SELF-ADAPTING FAÇADE SYSTEMS: EXPERIMENTATION REGARDING THE EXPLOITATION OF THERMAL DILATION

2020 ◽  
Vol 15 (4) ◽  
pp. 67-90
Author(s):  
Livio Petriccione ◽  
Fabio Fulchir ◽  
Francesco Chinellato
Keyword(s):  
Environmental Temperature ◽  
State Of The Art ◽  
The Self ◽  
External Energy ◽  
Building Envelopes ◽  
Orientation System ◽  
Thermal Dilation ◽  
Theoretical Results ◽  
Productive Development ◽  
Critical Aspects

ABSTRACT An original and innovative solar device orientation system is illustrated, together with the results of research and experimentation. The system proposed uses only the force generated by natural thermal dilation, without the help of motors, computerized devices or external energy sources, thus overcoming some critical aspects of the self-adaptive type of building envelopes used up until now. In the course of the research a mathematical model was developed to correlate the variation of the environmental temperature with the consequent expansion of the dilating elements of the system. The results of the tests carried out confirmed an excellent correspondence between the theoretical results and the experimentation. The state of the art of the research has all its theoretical aspects defined and some partial prototypes created. It is planned to build some complete prototypes with the realistic prospect of productive development.

scholarly journals Critical Aspects of Person Counting and Density Estimation

2021 ◽  
Vol 7 (2) ◽  
pp. 21
Author(s):  
Roland Perko ◽  
Manfred Klopschitz ◽  
Alexander Almer ◽  
Peter M. Roth
Keyword(s):  
Density Estimation ◽  
Network Architecture ◽  
Reference Data ◽  
State Of The Art ◽  
Limit State ◽  
Ground Truth ◽  
Data Sets ◽  
Ground Truth Generation ◽  
Baseline Approach ◽  
Critical Aspects

Many scientific studies deal with person counting and density estimation from single images. Recently, convolutional neural networks (CNNs) have been applied for these tasks. Even though often better results are reported, it is often not clear where the improvements are resulting from, and if the proposed approaches would generalize. Thus, the main goal of this paper was to identify the critical aspects of these tasks and to show how these limit state-of-the-art approaches. Based on these findings, we show how to mitigate these limitations. To this end, we implemented a CNN-based baseline approach, which we extended to deal with identified problems. These include the discovery of bias in the reference data sets, ambiguity in ground truth generation, and mismatching of evaluation metrics w.r.t. the training loss function. The experimental results show that our modifications allow for significantly outperforming the baseline in terms of the accuracy of person counts and density estimation. In this way, we get a deeper understanding of CNN-based person density estimation beyond the network architecture. Furthermore, our insights would allow to advance the field of person density estimation in general by highlighting current limitations in the evaluation protocols.

Study of the Effect of Hole Clearance and Thread Fit on the Self-Loosening of Threaded Fasteners

2006 ◽  
Vol 129 (6) ◽  
pp. 586-594 ◽  
Author(s):  
Sayed A. Nassar ◽  
Basil A. Housari
Keyword(s):  
Analytical Investigation ◽  
The Self ◽  
Time Data ◽  
Experimental Procedure ◽  
Test Setup ◽  
Threaded Fasteners ◽  
Service Load ◽  
Real Time Data ◽  
Theoretical Results ◽  
Simplified Mathematical Model

This study provides an experimental and theoretical investigation of the effect of hole clearance and thread fit on the self-loosening of tightened threaded fasteners that are subjected to a cyclic transverse service load. An experimental procedure and test setup are developed in order to collect real-time data on the rate of clamp load loss per cycle as well as the loosening rotation of the bolt head. Three levels of hole clearance are investigated; namely, 3%, 6%, and 10% of the bolt nominal diameter. For the commonly used 2A thread fit for a selected bolt size, three classes of the nut thread fit are considered; namely, 1B, 2B, and 3B. A simplified mathematical model is used for the analytical investigation of the effect of the hole clearance and thread fit on threaded fasteners self-loosening. The experimental and theoretical results are presented and discussed.

scholarly journals Effects of Admixtures on the Self Compacting Concrete State of the Art Report

2020 ◽  
Vol 1006 ◽  
pp. 012038
Author(s):  
S Christopher Gnanaraj ◽  
Ramesh Babu Chokkalingam ◽  
G LiziaThankam
Keyword(s):  
State Of The Art ◽  
The Self ◽  
Self Compacting Concrete

scholarly journals Large column densities and [12CII] 158 μm self-absorption in Orion B

2012 ◽  
Vol 8 (S292) ◽  
pp. 57-58
Author(s):  
J. Stutzki ◽  
U. U. Graf ◽  
R. Simon ◽  
S. W. J. Colgan ◽  
X. Guan ◽  
...  
Keyword(s):  
Present State ◽  
Molecular Cloud ◽  
Preliminary Analysis ◽  
State Of The Art ◽  
The Self ◽  
Absorption Component ◽  
Warm Core ◽  
High Column

AbstractWe present a preliminary analysis of the self-absorbed [CII]-spectra observed with SOFIA/GREAT towards NGC 2024. Together with the detected [13CII] hyperfine satellites, the observed spectra require surprisingly high column densities of C+, both in the warm core and the foreground absorption component. Such high column densities are a challenge to explain with present state-of-the-art PDR models of the UV/molecular cloud interaction.

Optimization Design of Self-Balacing Torsion Bar Diameter

2011 ◽  
Vol 308-310 ◽  
pp. 2486-2489
Author(s):  
Zhi Qi Huang
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Ant Colony Algorithm ◽  
The Self ◽  
Ant Colony ◽  
New Method ◽  
C Language ◽  
Torsion Bar ◽  
Bar Diameter ◽  
Theoretical Results

The thesis builds the optimization model for the self-balacing torsion bar, On the basis of the Ant Colony Algorithm, designs the Ant Colony Algorithm procedure using C Language and optimizes torsion bar diameter. Results show the Ant Colony Algorithm is feasible and provides a new method choosing torsion bar diameter. The max difference value is 1.12% between optimizing results and theoretical results.

scholarly journals Self-Attention ConvLSTM for Spatiotemporal Prediction

2020 ◽  
Vol 34 (07) ◽  
pp. 11531-11538
Author(s):  
Zhihui Lin ◽  
Maomao Li ◽  
Zhuobin Zheng ◽  
Yangyang Cheng ◽  
Chun Yuan
Keyword(s):  
Long Range ◽  
State Of The Art ◽  
The Self ◽  
Time Step ◽  
Traffic Flow Prediction ◽  
Spatial Features ◽  
Gating Mechanism ◽  
Spatial Dependencies ◽  
Previous State ◽  
Global And Local

Spatiotemporal prediction is challenging due to the complex dynamic motion and appearance changes. Existing work concentrates on embedding additional cells into the standard ConvLSTM to memorize spatial appearances during the prediction. These models always rely on the convolution layers to capture the spatial dependence, which are local and inefficient. However, long-range spatial dependencies are significant for spatial applications. To extract spatial features with both global and local dependencies, we introduce the self-attention mechanism into ConvLSTM. Specifically, a novel self-attention memory (SAM) is proposed to memorize features with long-range dependencies in terms of spatial and temporal domains. Based on the self-attention, SAM can produce features by aggregating features across all positions of both the input itself and memory features with pair-wise similarity scores. Moreover, the additional memory is updated by a gating mechanism on aggregated features and an established highway with the memory of the previous time step. Therefore, through SAM, we can extract features with long-range spatiotemporal dependencies. Furthermore, we embed the SAM into a standard ConvLSTM to construct a self-attention ConvLSTM (SA-ConvLSTM) for the spatiotemporal prediction. In experiments, we apply the SA-ConvLSTM to perform frame prediction on the MovingMNIST and KTH datasets and traffic flow prediction on the TexiBJ dataset. Our SA-ConvLSTM achieves state-of-the-art results on both datasets with fewer parameters and higher time efficiency than previous state-of-the-art method.

scholarly journals Efficient Management of Road Intersections for Automated Vehicles—The FRFP System Applied to the Various Types of Intersections and Roundabouts

2019 ◽  
Vol 10 (1) ◽  
pp. 316 ◽  
Author(s):  
Basilio Filocamo ◽  
Javier Alonso Ruiz ◽  
Miguel Angel Sotelo
Keyword(s):  
Travel Time ◽  
State Of The Art ◽  
Automatic Driving ◽  
Road Congestion ◽  
Efficient Management ◽  
Different Types ◽  
Road Intersections ◽  
The Right ◽  
New System ◽  
Critical Aspects

In the last decade, automatic driving systems for vehicles circulating on public roads have become increasingly closer to reality. There is always a strong interest in this topic among research centers and car manufacturers. One of the most critical aspects is the management of intersections, i.e., who will have to go first and in what ways? This is the question we want to answer through this research. Clearly, the goal is to manage the intersection safely, making it possible to reduce road congestion, travel time, emissions, and fuel consumption as much as possible. The research is conducted by comparing a new management system with the systems already known in the state of the art for different types of intersections. The new system proposed by us is called FRFP (first to reach the end of the intersection first to pass). In particular, vehicles will increase or decrease their speed in collaboration with each other by making the right decision. The vehicle that can potentially reach the intersection exit first.

scholarly journals An Equivalent Circuit Analysis and Suspension Characteristics of AC Magnetic Suspension Using Magnetic Resonant Coupling

Actuators ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 52
Author(s):  
Arifur Rahman ◽  
Takeshi Mizuno ◽  
Masaya Takasaki ◽  
Yuji Ishino
Keyword(s):  
Electrical Circuit ◽  
Magnetic Suspension ◽  
The Self ◽  
Wireless Power ◽  
Equivalent Circuit Analysis ◽  
Resonant Coupling ◽  
Secondary Current ◽  
Experimental Apparatus ◽  
Primary Current ◽  
Theoretical Results

The fundamental characteristics and performances of alternating current (AC) magnetic suspension using magnetic resonant coupling are studied analytically and experimentally. Nowadays, wireless power transfer to the suspended object is required during non-contact suspension in some applications. Therefore, magnetic resonant coupling has been introduced for AC magnetic suspension to achieve self-stabilizing magnetic suspension and energy transfer to the floator simultaneously. The effect of circuit parameters for developing an experimental apparatus and performances are predicted from the solution of the equivalent circuits analytically. First, an equivalent magnetic circuit is derived and analyzed to characterize the self-inductance and mutual inductance with the gap. Second, an equivalent electrical circuit is analyzed to derive the current and force equations including magnetic parameters of the circuit. The derivation of these equations is numerically solved to study the characteristics of the primary current, the secondary current, and the force with respect to the gap and the applied frequency. The comparison between theoretical and experimental results is depicted, and the reason for differences is explained. The experimental and theoretical results show that positive stiffness is possible, which is essential for achieving self-stabilization. The self-stability is confirmed by the frequency response of the suspension system to disturbance experimentally.

scholarly journals Self-Propulsion Enhances Polymerization

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 251 ◽  
Author(s):  
Maximino Aldana ◽  
Miguel Fuentes-Cabrera ◽  
Martín Zumaya
Keyword(s):  
Nucleic Acids ◽  
Self Assembly ◽  
The Self ◽  
Biological Molecules ◽  
Bonding Energy ◽  
Self Organization ◽  
External Energy ◽  
Present Evidence ◽  
Spontaneous Process ◽  
Propulsion Force

Self-assembly is a spontaneous process through which macroscopic structures are formed from basic microscopic constituents (e.g., molecules or colloids). By contrast, the formation of large biological molecules inside the cell (such as proteins or nucleic acids) is a process more akin to self-organization than to self-assembly, as it requires a constant supply of external energy. Recent studies have tried to merge self-assembly with self-organization by analyzing the assembly of self-propelled (or active) colloid-like particles whose motion is driven by a permanent source of energy. Here we present evidence that points to the fact that self-propulsion considerably enhances the assembly of polymers: self-propelled molecules are found to assemble faster into polymer-like structures than non self-propelled ones. The average polymer length increases towards a maximum as the self-propulsion force increases. Beyond this maximum, the average polymer length decreases due to the competition between bonding energy and disruptive forces that result from collisions. The assembly of active molecules might have promoted the formation of large pre-biotic polymers that could be the precursors of the informational polymers we observe nowadays.

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