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In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.

To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.

The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.

The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.

Despite the opportunities of digital twins (DTs) for smart buildings, limited research has been conducted regarding the facility management stage, and this is explained by the high complexity of accurately representing and modelling the physics behind the DTs process. This study thus organises and consolidates the fragmented literature on DTs implementation for smart buildings at the facility management stage by exploring the enablers, applications and challenges and examining the interrelationships amongst them.

A systematic literature review approach is adopted to analyse and synthesise the existing literature relating to the subject topic.

The study revealed six main categories of enablers of DTs for smart building at the facility management stage, namely perception technologies, network technologies, storage technologies, application technologies, knowledge-building and design processes. Three substantial categories of DTs application for smart buildings were revealed at the facility management stage: efficient operation and service monitoring, efficient building energy management and effective smart building maintenance. Subsequently, the top four major challenges were identified as being “lack of a systematic and comprehensive reference model”, “real-time data integration”, “the complexity and uncertainty nature of real-time data” and “real-time data visualisation”. An integrative framework is finally proposed by examining the interactive relationship amongst the enablers, the applications and the challenges.

The findings could guide facility managers/engineers to fairly understand the enablers, applications and challenges when DTs are being implemented to improve smart building performance and achieve user satisfaction at the facility management stage.

This study contributes to the knowledge body on DTs by extending the scope of the existing studies to identify the enablers and applications of DTs for smart buildings at the facility management stage and the specific challenges.

The purpose of this study is to propose a precise and standardized strategy for numerically simulating vehicle aerodynamics.

Error sources in computational fluid dynamics were analyzed. Additionally, controllable experiential and discretization errors, which significantly influence the calculated results, are expounded upon. Considering the airflow mechanism around a vehicle, the computational efficiency and accuracy of each solution strategy were compared and analyzed through numerous computational cases. Finally, the most suitable numerical strategy, including the turbulence model, simplified vehicle model, calculation domain, boundary conditions, grids and discretization scheme, was identified. Two simplified vehicle models were introduced, and relevant wind tunnel tests were performed to validate the selected strategy.

Errors in vehicle computational aerodynamics mainly stem from the unreasonable simplification of the vehicle model, calculation domain, definite solution conditions, grid strategy and discretization schemes. Using the proposed standardized numerical strategy, the simulated steady and transient aerodynamic characteristics agreed well with the experimental results.

Building upon the modified Low-Reynolds Number k-e model and Scale Adaptive Simulation model, to the best of the authors’ knowledge, a precise and standardized numerical simulation strategy for vehicle aerodynamics is proposed for the first time, which can be integrated into vehicle research and design.

The purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper studies the applicability of different CG designs and the efficiency of some design parameters.

After reviewing a number of different papers, two designs were selected for a number of exploratory experiments. Using design of experiments (DOE) techniques to identify important design parameters. Finally, the efficiency of the parts was investigated.

The research finds that a simpler design sacrifices some effectiveness in exchange for a remarkable decrease in production cost. Decreasing infill percentage of previous designs and 3D printing them, out of TPU, experimenting with different parameters yields functional products. Moreover, the paper identified some key parameters for further optimization attempts of such prototypes.

The cost of conducting FFF experiments for TPU increases dramatically with product size, number of parameters studied and the number of experiments. Therefore, all three of these factors had to be kept at a minimum. Further confirmatory experiments encouraged.

This paper addresses an identified need to investigate applications of FFF and TPU in manufacturing functional efficient flexible mechanisms, grippers specifically. While most research focused on designing for increased performance, some research lacks discussion on design philosophy, as well as manufacturing issues. As the needs for flexible grippers vary from high-performance grippers to lower performance grippers created for specific functions/conditions, some effectiveness can be sacrificed to reduce cost, reduce complexity and improve applicability in different robotic assemblies and environments.

The purpose of this study is analysis of deformation and vibrations of turbine blades produced by high electrolyte pressure during electrochemical machining.

An experimental setup was designed, experiments were conducted and the obtained results were compared with the finite element results. The deformations were measured according to various flow rates of electrolyte. In finite element calculations, the pressure distribution created by the electrolyte on the blade surface was obtained in the ANSYS® (A finite element analysis software) Fluent software and transferred to the static structural where the deformation analysis was carried out. Three different parameters were examined, namely blade thickness, blade material and electrolyte pressure on blade disk caused by mass flow rate. The deformation results were compared with the gap distances between cathode and anode.

Large deformations were obtained at the free end of the blade and the most curved part of it. The appropriate pressure values for the electrolyte to be used in the production of blisk blades were proposed numerically. It has been determined that high pressure applications are not suitable for gap distance lower than 0.5 mm.

When the literature is examined, it is required that the high speed flow of the electrolyte is desired in order to remove the parts that are separated from the anode from the machining area during electrochemical machining. However, the electrolyte flowing at high speeds causes high pressure in the blisk blades, excessive deformation and vibration of the machined part, and as a result, contact of the anode with the cathode. This study provides important findings for smooth electro chemical machining at high electrolyte flows.

This paper aims to investigate the moisture diffusion behavior in a system-in-package module systematically by moisture-thermalmechanical-coupled finite element modeling with different structure parameters under increasingly harsh environment.

A finite element model for a system-in-package module was built with moisture-thermal-mechanical-coupled effects to study the subsequences of hygrothermal conditions.

It was found in this paper that the moisture diffusion path was mainly dominated by hygrothermal conditions, though structure parameters can affect the moisture distribution. At lower temperatures (30°C~85°C), the direction of moisture diffusion was from the periphery to the center of the module, which was commonly found in simulations and literatures. However, at relatively higher temperatures (125°C~220°C), the diffusion was from printed circuit board (PCB) to EMC due to the concentration gradient from PCB to EMC across the EMC/PCB interface. It was also found that there exists a critical thickness for EMC and PCB during the moisture diffusion. When the thickness of EMC or PCB increased to a certain value, the diffusion of moisture reached a stable state, and the concentration on the die surface in the packaging module hardly changed. A quantified correlation between the moisture diffusion coefficient and the critical thickness was then proposed for structure parameter optimization in the design of system-in-package module.

The different moisture diffusion behaviors at low and high temperatures have seldom been reported before. This work can facilitate the understanding of moisture diffusion within a package and offer some methods about minimizing its effect by design optimization.