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It is of great significance to study the influence of subgrade filling on permafrost temperature field in permafrost area for the smooth construction and safe operation of railway.

The paper builds up the model for the hydrothermal coupling calculation of permafrost using finite element software COMSOL to study how permafrost temperature field changes in the short term after subgrade filling, on which basis it proposes the method of calculation for the concave distortion of freezing front in the subgrade-covered area.

The results show that the freezing front below the subgrade center sinks due to the thermal effect of subgrade filling, which will trigger hydrothermal erosion in case of sufficient moisture inflows, leading to the thawing settlement or the cracking of the subgrade, etc. The heat output of soil will be hindered the most in case of July filling, in which case the sinking and the distortion of the freezing front is found to be the most severe, which the recovery of the permafrost temperature field, the slowest, constituting the most unfavorable working condition. The concave distortion of the freezing front in the subgrade area increases with the increase in temperature difference between the filler and ground surface, the subgrade height, the subgrade width and the volumetric thermal capacity of filler, while decreases with the increase of the thermal conductivity of filler. Therefore, the filler chose for engineering project shall be of small volumetric thermal capacity, low initial temperature and high thermal conductivity whenever possible.

The concave distortion of the freezing front under different working conditions at different times after filling can be calculated using the method proposed.

This study aims to carry out an investigation of design approaches that should be used for the design of unconventional, innovative transmission system for construction yards to privilege a smooth behaviour efficiency, and the use of innovative production techniques. Results are quite surprising, as with a proper method it is possible to demonstrate that a cycloidal drive with Wolfrom topology should be an interesting solution for the proposed application.

With a functional approach, also considering materials and specifications related to the investigated application, it is possible to demonstrate that possible optimal solutions should be quite different respect to the ones that can be suggested with a conventional approach. In particular for proposed applications constraints related to encumbrances, the choice of new material has led to the innovative unconventional choice of a Wolfrom cycloidal speed reducer.

Provided solution is innovative respect current state of the art for machine currently used in construction yards: in terms of adopted transmission layout; in terms of chosen materials, resulting in an innovative solution.

Current research has strong implications on the adoption of polimeric materials for the construction of reliable transmission for harsh industrial environment as the proposed case study (concrete mixer for construction yard).

Proposed transmission system is absolutely original and innovative respect current state of art also considering proposed materials and consequently production methods. This is an example of transmission designed to be built with polymeric materials by optimizing chosen topology respect to chosen material.

The purpose of this paper is to apply the conjugate gradient (CG) method, together with the adjoint operator (AO) to the pulsating heat pipe problem, including some quite interesting experimental results. The CG method, together with the AO, was able to estimate the unknown functions more efficiently than the other techniques presented in this paper. The estimation of local heat transfer coefficients, rather than the global ones, in pulsating heat pipes is a relatively new subject and presenting a robust, efficient and self-regularized inverse tool to estimate it, supported also by some experimental results, is the main purpose of this paper. To also increase the visibility and the general use of the paper to the heat transfer community, the authors include, as supplemental material, all numerical and experimental data used in this paper.

The approach was established on the solution of the inverse heat conduction problem in the wall by using as starting data the temperature measurements on the outer surface. The procedure is based on the CG method with AO. The here proposed approach was first verified adopting synthetic data and then it was validated with real cases regarding pulsating heat pipes.

An original fast methodology to estimate local convective heat flux is proposed. The procedure has been validated both numerically and experimentally. The procedure has been compared to other classical methods presenting some peculiar benefits.

The approach is suitable for pulsating heat pipes performance evaluation because these devices present a local heat flux distribution characterized by an important variation both in time and in space as a result of the complex flow patterns that are generated in this type of devices.

The procedure here proposed shows these benefits: it affords a general model of the heat conduction problem that is effortlessly customized for the particular case, it can be applied also to large datasets and it presents reduced computational expense.

This paper aims to introduce a non-invasive and convenient method to detect a life-threatening disease called aortic dissection. A Bayesian inference based on enhanced multi-sensors impedance cardiography (ICG) method has been applied to classify signals from healthy and sick patients.

A 3D numerical model consisting of simplified organ geometries is used to simulate the electrical impedance changes in the ICG-relevant domain of the human torso. The Bayesian probability theory is used for detecting an aortic dissection, which provides information about the probabilities for both cases, a dissected and a healthy aorta. Thus, the reliability and the uncertainty of the disease identification are found by this method and may indicate further diagnostic clarification.

The Bayesian classification shows that the enhanced multi-sensors ICG is more reliable in detecting aortic dissection than conventional ICG. Bayesian probability theory allows a rigorous quantification of all uncertainties to draw reliable conclusions for the medical treatment of aortic dissection.

This paper presents a non-invasive and reliable method based on a numerical simulation that could be beneficial for the medical management of aortic dissection patients. With this method, clinicians would be able to monitor the patient’s status and make better decisions in the treatment procedure of each patient.

The purpose of this paper is to present the freely available finite element simulation software Pyrit.

In a first step, the design principles and the objective of the software project are defined. Then, the software’s structure is established: The software is organized in packages for which an overview is given. The structure is based on the typical steps of a simulation workflow, i.e., problem definition, problem-solving and post-processing. State-of-the-art software engineering principles are applied to ensure a high code quality at all times. Finally, the modeling and simulation workflow of Pyrit is demonstrated by three examples.

Pyrit is a field simulation software based on the finite element method written in Python to solve coupled systems of partial differential equations. It is designed as a modular software that is easily modifiable and extendable. The framework can, therefore, be adapted to various activities, i.e., research, education and industry collaboration.

The focus of Pyrit are static and quasistatic electromagnetic problems as well as (coupled) heat conduction problems. It allows for both time domain and frequency domain simulations.

In research, problem-specific modifications and direct access to the source code of simulation tools are essential. With Pyrit, the authors present a computationally efficient and platform-independent simulation software for various electromagnetic and thermal field problems.

The purpose of this paper is to reduce the artifacts in fast Bayesian reconstruction images in electrical tomography. This is in particular important with respect to object detection in electrical tomography applications.

The authors suggest to apply the Box-Cox transformation in Bayesian linear minimum mean square error (BMMSE) reconstruction to better accommodate the non-linear relation between the capacitance matrix and the permittivity distribution. The authors compare the results of the original algorithm with the modified algorithm and with the ground truth in both, simulation and experiments.

The results show a reduction of 50 percent of the mean square error caused by artifacts in low permittivity regions. Furthermore, the algorithm does not increase the computational complexity significantly such that the hard real time constraints can still be met. The authors demonstrate that the algorithm also works with limited observations angles. This allows for object detection in real time, e.g., in robot collision avoidance.

This paper shows that the extension of BMMSE by applying the Box-Cox transformation leads to a significant improvement of the quality of the reconstruction image while hard real time constraints are still met.

The paper aims to promote the development of intelligent materials and the 4D printing technology by introducing recent advances and applications of additive layered manufacturing (ALM) technology of intelligent materials and the development of the 4D printing technology. Also, an arm-type ALM technology of shape memory polymer (SMP) with thermosetting polyurethane is briefly introduced.

This paper begins with an overview of the development and applications of intelligent materials around the world and the 4D printing technology. Then, the authors provide a brief outline of their research on arm-type ALM technology of SMP with thermosetting polyurethane.

The paper provides the recent developments and applications of intelligent materials and 4D printing technology. Then, it is suggested that intelligent materials mixed with different functional materials will be developed, and these types of materials will be more suitable for 4D printing.

This paper overviews the current developments and applications of intelligent materials and its use in 4D printing technology, and briefly states the authors’ research on arm-type ALM technology of SMP with thermosetting polyurethane.

The purpose of this study is to develop a cylindrical capacitive sensor that has the advantages of high resolution, small size and designability and can be easily installed on lubricant pipeline to monitor lubricant oil debris.

A theoretical model of the cylindrical capacitive sensor is presented to analyze several parameters’ effectiveness on the performance of sensor. Numerical simulations are then conducted to determine the optimal parameters for preliminary experiments. Experiments are finally carried out to demonstrate the detectability of developed capacitive sensors.

It is clear from experimental results that the developed capacitive sensor can monitor the debris in lubricant oil well, and the capacitance values increase almost linearly when the number and size of debris increase.

There is lot of further work to do to apply the presented method into the application. Especially, it is necessary to consider several factors’ influence on monitoring results. These factors include the flow rate of the lubricant oil, the temperature, the debris distribution and the vibration. Moreover, future work should consider the influence of the oil degradation to the capacitance change and other contaminations (e.g. water and dust).

This work conducts a feasibility study on application of capacitive sensing principle for detecting debris in aero engine lubricant oil.

The novelty of the presented capacitance sensor can be summarized into two aspects. One is that the sensor structure is simple and characterized by two coaxial cylinders as electrodes, while conventional capacitive sensors are composed of two parallel plates as electrodes. The other is that sensing mechanism and physical model of the presented sensor is verified and validated by the simulation and experiment.