scholarly journals PENENTUAN LOKASI TOWER CRANE PADA PROYEK KONSTRUKSI BERBASIS SIMULASI

2020 ◽  
Vol 3 (4) ◽  
pp. 1305
Author(s):  
Gerwyn Persulessy ◽  
Basuki Anondho
Keyword(s):  
Travel Time ◽  
Construction Projects ◽  
Tower Crane ◽  
Location Determination ◽  
Heavy Equipment ◽  
Total Travel Time ◽  
Speed Up ◽  
High Level ◽  
Map Data ◽  
Geometric Layout

Development of high-level building construction projects that require complex equipment that can be used in high-level construction, equipment used to help complete construction projects called heavy equipment. One of the heavy equipment used in high-rise buildings is a tower crane. The use and layout of tower cranes can speed up the schedule and save on project costs. Therefore many methods have been developed to determine the tower crane layout. This study will discuss determining the location of tower cranes by discussing simulations. The location will be determined based on the site map data which is processed in the form of a geometric arrangement and tower crane data specifications. Location determination is done by comparing the total travel time of several simulated locations according to several different speed criteria in a construction project. Speed criteria are divided into four times the jib speed and trolley speed. Location of the location with the total travel time will be taken as the final result. Different speed criteria will make the total travel time change. ABSTRAKPerkembangan proyek pembangunan gedung bertingkat tinggi yang semakin kompleks menyebabkan diperlukannya peralatan yang dapat mempermudah pembangunan gedung bertingkat, peralatan yang digunakan untuk membantu menyelesaikan tugas konstruksi disebut alat berat. Salah satu peralatan berat yang digunakan pada gedung bertingkat tinggi adalah tower crane. Penggunaan dan tata letak tower crane yang baik dapat mempercepat jadwal dan menghemat biaya proyek. Oleh karena itu banyak dikembangkan metode-metode untuk menentukan tata letak tower crane. Penelitian ini akan membahas penetapan letak lokasi tower crane dengan pendekatan  simulasi. Letak lokasi akan ditetapkan berdasarkan data site map yang diolah dalam bentuk geometric layout dan data spesifikasi tower crane. Penetapan lokasi dilakukan dengan cara membandingkan total travel time dari beberapa lokasi yang disimulasi sesuai dengan beberapa kriteria kecepatan yang berbeda-beda pada suatu proyek konstruksi. Kriteria kecepatan terbagi menjadi empat berdasarkan besarnya kecepatan jib dan kecepatan trolley. Letak lokasi dengan total travel time terkecil akan diambil sebagai hasil akhir. Kriteria-kriteria kecepatan yang berbeda disimulasi akan membuat total travel time berubah.

scholarly journals Productivity of Column Casting Heavy Equipment in the Construction of 31 Sudirman Suites Makassar Apartment

2021 ◽  
Vol 3 (3) ◽  
pp. 10-20
Author(s):  
Fedelia Randan ◽  
Junus Mara ◽  
Lintje Tammu Tangdialla
Keyword(s):  
Construction Projects ◽  
Material Transfer ◽  
Work Time ◽  
Tower Crane ◽  
Heavy Equipment ◽  
Equipment Construction ◽  
Calculation Results ◽  
Real Value ◽  
Time Required ◽  
Equipment Operator

In the world of heavy equipment construction projects it is important to help complete human work. Tower Crane is one of the tools in the implementation of construction projects. In the implementation of the construction of Apartment 31 Sudirman Suites Makassar, there are 2 Tower Crane tools that operate with limited work time due to covid 19. This research was carried out by direct observation in the field and calculating the real value of the specifications to compare productivity. Tower Crane productivity is the result achieved or output, namely the amount of material moved by Tower Crane with all resources or inputs, namely the time required for material transfer. Based on the calculation results that the productivity of the specification is greater than the productivity of observations in the field, this is due to constraints on the weather that occurs and the equipment operator. For productivity, the average obtained on the 4th floor is 71,544 (%) and on the 5th floor it is obtained that is 73,727 (%).

scholarly journals Equity Effects of Congestion Charges: An Exploratory Analysis with MATSim

2017 ◽  
Vol 2670 (1) ◽  
pp. 75-82 ◽  
Author(s):  
Lucas Meyer de Freitas ◽  
Oliver Schuemperlin ◽  
Milos Balac ◽  
Francesco Ciari
Keyword(s):  
Travel Time ◽  
Large Scale ◽  
Agent Based ◽  
Promising Tool ◽  
Travel Time Savings ◽  
Time Savings ◽  
Time Changes ◽  
High Level ◽  
Congestion Charging ◽  
Equity Effects

This paper shows an application of the multiagent, activity-based transport simulation MATSim to evaluate equity effects of a congestion charging scheme. A cordon pricing scheme was set up for a scenario of the city of Zurich, Switzerland, to conduct such an analysis. Equity is one of the most important barriers toward the implementation of a congestion charging system. After the challenges posed by equity evaluations are examined, it is shown that agent-based simulations with heterogeneous values of time allow for an increased level of detail in such evaluations. Such detail is achieved through a high level of disaggregation and with a 24-h simulation period. An important difference from traditional large-scale models is the low degree of correlation between travel time savings and welfare change. While traditional equity analysis is based on travel time savings, MATSim shows that choice dimensions not included in traditional models, such as departure time changes, can also play an important role in equity effects. The analysis of the results in light of evidence from the literature shows that agent-based models are a promising tool to conduct more complete equity evaluations not only of congestion charges but also of transport policies in general.

Estimating Express Train Preference of Urban Railway Passengers Based on Extreme Gradient Boosting (XGBoost) using Smart Card Data

2021 ◽  
pp. 036119812110133
Author(s):  
Eun Hak Lee ◽  
Kyoungtae Kim ◽  
Seung-Young Kho ◽  
Dong-Kyu Kim ◽  
Shin-Hyung Cho
Keyword(s):  
Travel Time ◽  
Smart Card ◽  
Public Transportation ◽  
Gradient Boosting ◽  
Log Data ◽  
Smart Card Data ◽  
Extreme Gradient Boosting ◽  
Express Train ◽  
Total Travel Time ◽  
The Individual

As the share of public transport increases, the express strategy of the urban railway is regarded as one of the solutions that allow the public transportation system to operate efficiently. It is crucial to express the urban railway’s express strategy to balance a passenger load between the two types of trains, that is, local and express trains. This research aims to estimate passengers’ preference between local and express trains based on a machine learning technique. Extreme gradient boosting (XGBoost) is trained to model express train preference using smart card and train log data. The passengers are categorized into four types according to their preference for the local and express trains. The smart card data and train log data of Metro Line 9 in Seoul are combined to generate the individual trip chain alternatives for each passenger. With the dataset, the train preference is estimated by XGBoost, and Shapley additive explanations (SHAP) is used to interpret and analyze the importance of individual features. The overall F1 score of the model is estimated to be 0.982. The results of feature analysis show that the total travel time of the local train feature is found to substantially affect the probability of express train preference with a 1.871 SHAP value. As a result, the probability of the express train preference increases with longer total travel time, shorter in-vehicle time, shorter waiting time, and few transfers on the passenger’s route. The model shows notable performance in accuracy and provided an understanding of the estimation results.

scholarly journals Intelligent Ramp Control for Incident Response Using Dyna-QArchitecture

2015 ◽  
Vol 2015 ◽  
pp. 1-16
Author(s):  
Chao Lu ◽  
Yanan Zhao ◽  
Jianwei Gong
Keyword(s):  
Reinforcement Learning ◽  
Travel Time ◽  
Single Agent ◽  
Superior Performance ◽  
Model Free ◽  
Road Users ◽  
Total Travel Time ◽  
The Uk ◽  
Traffic Operation ◽  
Ramp Control

Reinforcement learning (RL) has shown great potential for motorway ramp control, especially under the congestion caused by incidents. However, existing applications limited to single-agent tasks and based onQ-learning have inherent drawbacks for dealing with coordinated ramp control problems. For solving these problems, a Dyna-Qbased multiagent reinforcement learning (MARL) system named Dyna-MARL has been developed in this paper. Dyna-Qis an extension ofQ-learning, which combines model-free and model-based methods to obtain benefits from both sides. The performance of Dyna-MARL is tested in a simulated motorway segment in the UK with the real traffic data collected from AM peak hours. The test results compared with Isolated RL and noncontrolled situations show that Dyna-MARL can achieve a superior performance on improving the traffic operation with respect to increasing total throughput, reducing total travel time and CO2emission. Moreover, with a suitable coordination strategy, Dyna-MARL can maintain a highly equitable motorway system by balancing the travel time of road users from different on-ramps.

Dynamic control cycle speed limit strategy for balanced reduction of travel time and emissions

2021 ◽  
Vol 35 (09) ◽  
pp. 2150153
Author(s):  
Minghui Ma ◽  
Yaozong Zhang ◽  
Shidong Liang
Keyword(s):  
Travel Time ◽  
Traffic Control ◽  
Dynamic Control ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Vehicle Exhaust ◽  
Environmental Benefit ◽  
Multiple Control ◽  
Total Travel Time ◽  
Co Emission

The vehicle exhaust has been one of the major sources of greenhouse gas emissions. With an increase in traffic volume, it has been found that the introduced intelligent traffic control is necessary. This paper investigated a novel VSL strategy considering the dynamic control cycle to improve the traffic efficiency and environmental benefit on freeway. An extension of the cell transmission model (CTM) was used to depict the traffic characteristics under VSL control, and integrated with the microscopic emission and fuel consumption model VT-Micro to estimate the pollution emission of each cell. The VSL strategy was designed to provide multiple control cycles with different length to adjust the scope of VSL changes, furthermore, a probability formula was developed and used to determine the optimal quantity of control cycles to reduce the computational complexity of controller. An objective optimization function was formulated with the aim of minimizing total travel time and CO emission. With simulation experiments, the results showed that the proposed VSL strategy considering the dynamic control cycle outperformed uncontrolled scenario, resulting in up to 8.4% of total travel time reductions, 26.7% of delay optimization, and 14.5% reduction in CO emission, which enhanced the service level of freeway network.

scholarly journals The prediction of tsunami travel time to Mataram City Indonesia based on North Lombok earthquake as the initial condition

2018 ◽  
Vol 229 ◽  
pp. 04007
Author(s):  
Eko Pradjoko ◽  
Lukita Wardani ◽  
Hartana ◽  
Heri Sulistiyono ◽  
Syamsidik
Keyword(s):  
Travel Time ◽  
Earthquake Hazard ◽  
Capital City ◽  
Maximum Magnitude ◽  
Initial Condition ◽  
Tsunami Simulation ◽  
The Past ◽  
The North ◽  
Tsunami Travel Time ◽  
High Level

The past earthquake records in North Lombok show the high level of earthquake hazard in this area. The maximum magnitude of the earthquake was 6.4 Mw on May 30th, 1979. But, there were no tsunami events records due to those earthquakes. Nevertheless, this area is very close to Mataram City (province capital city) and tourism area. Therefore, the assessment of tsunami hazard is very important. The tsunami simulation was conducted by using COMCOT Model, which is based on the North Lombok Earthquake as the initial condition. The simulation result shows the prediction of tsunami travel time is about 18 ~ 20 minutes from the source location to Mataram City. The height of the tsunami wave is 0.13 ~ 0.20 meters due to the earthquake magnitude is about 6 Mw.

scholarly journals Design of Signal Timing Plan for Urban Signalized Networks including Left Turn Prohibition

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Qinrui Tang ◽  
Bernhard Friedrich
Keyword(s):  
Travel Time ◽  
Treatment Options ◽  
User Equilibrium ◽  
Signal Timing ◽  
Stochastic User Equilibrium ◽  
Left Turn ◽  
Traffic Demand ◽  
Total Travel Time ◽  
Left Turns ◽  
Demand Patterns

Urban road networks may benefit from left turn prohibition at signalized intersections regarding capacity, for particular traffic demand patterns. The objective of this paper is to propose a method for minimizing the total travel time by prohibiting left turns at intersections. With the flows obtained from the stochastic user equilibrium model, we were able to derive the stage generation, stage sequence, cycle length, and the green durations using a stage-based method which can handle the case that stages are sharing movements. The final output is a list of the prohibited left turns in the network and a new signal timing plan for every intersection. The optimal list of prohibited left turns was found using a genetic algorithm, and a combination of several algorithms was employed for the signal timing plan. The results show that left turn prohibition may lead to travel time reduction. Therefore, when designing a signal timing plan, left turn prohibition should be considered on a par with other left turn treatment options.

scholarly journals An Open-Source Cloud-FPGA Gene Regulatory Accelerator

2021 ◽  
Author(s):  
Lucas Bragança ◽  
Jeronimo Penha ◽  
Michael Canesche ◽  
Dener Ribeiro ◽  
José Augusto M. Nacif ◽  
...  
Keyword(s):  
Open Source ◽  
Gene Regulatory Networks ◽  
High Performance ◽  
Regulatory Networks ◽  
Cloud Services ◽  
On Demand ◽  
Speed Up ◽  
Gene Regulatory ◽  
High Level ◽  
Better Than

FPGAs are suitable to speed up gene regulatory network (GRN) algorithms with high throughput and energy efficiency. In addition, virtualizing FPGA using hardware generators and cloud resources increases the computing ability to achieve on-demand accelerations across multiple users. Recently, Amazon AWS provides high-performance Cloud's FPGAs. This work proposes an open source accelerator generator for Boolean gene regulatory networks. The generator automatically creates all hardware and software pieces from a high-level GRN description. We evaluate the accelerator performance and cost for CPU, GPU, and Cloud FPGA implementations by considering six GRN models proposed in the literature. As a result, the FPGA accelerator is at least 12x faster than the best GPU accelerator. Furthermore, the FPGA reaches the best performance per dollar in cloud services, at least 5x better than the best GPU accelerator.

scholarly journals Deep Learning Strategies for ProtoDUNE Raw Data Denoising

2022 ◽  
Vol 6 (1) ◽  
Author(s):  
Marco Rossi ◽  
Sofia Vallecorsa
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Learning Strategies ◽  
Simulation Data ◽  
Raw Data ◽  
Digital Detector ◽  
Speed Up ◽  
Neural Network Hardware ◽  
Graph Neural Networks ◽  
High Level

AbstractIn this work, we investigate different machine learning-based strategies for denoising raw simulation data from the ProtoDUNE experiment. The ProtoDUNE detector is hosted by CERN and it aims to test and calibrate the technologies for DUNE, a forthcoming experiment in neutrino physics. The reconstruction workchain consists of converting digital detector signals into physical high-level quantities. We address the first step in reconstruction, namely raw data denoising, leveraging deep learning algorithms. We design two architectures based on graph neural networks, aiming to enhance the receptive field of basic convolutional neural networks. We benchmark this approach against traditional algorithms implemented by the DUNE collaboration. We test the capabilities of graph neural network hardware accelerator setups to speed up training and inference processes.

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