in the PL framework. The approach extends SPARQL by incorporating symbolic weights and qualitative preferences.

Dynamic low adhesion (DLA) has become an urgent problem for the high-speed wheel-rail system because of continuous decrease of adhesion redundancy in the past decades. This article aims to provide a simulation method to reveal the mechanism of DLA under high-frequency vibrations.

A transient wheel-rail rolling contact model is developed for a typical Chinese high-speed railway system using the explicit finite element (FE) method. Instantaneous adhesion exploitation levels are studied in the time domain, for which driving cases over corrugated rails are taken as an example. A speed up to 500 km/h is considered together with different traction coefficients and corrugation dimensions. DLA is expected when the instantaneous adhesion exploitation level reaches 1.0, that is adhesion saturates and full sliding contact occurs.

The instantaneous adhesion exploitation level can be very high in the presence of corrugation, even at low traction coefficients. DLA is found to occur as great vertical unloading takes place and causes a significant increase of creepage. An approach is further developed to determine the critical depth of corrugation over which DLA occurs.

This study employs the transient wheel-rail rolling contact model to predict the instantaneous adhesion exploitation level under high-frequency vibrations. The presented results reveal a mechanism of DLA being beneficial to guidelines for future railway practice.

The term knowledge refers to the part of the world investigated by a specific discipline and that includes a specific taxonomy, vocabulary, concepts, theories, research methods and standards of justification. Our approach uses domain knowledge to improve the quality of business process models (BPMs) by exploiting the domain knowledge provided by large language models (LLMs). Among these models, ChatGPT stands out as a notable example of an LLM capable of providing in-depth domain knowledge. The lack of coverage presents a limitation in each approach, as it hinders the ability to fully capture and represent the domain’s knowledge. To solve such limitations, we aim to exploit GPT-3.5 knowledge. Our approach does not ask GPT-3.5 to create a visual representation; instead, it needs to suggest missing concepts, thus helping the modeler improve his/her model. The GPT-3.5 may need to refine its suggestions based on feedback from the modeler.

We initiate our semantic quality enhancement process of a BPM by first extracting crucial elements including pools, lanes, activities and artifacts, along with their corresponding relationships such as lanes being associated with pools, activities belonging to each lane and artifacts associated with each activity. These data are systematically gathered and structured into ArrayLists, a form of organized collection that allows for efficient data manipulation and retrieval. Once we have this structured data, our methodology involves creating a series of prompts based on each data element. We adopt three approaches to prompting: zero-shot, few-shot and chain of thoughts (CoT) prompts. Each type of prompting is specifically designed to interact with the OpenAI language model in a unique way, aiming to elicit a diverse array of suggestions. As we apply these prompting techniques, the OpenAI model processes each prompt and returns a list of suggestions tailored to that specific element of the BPM. Our approach operates independently of any specific notation and offers semi-automation, allowing modelers to select from a range of suggested options.

This study demonstrates the significant potential of prompt engineering techniques in enhancing the semantic quality of BPMs when integrated with LLMs like ChatGPT. Our analysis of model activity richness and model artifact richness across different prompt techniques and input configurations reveals that carefully tailored prompts can lead to more complete BPMs. This research is a step forward for further exploration into the optimization of LLMs in BPM development.

The limitation is the domain ontology that we are relying on to evaluate the semantic completeness of the new BPM. In our future work, the modeler will have the option to ask for synonyms, hyponyms, hypernyms or keywords. This feature will facilitate the replacement of existing concepts to improve not only the completeness of the BPM but also the clarity and specificity of concepts in BPMs.

To demonstrate our methodology, we take the “Hospitalization” process as an illustrative example. In the scope of our research, we have presented a select set of instructions pertinent to the “chain of thought” and “few-shot prompting.” Due to constraints in presentation and the extensive nature of the instructions, we have not included every detail within the body of this paper. However, they can be found in the previous GitHub link. Two appendices are given at the end. Appendix 1 describes the different prompt instructions. Appendix 2 presents the application of the instructions in our example.

In our research, we rely on the domain application knowledge provided by ChatGPT-3 to enhance the semantic quality of BPMs. Typically, the semantic quality of BPMs may suffer due to the modeler's lack of domain knowledge. To address this issue, our approach employs three prompt engineering methods designed to extract accurate domain knowledge. By utilizing these methods, we can identify and propose missing concepts, such as activities and artifacts. This not only ensures a more comprehensive representation of the business process but also contributes to the overall improvement of the model's semantic quality, leading to more effective and accurate business process management.

Resin-based friction materials are the most widely used key materials in industry for braking and transmission. However, the friction coefficient of resin-based friction materials significantly decreases at temperatures above 300°C, which reduces their friction performance.

This study combines elevated-temperature mechanical experiments with friction and wear experiments to explain the thermal degradation resistance performance and temperature recovery performance of resin-based friction materials. It also investigates the influence of friction material strength and worn morphology on the friction coefficient of materials at elevated temperature.

The experimental results show that the increase in friction coefficient of friction materials below 300°C is mainly due to the increase in worn morphology characterization parameters, and the thermal degradation phenomenon above 300°C is mainly due to the decrease of shear strength of friction film. Basalt fiber can significantly improve the thermal degradation resistance of friction materials. The friction coefficient of basalt fiber-reinforced specimens after thermal degradation reaches 0.421–0.443, which is 19–25% higher than the original. The thermal decay rate is 9.03–11.0%, which is 7.9–9.87% lower than the original. Moreover, the friction coefficient has good cooling recovery performance.

Revealed the thermal degradation mechanism of resin-based friction materials, verified that basalt fibers can improve the thermal degradation resistance of friction materials and provided reference for the development of new friction materials.