scholarly journals Temperature Prediction Model in the Main Ventilation System of an Underground Mine

2020 ◽  
Vol 10 (20) ◽  
pp. 7238
Author(s):  
Marc Bascompta ◽  
Josep M. Rossell ◽  
Lluís Sanmiquel ◽  
Hernán Anticoi
Keyword(s):  
Underground Mining ◽  
Estimation Error ◽  
Ventilation System ◽  
Mine Ventilation ◽  
Temperature Sensors ◽  
Reliable Data ◽  
Temperature Prediction ◽  
Workplace Conditions ◽  
Drift Length

A model to forecast the underground temperature in a mine ventilation circuit was developed on the basis of a case study and actual data describing temperature, airflow, and drift length collected over several years. A mathematical model featuring seven variables with interactions provided reliable predicted temperatures, achieving a correlation of R2 = 0.933 with an estimation error of ±2 °C. Its soundness was proven using both the node-to-node analysis and the multi-node approach. The multi-node approach was shown to be an interesting option to model underground mining environments. This model can be very useful to predict the temperature evolution along the main ventilation system, determine the best workplace conditions in terms of temperature, and analyze different planning scenarios of the mine. Moreover, some recommendations are presented for obtaining reliable data when using temperature sensors and the model in a U-shaped ventilation system.

scholarly journals Airflow Stability and Diagonal Mine Ventilation System Optimization: A Case Study

2018 ◽  
Vol 54 (5) ◽  
pp. 813-820
Author(s):  
M. Bascompta ◽  
L. Sanmiquel ◽  
H. Zhang
Keyword(s):  
Ventilation System ◽  
System Optimization ◽  
Mine Ventilation

Optimum Mine Ventilation System Using Gallery Temperature Prediction

2016 ◽  
Vol 16 (3) ◽  
pp. 73-79
Author(s):  
Joon Uk Kwon ◽  
Doo Hwan Song ◽  
Yun Kwang Kim ◽  
Yun Ho Jang
Keyword(s):  
Ventilation System ◽  
Mine Ventilation ◽  
Temperature Prediction

The Potential of The Hotel Industry In Pandemic Era Based On Finance Performance Point Of View, Case Study: Indonesia

2021 ◽  
Vol 1 (1) ◽  
pp. 111-123
Author(s):  
Anton Effendi ◽  
◽  
Bambang Hadi Prabowo
Keyword(s):  
Hospitality Industry ◽  
Stock Exchange ◽  
Hotel Industry ◽  
Secondary Data ◽  
Reliable Data ◽  
Point Of View ◽  
Threshold Autoregressive ◽  
Performance Point ◽  
Occupancy Rates

This article aims to investigate and analyze the potential of the hospitality industry by comparing the potential occupancy rates and hotel revenues of foreign and domestic tourists. This investigation uses an investigation of company data obtained from reports from hotel companies throughout Indonesia which are listed on the Indonesia Stock Exchange and secondary data obtained from world banks and other reliable data. This study uses behavioral data analysis using Threshold Autoregressive from 2000 to 2019. It was found that domestic tourists are a new hope that needs to be considered in surviving and restoring the hospitality industry after being exposed to the COVID-19 pandemic which has led hotel companies. temporarily closed operations and part of the hotel went bankrupt. Optimization of domestic tourists allowed the hotel industry to develop rapidly after the Covid-19 pandemic ended.

scholarly journals StreamFlow 1.0: an extension to the spatially distributed snow model Alpine3D for hydrological modelling and deterministic stream temperature prediction

2016 ◽  
Vol 9 (12) ◽  
pp. 4491-4519 ◽  
Author(s):  
Aurélien Gallice ◽  
Mathias Bavay ◽  
Tristan Brauchli ◽  
Francesco Comola ◽  
Michael Lehning ◽  
...  
Keyword(s):  
Source Code ◽  
Stream Temperature ◽  
Object Oriented Programming ◽  
Temperature Prediction ◽  
Uncertainty Estimates ◽  
Physically Based ◽  
Snow Model ◽  
Alpine Catchments ◽  
Alpine Rivers

Abstract. Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one of the promising approaches to reduce our uncertainty of future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface flow, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash–Sutcliffe efficiency (NSE) of 0.82 and hourly mean temperature with a NSE of 0.78.

scholarly journals Real-Time Hydraulic Interval State Estimation for Water Transport Networks: a Case Study

2017 ◽  
Author(s):  
Stelios G. Vrachimis ◽  
Demetrios G. Eliades ◽  
Marios M. Polycarpou
Keyword(s):  
State Estimation ◽  
Real Time ◽  
Water Distribution ◽  
Estimation Error ◽  
Distribution Networks ◽  
Water Levels ◽  
Water Distribution Networks ◽  
Unaccounted For Water ◽  
Tank Water

Abstract. Hydraulic state estimation in water distribution networks is the task of estimating water flows and pressures in the pipes and nodes of the network based on some sensor measurements. This requires a model of the network, as well as knowledge of demand outflow and tank water levels. Due to modeling and measurement uncertainty, standard state-estimation may result in inaccurate hydraulic estimates without any measure of the estimation error. This paper describes a methodology for generating hydraulic state bounding estimates based on interval bounds on the parametric and measurement uncertainties. The estimation error bounds provided by this method can be applied to estimate the unaccounted-for water in water distribution networks. As a case study, the method is applied to a transport network in Cyprus, using actual data in real-time.

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