70 research outputs found
The Evaluation of the Parallel Bond’s Properties in DEM Modeling of Soils
In this study we conducted the sensitivity analysis of the parallel bond used in the discrete element method (DEM, 3D) based soil model. We researched those parameters which simulate real soil physique attributes. In our investigations we modeled the inhomogeneity by the differentiation in particle size, the soil moisture condition by the parallel bond’s radius R, the cracking tendency by the bonding stiffnesses kn, ks and the air phase by the pore volume of the particle block. We based the validation of the simulation on the results of the simple direct shear box test which were performed in laboratory environment. We analyzed the effect of micromechanical and macromechanical parameters, used in the modeled particle block, with the use of direct shear box and triaxial shear simulations. After the recalculation of micromechanical parameters (EC, ĒC, γ) we analyzed the effect of the adjustable macromechanical parameters (kn, ks ,λ, kn, ks, σC, τC) used in the block with triaxial shear simulation. Based on the comparison of the shear simulations’ results the accuracy of the recalculation of the parallel bond’s micro-macro parameters is proved by the good correlation of the Coulomb failure criterion lines (σ-τ)
Emergence of non-Fourier hierarchies
The non-Fourier heat conduction phenomenon on room temperature is analyzed
from various aspects. The first one shows its experimental side, in what form
it occurs and how we treated it. It is demonstrated that the Guyer-Krumhansl
equation can be the next appropriate extension of Fourier's law for room
temperature phenomena in modeling of heterogeneous materials. The second
approach provides an interpretation of generalized heat conduction equations
using a simple thermomechanical background. Here, Fourier heat conduction is
coupled to elasticity via thermal expansion, resulting in a particular
generalized heat equation for the temperature field. Both of the aforementioned
approaches show the size dependency of non-Fourier heat conduction. Finally, a
third approach is presented, called pseudo-temperature modeling. It is shown
that non-Fourier temperature history can be produced by mixing different
solutions of Fourier's law. That kind of explanation indicates the
interpretation of underlying heat conduction mechanics behind non-Fourier
phenomena
Method for Evaluating a Building Information Model
This paper discusses a method for evaluating building information models from the point of view of different disciplines. The ultimate goal is to provide a methodology for decision-makers on an Architecture, Engineering, and Construction (AEC) project, where they can follow the status and performance of the BIM model at each project milestone, from different aspects, in a comparable manner. This methodology requires an evaluation method that aggregates data input by the designers. Interpreting BIM models is complex – multi-dimensional, in fact, considering the meta-information added to it. Therefore, the aggregation process is not trivial and may differ in several cases. We build up multi-dimensional diagrams to chart the possible factors of the evaluation, besides introducing aggregation rules and visualizations. For such a method, it was essential to analyze BIM ontologies in order to establish a precise definition for each concept: milestones, building parts, indicator metrics, etc. We describe an example project workflow where our method works in theory, while we give a practical solution how to add the evaluation data to the BIM model with CAAD software
Building Information Dashboard as Decision Support during Design Phase
This paper discusses the Building Information Dashboard, a data representation
method which provides a solid basis for decision-makers to make optimal
decisions during the design phase of an Architecture, Engineering, and
Construction project. We describe an example project workflow where the
dashboard is integrated. We sum up the evaluation method, which is the basis of
the dashboard, and we research what type of visualization method is best suited to
representing this type of data. To this end, an evaluation matrix was created to
compare the alternative charts. We take into account what kind of information
such a dashboard should represent and what kind of features it should have. We
suggest layouts for different use cases - both for professional and
non-professional decision-makers, as well as for discipline designers
Coupling traffic originated urban air pollution estimation with an atmospheric chemistry model
Due to increasing issues of air pollution in urban areas continuous research is being conducted to upgrade models, which can predict the distribution of pollutants and thus enable timely interventions to mitigate their negative effects. To support these efforts, traffic data from an integrated transport model was used to drive the COPERT traffic emission model and the WRF-Chem atmospheric chemistry model. With reliable macroscopic traffic data from the Budapest region, traffic state estimations were calculated for every fifteen minutes of the day using dynamic assignment with predefined and time-varying static demand matrices. Then the COPERT vehicular emission model of average speeds was applied to provide the emission factors, so that the macroscopic emissions for the traffic network could be calculated. As a next step the WRF-Chem online coupled weather and atmospheric chemistry model was adapted to estimate atmospheric dispersion of pollutants (CO, NOx, O3). The coupled models are presented in a 2-day case study with qualitative comparison of obtained results with measurements. As a result, it can be stated that combining macroscopic road traffic modeling with atmospheric models can enhance the estimation efficiency of urban air pollution
Laborkészülékek kreatin-kináz mérési eredményeinek összehasonlítása válogatott labdarúgók esetében = Creatine Kinase Measurement Comparison of Two Laboratory Analysers in National Team Soccer Players
Medium-Term Results of Staged Laparoscopic Traction Orchiopexy for Intra-abdominal Testes : A Multicenter Analysis
Staged laparoscopic traction orchiopexy (SLTO) is a novel technique for the intra-abdominal testis (IAT) based on elongation of the testicular vessels without separating them. This multicenter study evaluated the medium-term results of this technique.Data of SLTO performed in three pediatric surgical centers between 2013 and 2020 were analyzed retrospectively. In 2021, physical and Doppler ultrasound examinations were performed to determine the position and viability of testes. Success was defined as an intra-scrotal testicle without atrophy.SLTO was performed on 48 cases (55 testes, 7 bilateral). Mean age at first stage was 2.9 (0.8-12.6) years. High intra-abdominal testes were found in 16.4% and in 60% morphological abnormalities were observed. To fix the testes to the abdominal wall monofilament suture was used in 67.3%, braided in 29.1%. Mean time between the two stages was 16.4 weeks; three testes required redo traction. Perioperative complications occurred in 21 patients (38.2%) including insufficient fixation (11), testicular atrophy (4), wound complications (4), adhesion of the spermatic cords (1) and hydrocele (1). In case of insufficient fixation monofilament sutures were used in 90.9%. In 2021 38 patients (43 testes) had physical and 36 patients (41 testes) had ultrasound examinations. Mean follow-up was 2.7 (0.34-7.9) years. Altogether five atrophies were identified, and three testicular ascents (7.0%) occurred. The overall success rate was 82.2%.SLTO may be a feasible alternative to conventional treatments of IATs. Additionally, braided suture seems to be a better option to fix the testicle to the abdominal wall.LEVEL IV
Real-world effectiveness of IDegLira compared with intensified conventional insulin therapy in adults with type 2 diabetes: a retrospective cohort study
Background:
IDegLira is a fixed-ratio combination of insulin degludec and liraglutide with proven efficacy against simpler regimens and non-inferiority against basal-bolus insulin therapy. However, the evaluation of its real-world effectiveness is hindered by technical issues and requires further exploration. Thus we aimed to compare effectiveness of insulin degludec/liraglutide (IDegLira) versus intensified conventional insulin therapy (ICT) for type 2 diabetes in a real-world setting.
Methods:
This retrospective cohort study from an outpatient clinic in Hungary included people who initiated IDegLira due to inadequate glycaemic control (HbA1c > 7.0% [53.0 mmol/mol]) with oral and/or injectable antidiabetic drugs. Data were compared with a historical cohort who initiated ICT. Outcomes included HbA1c, body weight, and hypoglycaemia differences over 18 months of follow-up.
Results:
Data were included from 227 and 72 people who initiated IDegLira and ICT, respectively. Estimated mean difference (MD) in HbA1c at 18 months favoured IDegLira versus ICT (MD 0.60, 95% CI 0.88–0.32 [MD 6.6 mmol/mol, 95% CI 9.6–3.5]). More people reached target HbA1c ≤7.0% (53.0 mmol/mol) with IDegLira than ICT (odds ratio 3.36, 95% CI 1.52–7.42). IDegLira treatment was associated with weight loss compared with gain for ICT (MD 6.7 kg, 95% CI 5.0–8.5). The hazard ratio for hypoglycaemia comparing IDegLira with ICT was 0.18 (95% CI 0.08–0.49).
Conclusions:
Treatment with IDegLira over 18 months resulted in greater HbA1c reductions, weight loss versus gain, and a lower rate of hypoglycaemia versus ICT in people with type 2 diabetes
Road abnormality detection using piezoresistive force sensors and adaptive signal models
Intelligent tires can be used for a wide array of applications ranging from
tire pressure monitoring to analyzing tire/road interactions, wheel loading,
and tread wear monitoring. In this article, we develop a measurement system for
intelligent tires equipped with a 3-D piezoresistive force sensor. The output
of the sensor is segmented into tire revolution cycles, which are then
represented by a transformation relying on adaptive Hermite functions. The
underlying idea behind this step is to extract relevant features which capture
tire dynamics. Then we evaluate the proposed measurement system in a potential
vehicle application, that is, abnormal road surface detection. We deal with the
corresponding binary classification problem by developing both low-complexity
analytical and data-driven machine learning algorithms, which are tested on
real-world measurement data. Our experiments showed that the proposed methods
are able to detect abnormalities on the road surface with a mean accuracy of
over 97%
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