A system dynamic model for assessing the level of BIM implementation in construction phase: a China case study

PurposeBuilding information modeling (BIM) is recognized as one of the technologies to upgrade the informatization level of the architecture engineering and construction (AEC) industry. However, the level of BIM implementation in the construction phase lags behind other phases of the project. Assessing the level of BIM implementation in the construction phase from a system dynamics (SD) perspective can comprehensively understand the interrelationship of factors in the BIM implementation system, thereby developing effective strategies to enhance BIM implementation during the construction phase. This study aims to develop a model to investigate the level of BIM implementation in the construction phase.Design/methodology/approachAn SD model which covered technical subsystem, organizational subsystem, economic subsystem and environmental subsystem was developed based on questionnaire survey data and literature review. Data from China were used for model validation and simulation.FindingsThe simulation results highlight that, in China, from 2021 to 2035, the ratio of BIM implementation in the construction phase will rise from 48.8% to 83.8%, BIM model quality will be improved from 27.6% to 77.2%. The values for variables “BIM platform”, “organizational structure of BIM” and “workflow of BIM” at 2035 will reach 65.6%, 72.9% and 72.8%, respectively. And the total benefits will reach 336.5 billion yuan in 2035. Furthermore, the findings reveal five factors to effectively promote the level of BIM implementation in the construction phase, including: policy support, number of BIM standards, owners demand for BIM, investment in BIM and strategic support for BIM.Originality/valueThis study provides beneficial insights to effectively enhance the implementation level of BIM in the construction phase. Meanwhile, the model developed in this study can be used to dynamically and quantitatively assess the changes in the level of BIM implementation caused by a measure.

Impact of visits on the microclimates of caves, Experimental evidence from Škocjan Caves

Tourism activities in caves can result in changes in the microclimates of caves. The natural microclimate in closed caves is constant due to the balance between cave air and cave walls, while in open caves exchanges with outside air influence the microclimate. Visits to caves, especially in closed smaller caves, can thus endanger the natural balance if the microclimate does not return to natural conditions quickly enough.Continuous monitoring of the temperature and concentration of carbon dioxide in Škocjan Caves enables the assessment of the impact of visits. For this purpose, we used data measured in the relatively closed Silent Cave, at the locations named Calvary (Kalvarija), Tent (Šotor), and Passage (Prehod) in 2016, and in the wide open Murmuring Cave, at the locations named Bridge (Most) and Rimstone Pools (Ponvice), in 2013. The outdoor air temperature, as measured at the Škocjan meteorological station on the surface plateau, was considered in both cases. Along the tourist part of Škocjan Caves, the most closed part of the cave in Silent Cave is the location at Calvary, when the entrance doors through an artificially dug tunnel are closed. During the visits, the microclimate is subjected to draughts through open doors and to anthropogenic emissions. The data suggest that the influence of draughts predominates over direct anthropogenic emissions. In winter or on cold days air flows upwards and through the tunnel out of the cave, whereas in summer or on warm days it flows downwards. In such cases, the CO2 concentration decreases markedly due to the downwards chimney effect as the concentration in the outside air is much lower than in the cave. The data show that the temperature overnight and towards morning always returns to its natural value even in this rather small location in the cave. The changes in CO2 concentration persist for a longer period, until the time of the first visit the next morning, when it is again perturbed by a new visit. The data on time courses support the theoretically estimated characteristic of the exponential decline of disturbances backward towards natural conditions, depending on the size of a cave and on the efficiency of exchanges with its walls. For tem­perature, this characteristic time tT is about three to six hours at the Calvary site. The return of CO2 to natural conditions tCO2 is longer and its estimate less reliable than the one for temperature. In the wide-open and large Murmuring Cave, the impact of visits is negligible throughout the year. In this part of the cave we can observe the influence of external daily and annual changes, the amplitudes of which get smaller, and their phase lags bigger, deeper in the cave.

Phase-locked transcranial electrical brain stimulation for tremor suppression in dystonic tremor syndromes

Background: Tremor is a common and burdensome symptom in patients with dystonia, which is clinically heterogeneous and often resistant to treatment. The pathophysiology is suggested to involve abnormal activity in the cerebellum and motor cortex, but the causal role of these brain regions remains to be established. Transcranial alternating current stimulaton (TACS) can suppress rhytmic cerebral activity in other tremor disorders when phase-locked to the ongoing arm tremor, but the effect on dystonic tremor syndromes is unknown. Objective/Hypothesis: We aimed to establish the causal role of the cerebellum and motor cortex in dystonic tremor syndromes, and explore the therapeutic efficacy of phase-locked TACS. Methods: We applied phase-locked TACS over the ipsilateral cerebellum (N=14) and contralateral motor cortex (N=17) in dystonic tremor syndrome patients, while patients assumed a tremor-evoking posture. We measured tremor power using accelerometery during 30s stimulation periods at 10 different phase-lags (36-degrees increments) between tremor and TACS for each target. Post-hoc, TACS-effects were related to a key clinical feature: the jerkiness (regularity) of tremor. Results: Cerebellar TACS modulated tremor amplitude in a phase-dependent manner, such that tremor amplitude was suppressed or enhanced at opposite sides of the phase-cycle. This effect was specific for patients with non-jerky (sinusoidal) tremor (n=10), but absent in patients with jerky (irregular) tremor (n=4). Phase-locked stimulation over the motor cortex did not modulate tremor amplitude. Conclusions: This study indicates that the cerebellum plays a causal role in the generation of (non-jerky) dystonic tremor syndrome. Our findings suggest pathophysiologic heterogeneity between patients with dystonic tremor syndrome, which mirrors clinical variability.

Finite Element Analysis of Thermal-Diffusions Problem for Unbounded Elastic Medium Containing Spherical Cavity under DPL Model

In this work, the thermo-diffusions interaction in an unbounded material with spherical cavities in the context dual phase lag model is investigated. The finite element technique has been used to solve the problem. The bounding surface of the inner hole is loaded thermally by external heat flux and is traction-free. The delay times caused in the microstructural interactions, the requirement for thermal physics to take account of hyperbolic effects within the medium, and the phase lags of chemical potential and diffusing mass flux vector are interpreted. A comparison is made in the case of the presence and the absence of mass diffusions between coupled, Lord-Shulman and dual phase lag theories. The numerical results for the displacement, concentration, temperature, chemical potential and stress are presented numerically and graphically.

Influence of Initial Stress and Variable Thermal Conductivity on a Fiber-Reinforced Magneto-Thermoelastic Solid with Micro-Temperatures by Multi-Phase-Lags Model

This paper presents the theory of multi-phase-lags thermoelasticity that was used to study the wave propagation on a fiber-reinforced thermoelastic medium with micro-temperatures. The medium was considered to be homogeneous, isotropic and thermal conductivity as a linear function of thermodynamic temperature. The Fourier transform and Laplace transform are employed to solve the governing equations and obtained the solution of the physical quantities. The graphical illustrations of the impact that initial stress, variable thermal conductivity, magnetic field, and the phase-lags have on the field functions are presented. The variable thermal conductivity, initial stress, and magnetic field have a good impact in all the physical quantities.

The Time-Robustness Analysis of Individual Identification Based on Resting-State EEG

An ongoing interest towards identification based on biosignals, such as electroencephalogram (EEG), magnetic resonance imaging (MRI), is growing in the past decades. Previous studies indicated that the inherent information about brain activity may be used to identify individual during resting-state of eyes open (REO) and eyes closed (REC). Electroencephalographic (EEG) records the data from the scalp, and it is believed that the noisy EEG signals can influence the accuracies of one experiment causing unreliable results. Therefore, the stability and time-robustness of inter-individual features can be investigated for the purpose of individual identification. In this work, we conducted three experiments with the time interval of at least 2 weeks, and used different types of measures (Power Spectral Density, Cross Spectrum, Channel Coherence and Phase Lags) to extract the individual features. The Pearson Correlation Coefficient (PCC) is calculated to measure the level of linear correlation for intra-individual, and Support Vector Machine (SVM) is used to obtain the related classification accuracy. Results show that the classification accuracies of four features were 85–100% for intra-experiment dataset, and were 80–100% for fusion experiments dataset. For inter-experiments classification of REO features, the optimized frequency range is 13–40 Hz for three features, Power Spectral Density, Channel Coherence and Cross Spectrum. For inter-experiments classification of REC, the optimized frequency range is 8–40 Hz for three features, Power Spectral Density, Channel Coherence and Cross Spectrum. The classification results of Phase Lags are much lower than the other three features. These results show the time-robustness of EEG, which can further use for individual identification system.