Acta Technica Jaurinensis

Effect of Reprocessing on the Crystallization of Different Polyesters

Zoubeida Taha Taha, Andrea Ádámné Major, Ferenc Ronkay — Wed, 27 Dec 2023 00:00:00 +0000

The changes in crystallization characteristics of four polyesters were investigated during multiple processing. Two of these were petroleum-based materials: poly (ethylene terephthalate) (PET) and poly (butylene terephthalate) (PBT), and two were bio-based materials: poly (lactic acid) (PLA) and poly (butylene succinate) (PBS). We found that during non-isothermal crystallization the different type of polyesters shown different behaviour: the PET and PLA materials were more sensitive to the cooling rate than the PBT and PBS. Interestingly, at low cooling rates, the number of reprocessing steps had no significant effect on the crystallinity of PBT and PBS, but reduced it for PET, but increased it for PBT.

Use of Zero-crossings Segmentation for Track Quality Assessment

Abdaljbbar Dawod, György Terdik — Sat, 17 Feb 2024 00:00:00 +0000

This study concerns track quality assessment of standard-gauge railways in the context of the Hungarian railway system. Data gathered by multipurpose track recording vehicles matched the EN 13,848 requirements. Track Quality Index (TQI) measurement systems (The Federal Railroad Administration (FRA), the Netherlands’, and the Chinese TQI) are considered where three types of predetermined segment techniques: separate, moving, and Zero-crossings segmentation are employed. The importance of track segmentation in quality assessment, which affects maintenance planning, is shown by key findings. For heterogeneous data, the TQIs might be deceptive, highlighting the need for alternatives. The robustness of the Zero-crossings method makes it possible to analyze deterioration factors in great detail and in some efficient way. Longer analytical segments and smoothing of the data improved precision. Based on empirical data, we advise considering a Zero-crossings strategy for precise and efficient track-quality evaluations. With the help of this study, track quality can be better evaluated for train systems.

The development of a stitch-based strain sensor for woven lashing straps

Norman Lesser, Bernd Sadlowsky — Mon, 19 Feb 2024 00:00:00 +0000

In this paper the development of a stitch-based strain sensor for lashing straps is discussed. A variety of Three different commercial woven narrow fabric straps were embroidered with conductive yarns in two designed patterns to enable belt tension measurement and monitoring. The applications were tested in a cyclic elongation test and a creep elongation procedure to investigate the strain sensitivity and the influences of the narrow fabric’s properties, the stitch design, and the conductive yarn properties. It was found that the developed applications provided a good strain sensing ability but lack in cyclic recovery abilities.

Soft computing implementations for evaluating Los Angeles abrasion value of rock aggregates from Kütahya, Turkey

Ekin Köken — Wed, 28 Feb 2024 00:00:00 +0000

The Los Angeles abrasion value (LAAV) of rocks is a critical mechanical aggregate property for designing road infrastructures and concrete quality. However, the determination of this critical aggregate property is labour-intensive and time-consuming and thus, in the literature, there are many predictive models to estimate the LAAV for different rock types. However, most of them are based on classical regression analyses, limiting their broader usage. In this study, several soft computing analyses are performed to develop robust predictive models for the evaluation of LAAV of rocks in the Ilıca region (Kütahya – Turkey). The main motivation for implementing soft computing analyses is that precise predictive models might be useful when exploring suitable rock types that are manufactured in crushing–screening plants. For this purpose, a comprehensive laboratory schedule was established to obtain some inputs for the evaluation of LAAV. As a result of the soft computing analyses, four robust predictive models are developed based on artificial neural networks (ANN), multiple adaptive regression spline (MARS), adaptive neuro-fuzzy inference system (ANFIS) and gene expression programming (GEP) methodologies. The performance of the proposed models is investigated by some statistical indicators such as R² and RMSE values and scatter plots. As a result, the ANFIS-based predictive model turns out to be the best alternative to estimate the LAAV of the investigated rocks.

Influence of different factors on the value of the rail wear rate

Yurii Makarov, Roman Zaleskyi, Mykola Mykhalichenko — Wed, 28 Feb 2024 00:00:00 +0000

The article deals with the study of the influence of train operating modes on the uphill and downhill sections with radii less than 450 m, as well as the influence of railway superstructure design in curved sections on the wear rate of rolling stock wheel flanges and rails. The aim of the research is to reduce the wear that occurs between the wheel flanges of the rolling stock and the rails. Rail joints have been found to be the main shock source in the dynamic interaction between the railway and the rolling stock. There is unstable motion within the transition curves and at the joints of the curved rail on the curved track sections. This is accompanied by abrupt lateral rail wear in the joint area between the trailing and facing rails in the direction of train movement. It has been found that reducing the weight of the trains leads to a reduction in intensive lateral rail wear on curved track sections and can reach the following percentages: in curves with a radius of up to 300 m: up to 33% uphill, up to 55% downhill; in curves with a radius of 300 m to 450 m: up to 32.9% uphill, up to 26.3% downhill; in curves with a radius of 450 m: up to 3.2% uphill, up to 17.6% downhill. On the uphill and downhill sections, reducing the height and adjusting to the speed limit in percentage gives a positive result from 4.7% to 53.59%.