Analyses of High Grade Strength Steel Bars in the Design of a Five-Storey Reinforced Concrete Structure with Comparison of Energy Consumption and CO2 Emission

2012 ◽  
Vol 511 ◽  
pp. 64-69
Author(s):  
Pei Zhang ◽  
Han Zhu ◽  
Apostolos Fafitis
Keyword(s):  
Energy Consumption ◽  
Reinforced Concrete ◽  
Structural Design ◽  
Energy Cost ◽  
High Energy ◽  
Maximum Energy ◽  
Reinforced Concrete Structure ◽  
Design Code ◽  
Rc Structure ◽  
Steel Bars

Energy consumption and CO2 emissions in buildings is becoming an increasingly important issue. Steel is a major building material with high energy cost. In a reinforced concrete (RC) structure, it accounts for the maximum energy consumption. There is a need to quantify the steel amount in RC for various situations so that reduction or optimization in steel usage can be analyzed. In this paper two different calculations (Calculation-I and Calculation-II) are conducted by using two groups of steel in designing beams, columns and plates for a 20000 m2 five-storeyed frame RC structure. In Calculation-I, or Cal-I in abbreviation, the steel used for beams, columns and plates is HRB335, HRB400 and HPB235 respectively. In Calculation-II, or Cal-II in abbreviation, the steel used for beams, columns and plates is HRB400, HRB500 and CRB550 respectively. The strength of steel used in Cal-II is higher than that in Cal-I. The calculation is carried out by following the standardized concrete structural design code, and the steps involved in calculation are given in certain details as seen necessary. The corresponding energy for producing the steel used in beams, columns and plates is also computed and normalized on per square meter basis. The results show that Cal-II saves 101.76 tons of steel than Cal-I, or 5.09kg/m2, which means a saving of about 64.11 t of standard coal or 1.6×102 t CO2 for the whole structure, or 3.2 kg of standard coal or 7.98kg CO2 for per square meter.

Test and Study on Impact of Corrosion on Bond Force between Steel and Concrete

2010 ◽  
Vol 36 ◽  
pp. 176-181
Author(s):  
Xian Feng He ◽  
Shou Gang Zhao ◽  
Yuan Bao Leng
Keyword(s):  
Reinforced Concrete ◽  
Corrosion Rate ◽  
Concrete Structure ◽  
Steel Corrosion ◽  
Reinforced Concrete Structure ◽  
Bond Force ◽  
Steel Bars ◽  
Protection Layer ◽  
Corrosion Of Steel ◽  
The Impact

The corrosion of steel will have a bad impact on the safety of reinforced concrete structure. In severe cases, it may even be disastrous. In order to understand the impact of steel corrosion on the structure, tests are carried out to study corrosion and expansion rules of steel bars as well as the impact rules of corrosion on bond force between steel and concrete. The results show that wet and salty environment will result in steel corrosion; relatively minor corrosion will not cause expansion cracks of protection layers; when steel rust to a certain extent, it will cause cracks along the protection layer; when there exists minor corrosion in steel and the protection layer does not have expansion cracks, the bond force is still large and rapidly decreases as the corrosion rate increases.

Resource Scheduling and Load Balancing Fusion Algorithm with Deep Learning Based on Cloud Computing

2020 ◽  
pp. 1042-1057
Author(s):  
Xiaojing Hou ◽  
Guozeng Zhao
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Energy Consumption ◽  
Load Balancing ◽  
Energy Cost ◽  
Learning Strategy ◽  
Resource Scheduling ◽  
High Energy ◽  
Fusion Algorithm ◽  
Low Efficiency

With the wide application of the cloud computing, the contradiction between high energy cost and low efficiency becomes increasingly prominent. In this article, to solve the problem of energy consumption, a resource scheduling and load balancing fusion algorithm with deep learning strategy is presented. Compared with the corresponding evolutionary algorithms, the proposed algorithm can enhance the diversity of the population, avoid the prematurity to some extent, and have a faster convergence speed. The experimental results show that the proposed algorithm has the most optimal ability of reducing energy consumption of data centers.

Compressive Sensing for Structural Damage Detection of Reinforced Concrete Structures

2013 ◽  
Vol 569-570 ◽  
pp. 742-750 ◽  
Author(s):  
Madhuka Jayawardhana ◽  
Xin Qun Zhu ◽  
Ranjith Liyanapathirana ◽  
Upul Gunawardana
Keyword(s):  
Energy Consumption ◽  
Reinforced Concrete ◽  
Damage Detection ◽  
Compressive Sensing ◽  
Data Storage ◽  
Structural Damage ◽  
Structural Response ◽  
High Energy ◽  
Reconstructed Signal ◽  
Detection And Localization

High energy consumption, excessive data storage and transfer requirements are prevailing issues associated with structural health monitoring (SHM) systems, especially with those employing wireless sensors. Data compression is one of the techniques being explored to mitigate the effects of these issues. Compressive sensing (CS) introduces a means of reproducing a signal with a much less number of samples than the Nyquist's rate, reducing the energy consumption, data storage and transfer cost. This paper explores the applicability of CS for SHM, in particular for damage detection and localization. CS is implemented in a simulated environment to compress SHM data. The reconstructed signal is verified for accuracy using structural response data obtained from a series of tests carried out on a reinforced concrete (RC) slab. Results show that the reconstruction was close, but not exact as a consequence of the noise associated with the responses. However, further analysis using the reconstructed signal provided successful damage detection and localization results, showing that although the reconstruction using CS is not exact, it is sufficient to provide the crucial information of the existence and location of damage.

Double-Shift: A Low-Power DNN Weights Storage and Access Framework based on Approximate Decomposition and Quantization

2022 ◽  
Vol 27 (2) ◽  
pp. 1-16
Author(s):  
Ming Han ◽  
Ye Wang ◽  
Jian Dong ◽  
Gang Qu
Keyword(s):  
Energy Consumption ◽  
Low Power ◽  
Energy Cost ◽  
Computing Methodology ◽  
High Energy ◽  
Classification Error ◽  
Approximate Computing ◽  
Storage Allocation ◽  
Original Size ◽  
Iot Devices

One major challenge in deploying Deep Neural Network (DNN) in resource-constrained applications, such as edge nodes, mobile embedded systems, and IoT devices, is its high energy cost. The emerging approximate computing methodology can effectively reduce the energy consumption during the computing process in DNN. However, a recent study shows that the weight storage and access operations can dominate DNN's energy consumption due to the fact that the huge size of DNN weights must be stored in the high-energy-cost DRAM. In this paper, we propose Double-Shift, a low-power DNN weight storage and access framework, to solve this problem. Enabled by approximate decomposition and quantization, Double-Shift can reduce the data size of the weights effectively. By designing a novel weight storage allocation strategy, Double-Shift can boost the energy efficiency by trading the energy consuming weight storage and access operations for low-energy-cost computations. Our experimental results show that Double-Shift can reduce DNN weights to 3.96%–6.38% of the original size and achieve an energy saving of 86.47%–93.62%, while introducing a DNN classification error within 2%.

Investigation of the Influence of Cracks on Vibration Processes in a Reinforced Concrete Structure

2018 ◽  
Vol 938 ◽  
pp. 132-138
Author(s):  
Igor N. Shardakov ◽  
A. Shestakov ◽  
R.V. Tsvetkov ◽  
V. Yepin ◽  
I. Glot
Keyword(s):  
Reinforced Concrete ◽  
Concrete Structure ◽  
Numerical Experiments ◽  
Crack Nucleation ◽  
Numerical Data ◽  
Diagnostic Parameter ◽  
Reinforced Concrete Structure ◽  
Rc Structure ◽  
Proposed Model ◽  
The Mathematical Model

The validity of the mathematical model describing the propagation of vibrations in a reinforced concrete (RC) structure was verified by comparing the experimental and numerical data. The proposed model allowed one to perform numerical experiments aimed at comparing vibrorecords obtained from the structure without defects and the structure with cracks. A numerical experiment was performed aimed to explore the changes in vibrorecords when cracks appear in the structure. Based on the results these experiments, an informative diagnostic parameter controlling crack nucleation and propagation in the reinforced concrete structure was derived.

Comparison between Experiments and FEM Simulations of the Reinforced Concrete Structure under Shake Table Test

2013 ◽  
Vol 842 ◽  
pp. 477-481
Author(s):  
Ren Zuo Wang ◽  
Wen Yu Chang ◽  
Bing Chang Lin ◽  
Chao Hsun Huang
Keyword(s):  
Reinforced Concrete ◽  
Structural Model ◽  
Plastic Hinge ◽  
Structural Models ◽  
Shake Table ◽  
Reinforced Concrete Structure ◽  
Simulation Procedure ◽  
Nonlinear Responses ◽  
Rc Structure ◽  
Hinge Model

In this paper, the numerical simulation procedure of the reinforced concrete (RC) structure is purposed using SAP2000 software. The plastic hinge model (PHM) is using SWPH code. This PHM is to simulate the nonlinear responses of the RC structure under seismic. The numerical structural models are established using FEM models. The test specimen under shake table is two-span RC structure. In order to demonstrate the accuracy of RC structural model, comparisons between the experimental and numerical results are close. The proposed procedure can be used to simulate the nonlinear responses of RC structure under seismic.

Brief Introduction of Structural Design for Lijiang Sports Center Stadium

2013 ◽  
Vol 743 ◽  
pp. 159-163
Author(s):  
Wei Qiang Xu ◽  
Jing Xu Song ◽  
Wen Pan
Keyword(s):  
Reinforced Concrete ◽  
Structural Design ◽  
Concrete Structure ◽  
Pile Foundation ◽  
Reinforced Concrete Structure ◽  
Horizontal Shear ◽  
Shear Forces ◽  
Foundation Design ◽  
Combined Analysis ◽  
Selection Of

This paper focuses on the structural design for Lijiang Sports Center Stadium, reasonable structure partition of the stadium and the combined analysis of the lower part of reinforced concrete structure with the upper part of steel marguise. Besides, foundation design under larger eccentric loads and horizontal shear forces as well as the selection of pile foundation design are also investigated.

scholarly journals Energy Consumption and Internal Distribution in Activated Sludge Wastewater Treatment Plants of Greece

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1204 ◽  
Author(s):  
Alexandra Siatou ◽  
Anthoula Manali ◽  
Petros Gikas
Keyword(s):  
Wastewater Treatment ◽  
Energy Consumption ◽  
Activated Sludge ◽  
Energy Cost ◽  
Wastewater Treatment Plants ◽  
Electric Energy ◽  
High Energy ◽  
Energy Requirements ◽  
Electric Energy Consumption ◽  
Volume Unit

The high-energy consumption of wastewater treatment plants (WWTPs) is a crucial issue for municipalities worldwide. Most WWTPs in Greece operate as extended aeration plants, which results in high operational costs due to high energy needs. The present study investigated the energy requirements of 17 activated sludge WWTPs in Greece, serving between 1100–56,000 inhabitants (population equivalent, PE), with average daily incoming flowrates between 300–27,300 m3/d. The daily wastewater production per inhabitant was found to lie between 0.052 m3/PE·d and 0.426 m3/PE·d, with average volume of 0.217 ± 0.114 m3/PE·d. The electric energy consumption per volume unit (EQ (kWh/m3)) was between 0.128–2.280 kWh/m3 (average 0.903 ± 0.509 kWh/m3) following a near logarithmic descending correlation with the average incoming flowrate (Qav) (EQ = −0.294lnQav + 3.1891; R2 = 0.5337). A similar relationship was found between the daily electric energy requirements for wastewater treatment per inhabitant (EPE (kWh/PE·d)) as a function of PE, which varied from 0.041–0.407 kWh/PE·d (average 0.167 ± 0.101 kWh/PE·d)) (EPE = −0.073ln(PE) + 0.8425; R2 = 0.6989). Similarly, the daily energy cost per inhabitant (E€/PE (€/PE·d)) as a function of PE and the electric energy cost per wastewater volume unit (E€/V (€/m3)) as a function of average daily flow (Qav) were found to follow near logarithmic trends (E€/PE = −0.013ln(PE) + 0.1473; R2 = 0.6388, and E€/V = −0.052lnQav + 0.5151; R2 = 0.6359), respectively), with E€/PE varying between 0.005–0.073 €/PE·d (average 0.024 ± 0.019 €/PE·d) and E€/V between 0.012–0.291 €/m3 (average 0.111 ± 0.077 €/m3). Finally, it was calculated that, in an average WWTP, the aeration process is the main energy sink, consuming about 67.2% of the total electric energy supply to the plant. The large variation of energy requirements per inlet volume unit and per inhabitant served, indicate that there is large ground for improving the performance of the WWTPs, with respect to energy consumption.

Prediction of average debris launch velocity from a reinforced concrete structure based on SDOF system

2020 ◽  
pp. 136943322096027
Author(s):  
Seung-Hun Sung ◽  
Hun Ji ◽  
Surin Kim ◽  
Jinwung Chong
Keyword(s):  
Reinforced Concrete ◽  
Comparative Study ◽  
Conservation Equation ◽  
Reinforced Concrete Structure ◽  
Reinforcing Bars ◽  
Sdof System ◽  
Energy Conservation Equation ◽  
Rc Structure ◽  
Proposed Model ◽  
Velocity Prediction

This study presents a physics-based model for debris launch velocity prediction of a reinforced concrete (RC) structure subjected to a blast load. The model is basically derived from energy conservation equation. Especially, a resistance-deflection relationship for the structural single degree of freedom (SDOF) system is newly considered to evaluate the energy consumed by the damage and fragmentation of the RC structure. By applying the resistance-deflection relationship, the proposed model can consider the interactions between reinforcing bars and concrete. Moreover, since the resistance-deflection curve is evaluated considering various structural properties as well as boundary conditions, the proposed model can be flexibly utilized compared to conventional approaches. In order to confirm the performance of the proposed model, a comparative study was carried out against benchmark experiments on closed concrete box structures under an internal blast. From the comparative study, it was shown that the debris launch velocities estimated from the proposed model had a good agreement with the test results compared with the other models.

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