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Conventional investment casting of turbine blades is a time consuming and expensive process due to the complications in wax injection steps and the complex shape of airfoil surfaces. By using rapid investment casting, a substantial improvement in the gas turbine blade manufacturing process can be expected. However, this process needs to be able to compete with conventional investment casting from a dimensional accuracy view of point. The purpose of this paper is to investigate the manufacture of gas turbine blades via two indirect rapid tooling (RT) technologies, namely epoxy (EP) resin tooling and silicon rubber molding.

The second stage blade of a Ruston TA 1750 gas turbine (rated at 1.3 MW) was digitized by a coordinate measuring machine. The aluminum‐filled EP resin and silicon rubber molds were fabricated using StereoLithography master models. Several wax patterns were made by injection in the EP resin and silicone rubber molds. These wax patterns were utilized for ceramic shell fabrication and blade casting.

Dimensional inspection of cast blades showed that silicone rubber molding was not a suitable approach for production of blade wax patterns. The maximum deviation for the final cast blade made using the silicone rubber mold was +0.402 mm. The maximum deviation for the final cast blade made using the EP resin mold was lower at −0.282 mm. This showed that EP resin tooling could enable new cost‐effective solutions for small batch production of gas turbine blades.

The research results presented will give efficient industrial approach and scientific insight of the gas turbine blade manufacturing by use of rapid technologies.

There are some general research works related to utilization of rapid technologies for manufacturing of gas turbine blade. However, this paper presents a unique procedure of integrated reverse engineering and RT technologies for rapid investment casting of gas turbine blade through presenting comprehensive comparison between two techniques from dimensional accuracy view of point.

The purpose of this study is to evaluate the geometric quality of small diameter holes in parts printed by direct metal laser sintering (DMLS) technology. An in-process optical inspection method is proposed and assessed during a pilot study. The influence of the theoretical hole diameter assumed in a computer-aided design (CAD) system and the sample thickness (hole length) on the hole clearance was analyzed.

The samples are made of two different materials: EOS MaragingSteel MS1 and aluminium alloy EOS Aluminium consisted of straight through holes of different diameters and lengths. Dimensional and shape accuracy of the holes were determined with the use of the image processing software and the computer analysis of two-dimensional (2-D) images. The definition of the equivalent hole diameter was proposed to calculate the hole clearance. Feret’s diameters were determined for the evaluation of the shape accuracy.

The dependency between the equivalent hole diameter and the theoretical diameter was approximated by the linear function for a specific sample thickness. Additionally, a general empirical model for determining the hole clearance was developed, allowing for calculating the equivalent hole diameter as a function of a sample thickness and a theoretical hole diameter.

Developed functions can be used by designers for a proper assignment of a hole diameter to achieve the required patency. The relevant procedures and macros based on proposed empirical models can be embedded in CAD systems to support the designing process.

The analysis of the geometric quality of the holes in parts printed by DMLS was based on the computer analysis of 2-D images. The proposed method of assessing the shape accuracy of straight through holes is relatively cheap, is widely available and can be applied to the features of other shapes produced by three-dimensional printing.

Rapid tooling (RT) integrated with additive manufacturing technologies have been implemented in various sectors of the RT industry in recent years with various kinds of prototype applications, especially in the development of new products. The purpose of this study is to analyze the current application trends of RT techniques in producing hybrid mold inserts.

The direct and indirect RT techniques discussed in this paper are aimed at developing a hybrid mold insert using metal epoxy composite (MEC) in increasing the speed of tooling development and performance. An extensive review of the suitable development approach of hybrid mold inserts, material preparation and filler effect on physical and mechanical properties has been conducted.

Latest research studies indicate that it is possible to develop a hybrid material through the combination of different shapes/sizes of filler particles and it is expected to improve the compressive strength, thermal conductivity and consequently increasing the hybrid mold performance (cooling time and a number of molding cycles).

The number of research studies on RT for hybrid mold inserts is still lacking as compared to research studies on conventional manufacturing technology. One of the significant limitations is on the ways to improve physical and mechanical properties due to the limited type, size and shape of materials that are currently available.

This review presents the related information and highlights the current gaps related to this field of study. In addition, it appraises the new formulation of MEC materials for the hybrid mold inserts in injection molding application and RT for non-metal products.

We present Bayesian models for finding the longitudinal causal effects of a randomized two-arm training program when compliance with the randomized assignment is less than perfect in the training arm (but perfect in the non-training arm) for reasons that are potentially correlated with the outcomes. We deal with the latter confounding problem under the principal stratification framework of Sommer and Zeger (1991) and Frangakis and Rubin (1999), and others. Building on the Bayesian contributions of Imbens and Rubin (1997), Hirano et al. (2000), Yau and Little (2001) and in particular Chib (2007) and Chib and Jacobi (2007, 2008), we construct rich models of the potential outcome sequences (with and without random effects), show how informative priors can be reasonably formulated, and present tuned computational approaches for summarizing the posterior distribution. We also discuss the computation of the marginal likelihood for comparing various versions of our models. We find the causal effects of the observed intake from the predictive distribution of each potential outcome for compliers. These are calculated from the output of our estimation procedures. We illustrate the techniques and ideas with data from the 1994 JOBS II trial that was set up to test the efficacy of a job training program on subsequent mental health outcomes.

This paper aims to suggest the use of air or iron intervals between axially magnetized rings to increase the forces and stiffness of permanent magnet passive magnetic bearings (PMBs). The paper calculates the stiffness of such bearings through an analytical method and optimizes the dimensions of the magnets for achieving maximum stiffness.

For determining the magnetic fields distribution, forces and stiffness of the bearings, a 2D analytical method is used, based on the subdomain method. For the sake of generalization, all of the parameters are normalized and optimized for maximum normalized stiffness per magnet volume ratio.

The optimum sizes of the magnets as well as the optimum dimensions of the air or iron intervals are calculated in this paper. The optimum sizes of the magnets are around the air gap length and it is very difficult to realize them. Using iron intervals can improve the stiffness to the extremely high values in practical dimensions of the magnets.

This paper presents a novel configuration for improving the performance of PMBs with alternately axially magnetized rings.

Permanent magnet passive magnetic bearings (PMBs) are used for suspension of rotating shafts in one direction. PMBs with alternating radially magnetized rings having back iron is one of the most optimum configurations among all configurations of PMBs. This paper aims to investigate the effect of the conductivity and permeability of these back irons on the stiffness and damping of the configuration.

The stiffness and damping of the configuration will be calculated through a 2D dynamic analytical method and validated by FEM simulations.

The results of the paper show how the permeability and conductivity of the back irons can affect stiffness and damping of PMB. Furthermore, the size of the magnets and the air intervals between them are optimized for maximum stiffness and damping.

The results show that these bearings can have some intrinsic damping without any loss of stiffness, which can be useful for many applications.

Reliability-based design optimizations (RBDOs) of engineering structures involve complex non-linear/non-differentiable performance functions, including both continuous and discrete variables. The gradient-based RBDO algorithms are less than satisfactory for these cases. The simulation-based approaches could also be computationally inefficient, especially when the double-loop strategy is used. This paper aims to present a pseudo-double loop flexible RBDO, which is efficient for solving problems, including both discrete/continuous variables.

The method is based on the hybrid improved binary bat algorithm (BBA) and weighed simulation method (WSM). According to this method, each BBA’s movement generates proper candidate solutions, and subsequently, WSM evaluates the reliability levels for design candidates to conduct swarm in a low-cost safe-region.

The accuracy of the proposed enhanced BBA and also the hybrid WSM-BBA are examined for ten benchmark deterministic optimizations and also four RBDO problems of truss structures, respectively. The solved examples reveal computational efficiency and superiority of the method to conventional RBDO approaches for solving complex problems including discrete variables.

Unlike other RBDO approaches, the proposed method is such organized that only one simulation run suffices during the optimization process. The flexibility future of the proposed RBDO framework enables a designer to present multi-level design solutions for different arrangements of the problem by using the results of the only one simulation for WSM, which is very helpful to decrease computational burden of the RBDO. In addition, a new suitable transfer function that enhanced convergence rate and search ability of the original BBA is introduced.

The purpose of this paper is to explore addiction service users’ experiences of psychological interventions for depression symptoms, with an emphasis on understanding obstacles to engage with treatment.

This was a thematic analysis of semi-structured interviews with ten people who took part in a randomised controlled trial of cognitive and behavioural interventions; four of whom never engaged with treatment.

Five prominent obstacles to access therapy were: memory deficits, becoming overwhelmed by multiple demands and appointments, being housebound due to fluctuations in mental health problems, tendency to avoid the unfamiliar, and contextual life problems related to deprivation and social conflict.

The authors note some possible limitations related to overreliance on telephone interviews and interviewers’ field notes. The authors discuss the findings in light of epidemiological research, cognitive, behavioural and motivational enhancement theories.

The authors propose it is important to recognise and address multiple obstacles to therapy. Offering therapy appointments that are co-located within addiction services and time-contingent to other social/medical interventions may help to address some of these obstacles.

The present qualitative results complement the prior experimental research and enrich the understanding of how to maximise engagement with psychological interventions.

In order to solve the problems faced by First Order Reliability Method (FORM) and First Order Saddlepoint Approximation (FOSA) in structural reliability optimization, this paper aims to propose a new Reliability-based Design Optimization (RBDO) strategy for offshore engineering structures based on Original Probabilistic Model (OPM) decoupling strategy. The application of this innovative technique to other maritime structures has the potential to substantially improve their design process by optimizing cost and enhancing structural reliability.

In the strategy proposed by this paper, sequential optimization and reliability assessment method and surrogate model are used to improve the efficiency for solving RBDO. The strategy is applied to the analysis of two marine engineering structure cases of ship cargo hold structure and frame ring of underwater skirt pile gripper. The effectiveness of the method is proved by comparing the original design and the optimized results.

In this paper, the proposed new RBDO strategy is used to optimize the design of the ship cargo hold structure and the frame ring of the underwater skirt pile gripper. According to the results obtained, compared with the original design, the structure of optimization design has better reliability and stability, and reduces the risk of failure. This optimization can also better balance the relationship between performance and cost. Therefore, it is recommended for related RBDO problems in the field of marine engineering.

In view of the limitations of FORM and FOSA that may produce multiple MPPs for a single performance function, the new RBDO strategy proposed in this study provides valuable insights and robust methods for the optimization design of offshore engineering structures. It emphasizes the importance of combining advanced MPP search technology and integrating SORA and surrogate models to achieve more economical and reliable design.

Different external supply scenarios faced by the retailers will affect their choice of strategy when supply is disrupted and becomes far less than demand, urgently. This study focuses on analyzing both demand and supply side response strategies to meet customer demand and reduce the impact of the shortage during supply disruptions.

According to the quantity of products that the external market can provide, the external supply scenarios were divided into sufficient-type external supply and learning-type external supply. A two-echelon perishable goods supply chain was analyzed, and three kinds of contingency strategy models for downstream retailers were investigated. First, in the sufficient external supply scenario, the optimal price and transshipment quantity to maximize retailer's profits is discussed. Second, in the scenario of learning-type external supply, this study analyzes the optimal decision in three mechanisms of the hybrid strategy and their application: price priority mechanism, quantity priority mechanism and price–quantity balance mechanism. Furthermore, the influence of penalty cost and supply on the priority orders of different mechanisms was studied.

Results show that comparing the two pure strategies (pricing strategy and transshipment strategy)it was noted that the hybrid strategy produces the best results in sufficient-type external supply scenario. In the learning-type external supply scenario, a numerical study has shown the existence of three areas in case of penalty cost and supplier's capacity, and each areas has different priority orders of the three mechanisms. Under the situation of learning external supply, the retailer's optimal strategy is affected by parameters such as penalty cost and supply volume.

The main innovation of the work lies in the following: First; the external supply situation was divided into sufficiency type and learning type, which improves the external situation faced by retailers after the outbreak of emergencies, helps retailers understand the external situation, conforms to the actual situation and has certain practical application value. Second; in the context of learning external supply, there are three coping strategies for retailers, including: Price priority mechanism, Quantity priority mechanism and Pricing and transshipment balance mechanism. This will help retailers make strategic choices, make more scientific management decisions and improve the supply chain emergency management theory. Third; the demand side response was managed through the change of external supply during supply side recovery period and supply disruption. The proposed model enables managing and analyzing supply disruption efficiently and effectively via handling uncertainty by considering all aspects of decision-making process. The proposed model can be applied in various fields such as vegetable and fruit, fresh food, etc.