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IN order to prevent acoustic fatigue cracks occurring in structure subjected to jet noise the various airworthiness authorities are proposing to lay down appropriate design criteria. It may not be long therefore before airframe manufacturers are required to show to airworthiness authorities that either:

In this article, we discuss an innovative audience research methodology developed for the AHRC-funded “Beyond the Multiplex: Audiences for Specialised Film in English Regions” project (BtM). The project combines a computational ontology with a mixed-methods approach drawn from both the social sciences and the humanities, enabling research to be conducted both at scale and in depth, producing complex relational analyses of audiences. BtM aims to understand how we might enable a wide range of audiences to participate in a more diverse film culture, and embrace the wealth of films beyond the mainstream in order to optimise the cultural value of engaging with less familiar films. BtM collects data through a three-wave survey of film audience members’ practices, semi-structured interviews and film-elicitation groups with audience members alongside interviews with policy and industry experts, and analyses of key policy and industry documents. Bringing each of these datasets together within our ontology enables us to map relationships between them across a variety of different concerns. For instance, how cultural engagement in general relates to engagement with specialised films; how different audiences access and/or share films across different platforms and venues; how their engagement with those films enables them to make meaning and generate value; and how all of this is shaped by national and regional policy, film industry practices, and the decisions of cultural intermediaries across the fields of film production, distribution and exhibition. Alongside our analyses, the ontology enables us to produce data visualisations and a suite of analytical tools for audience development studies that stakeholders can use, ensuring the research has impact beyond the academy. This paper sets out our methodology for developing the BtM ontology, so that others may adapt it and develop their own ontologies from mixed-methods empirical data in their studies of other knowledge domains.

The paper aims to highlight the importance of having an optical method that can accurately measure the surface finish of 3D printed parts and the influence this has on the total volume of the build.

The paper describes the application of digital moiré to the determination of the surface finish of 3D printed parts.

This study shows that surface roughness plays an important role in the volumetric analysis. There was an increase of 7 per cent from the total volume of the original CAD drawing; in total, there was 19 per cent more material deposited.

This methodology provides a robust tool for future research in the area of geometrical verification and optimization in addition to the potential use for residual stress determination.

This study shows that process optimization can be carried out more efficiently, and it is possible to determine the efficiency of an AM process by directly correlating the processing parameters and accurately comparing the prescribed CAD dimensions/volume to that of the as built part.

By reducing the amount of waste through process optimization, this leads to a reduced consumption of energy which can have a major impact on the environment.

This paper fulfills the need for high accuracy volumetric measurement of 3D printed components.

THE solution of the differential equations for the varied cases of laterally loaded struts present arithmetical difficulties particularly as the number of the integration constants contained in a problem increase. The time taken to obtain an acceptable solution can be extremely long if the first answer arrived at does not seem to be of the right order, thereby indicating an error in the evaluation of the constants.

A key challenge for cost-effective Intelligent Tutoring Systems (ITSs) is the ability to create generalizable domain, learner, and pedagogical models so they can be re-used many times over. Investment in this technology will be needed to succeed in developing ITSs for team training. The purpose of this chapter is to propose an instructional framework for guiding team ITS researchers in their development of these models for reuse. We establish a foundation for the framework with three propositions. First, we propose that understanding how teams develop is needed to establish a science-based foundation for modeling. Toward this end, we conduct a detailed exploration of the Kozlowski, Watola, Jensen, Kim, and Botero (2009) theory of team development and leadership, and describe a use case example to demonstrate how team training was developed for a specific stage in their model. Next, we propose that understanding measures of learning and performance will inform learner modeling requirements for each stage of team development. We describe measures developed for the use case and how they were used to understand teamwork skill development. We then discuss effective team training strategies and explain how they were implemented in the use case to understand their implications for pedagogical modeling. From this exploration, we describe a generic instructional framework recommending effective training strategies for each stage of team development. To inform the development of reusable models, we recommend selecting different team task domains and varying team size to begin researching commonalities and differences in the instructional framework.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

The purpose of this study was to use bridge curvature method (BCM) to quantify stress, while multiscale modeling with adaptive coarsening predicted distortions based on experimentally validated models. Taguchi method and response surface method were used to optimize process parameters (energy density, hatch spacing, scanning speed and beam diameter).

Laser powder bed fusion (LPBF) offers significant design freedom but suffers from residual stresses due to rapid melting and solidification. This study presents a novel approach combining multiscale modeling and statistical optimization to minimize residual stress in SS316L.

Optimal parameters were identified through simulations and validated with experiments, achieving an 8% deviation. This approach significantly reduced printing costs compared to traditional trial-and-error methods. The analysis revealed a non-monotonic relationship between residual stress and energy density, with an initial increase followed by a decrease with increasing hatch spacing and scanning speed (both contributing to lower energy density). Additionally, beam diameter had a minimal impact compared to other energy density parameters.

This work offers a unique framework for optimizing LPBF processes by combining multiscale modeling with statistical techniques. The identified optimal parameters and insights into the individual and combined effects of energy density parameters provide valuable guidance for mitigating residual stress in SS316L, leading to improved part quality and performance.

The ability to use laser powder bed fusion (LPBF) to print parts with tailored surface topography could reduce the need for costly post-processing. However, characterizing the as-built surface topography as a function of process parameters is crucial to establishing linkages between process parameters and surface topography and is currently not well understood. The purpose of this study is to measure the effect of different LPBF process parameters on the as-built surface topography of Inconel 718 parts.

Inconel 718 truncheon specimens with different process parameters, including single- and double contour laser pass, laser power, laser scan speed, build orientation and characterize their as-built surface topography using deterministic and areal surface topography parameters are printed. The effect of both individual process parameters, as well as their interactions, on the as-built surface topography are evaluated and linked to the underlying physics, informed by surface topography data.

Deterministic surface topography parameters are more suitable than areal surface topography parameters to characterize the distinct features of the as-built surfaces that result from LPBF. The as-built surface topography is strongly dependent on the built orientation and is dominated by the staircase effect for shallow orientations and partially fused metal powder particles for steep orientations. Laser power and laser scan speed have a combined effect on the as-built surface topography, even when maintaining constant laser energy density.

This work addresses two knowledge gaps. (i) It introduces deterministic instead of areal surface topography parameters to unambiguously characterize the as-built LPBF surfaces. (ii) It provides a methodical study of the as-built surface topography as a function of individual LPBF process parameters and their interaction effects.

The increased use cases for laser powder bed fusion (LPBF) in the research and commercial domains necessitate a better understanding of the inputs and the processing parameters. Porosity in parts manufactured by LPBF could lead to premature failure and increased cost. The powder bed, which is selectively laser melted, must be as densely packed as possible to ensure high-density parts. This paper aims to identify and qualify the variables that affect the packing density of the powder bed.

Six different independent variables that affect the packing density of the powder were identified and quantified. The chemical composition, true powder density, powder size distribution, powder circularity and convexity and powder morphology were studied. A powder bed density capsule was printed in place to determine the actual powder bed density in the LPBF unit.

Particle size destitution is the most critical aspect of the packing density in the LPBF unit. Powder with better circularity, convexity and higher powder density has proven to pack less densely than powder with many smaller particles. A more significant number of fine particles will ensure the voids between larger particles are filled, and a denser item, with less porosity, can be manufactured.

The independent variables quantified in this study to determine their effect on the packing densities are discussed. Adherence to the ASTM standard applicable to this industry is discussed, and the quantification method is evaluated. This work’s original contribution is identifying the effect of the ratio of D₉₀ to D₁₀ values based on particle diameter and its interaction within the LPBF unit to result in the highest possible packing density.

The purpose of this study is to examine the effects of nitrogen (N) deposition on clonal growth in a rhizome clonal plant, Leymus chinensis (Trin.) Tzvel.

The study established seven N concentration gradients (0, 2, 4, 8, 16, 32 and 64 g N m⁻²) to simulate the continuous increase in N deposition for the cultivation of L. chinensis seedlings and assess the response mechanism of the cloned L. chinensis plant at different N levels by analyzing the aboveground and belowground plant appearance traits, parent ramets and daughter ramets of resource allocation and biomass allocation.

The results of this study showed that the different N treatment levels could promote clonal growth and had certain regularity under the seven treatments. The addition of N could significantly increase the ramet number, rhizome length, rhizome spacer length, biomass of mother ramets, daughter ramets and belowground L. chinensis population when the N addition was greater than 4 g m⁻²; however, the clonal growth ability of L. chinensis decreased and the rhizome length, ramet number, stem and leaf biomass of daughter ramets and stem biomass of mother ramets significantly decreased when the N addition was greater than 32 g N m⁻².

With global warming, atmospheric N deposition is increasing and it is of great significance to explore the response mechanism of different N levels for the growth of clone plants. This study provides basic data and a theoretical basis for the survival prediction of cloned plants under the background of a global climate change strategy and has important theoretical and practical significance for the scientific management of grasslands in the future.