Operational energy minimisation for forced draft, direct-contact bulk air cooling tower through a combination of forward and first-principle modelling, coupled with an optimisation platform

Bornman, Waldo; Dirker, Jaco; Arndt, Deon C.; Meyer, Josua P.

doi:10.1016/j.energy.2016.08.069

Cited by 13 publications

(12 citation statements)

References 21 publications

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“…As analyzed above, the recognized damping ratios had a dispersed distribution. Here, following the method of modal combination, the mass participation factors of the first 10 modes were used as the additional weights for the damping ratio of the corresponding mode. Thus, the equivalent synthetic damping ratio of the overall structure was calculated by weighting,

ξ_{eq} = \sum_{i = 1}^{10} η_{i} ξ_{i},

where ξ eq is equivalent to synthetic damping ratio (%); η i is the mass participation factor for mode i ; ξ i is damping ratio for mode i (%).…”

Section: Field Measurements and Modal Recognitionmentioning

confidence: 99%

“…where ξ eq is equivalent to synthetic damping ratio (%); η i is the mass participation factor for mode i; ξ i is damping ratio for mode i (%). By resorting to the method of modal combination, [33] a weight was attributed to the damping ratio of each mode of vibration to calculate the equivalent synthetic damping ratio of the entire structure. Figure 5 shows the proportionality coefficients and damping ratio distribution curve of the first 10 orders.…”

Section: Modal Parameter Recognizationmentioning

confidence: 99%

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Identification of damping ratio and its influences on wind‐ and earthquake‐induced effects for large cooling towers

et al. 2018

Structural Design Tall Build

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Summary Standard 5% damping ratio for high‐rise concrete structures is generally used for dynamic analysis under the action of wind and earthquakes in the existing cooling tower regulations and researches. But considering the unique configuration and material attributes of large cooling towers, the actual damping ratio must be far smaller than the recommended. However, only a few field measurements of damping ratio for large cooling towers have been conducted; neither are there thorough investigation into the qualitative and quantification of wind and seismic effects under different damping ratio. To fill this gap, field measurements of a large cooling tower standing 179 m in northwestern China was performed and acceleration vibration signals at representative positions of the tower under ambient excitation were obtained. The vibration signals were preprocessed combining random decrement technique and natural excitation technique. Three pattern recognition methods (auto‐regressive and moving mean model, Ibrahim time domain, and spare time domain (STD)) were applied to analyze the frequencies, damping ratios, and modes of vibration for the first 10 order modes. Following the line of thought of modal combination, the equivalent synthetic damping ratio was derived. Under 5 damping ratios (0.5%, 1%, 2%, 3%, and 5%), a comparative analysis on the dynamic responses of the cooling tower to wind and single seismic loading by using full transient method was performed. On this basis, the patterns of influence of damping ratio on wind‐induced vibration, wind vibration coefficient, and time history and extrema of seismic responses were extracted. Finally, different combinations of dead weight, wind, temperature in winter, sunshine duration, and seismic intensity and those of accidental seismic effects (8 working conditions) were considered, using equivalent synthetic damping ratio and standard damping ratio. Thus, the most unfavorable working conditions were identified under actual and standard damping ratios for the large cooling tower. Our research findings provide reference for determining the value of damping ratio in large cooling towers and deepening the understanding on the influence mechanism of damping ratio.

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ξ_{eq} = \sum_{i = 1}^{10} η_{i} ξ_{i},

where ξ eq is equivalent to synthetic damping ratio (%); η i is the mass participation factor for mode i ; ξ i is damping ratio for mode i (%).…”

Section: Field Measurements and Modal Recognitionmentioning

confidence: 99%

Section: Modal Parameter Recognizationmentioning

confidence: 99%

Identification of damping ratio and its influences on wind‐ and earthquake‐induced effects for large cooling towers

et al. 2018

Structural Design Tall Build

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“…Coefficients to are system specific constants which can be obtained similar to and by using Eq. (6) [39].…”

Section: ̇ ̇ ̇ ̇ (5)mentioning

confidence: 99%

“…To model the cooling towers with the objective of integrated optimisation, an explicit model is required, which would allow the prediction of the outlet conditions from any set of inlet conditions without the requirement for iterative computation. A suitable method for this is by using the approach proposed by Bornman et al [39] whereby the performance of direct contact cooling towers can be determined by means of a combined forward and first-principle model which is based on underlying energy balance and heat transfer principles. This model is bound by the following assumptions: (1) water loss through evaporation is not significant;…”

Section: Cooling Towers and Air Coolers 32mentioning

confidence: 99%

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Integrated energy simulation of a deep level mine cooling system through a combination of forward and first-principle models applied to system-side parameters

Bornman

Dirker

Arndt³

et al. 2017

Applied Thermal Engineering

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Highlights• Proposition of an integrated mine cooling system energy modelling method.• The model is be calibrated with system measured or manufacturer data.• Major energy consuming devices include chillers, cooling towers, pumps and fans.• Model parameter identification achieved RMSRE values between 0.0114 and 0.0651.• An overall absolute average error between 2.5% and 3.5% was obtained. 2 AbstractMine cooling systems typically account for around 25% of the total electrical energy consumption of deep level mines. Numerous energy saving strategies have been implemented; with various levels of success. Most of the previously implemented strategies involved load shifting, energy efficiency and demand reduction. To achieve this, some levels of control are often introduced to control chilled water consumption, water and air mass flow rates as well as scheduling cooling system operation in order to shift the load primarily to offpeak periods.To support and sustain further reduction of energy consumption and optimisation of savings, a simulation model of the integrated cooling system represented by smooth and continuous equations is needed to assist the optimisation computation. This study focused on developing such an integrated mine cooling system simulation model to mimic the thermal hydraulic behaviour along with the energy consumption of the complete mine cooling system. This was achieved by coupling various models representing the major cooling system components such as chillers, cooling towers, pumps and fans together. Although various cooling system energy simulations were considered before, very few quantify the simulation accuracy on a component basis; furthermore, only limited cases were found where the entire system was considered. For these cases not all components were always based on explicit models which would eliminate the requirement for iterative computation which deter optimisation applications.The simulation model was used to predict the energy consumption of the integrated cooling system of a deep level gold mine in South Africa. The simulation model obtained an average error when compared to the mine's system data of 3.5% for a selected dataset and 2.5% for 3 another dataset one month later. The successful energy simulation of an integrated mine cooling system would allow for a holistic view on the total power consumption as one parameter or any combination of parameters of the system changes. NomenclatureA area [m²] BAC bulk air cooler C local loss coefficient specific heat capacity [J/kg K] CC cooling capacity [W] CCT condenser cooling tower COP coefficient of performance D h hydraulic diameter [m] f friction factor enthalpy [J/kg] HVAC heating ventilation and air conditioning k flow admittance [m 4 ] L length [m] ̇ mass flow rate [kg/s] MIN minimum N dataset length P pressure [Pa] PCT pre-cooling tower ̇ cooling [W] R correlation coefficient RH relative humidity RMSRE root mean square of relative error 4 SCADA supervisory control and data acquisition system temperature [ºC] V velocity [m/s] ̇ p...

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Development of Guidelines for Optimal Operation of a Cogeneration System

Kang¹,

Chang²,

Shieh³

et al. 2019

Computer Aided Chemical Engineering

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Operational energy minimisation for forced draft, direct-contact bulk air cooling tower through a combination of forward and first-principle modelling, coupled with an optimisation platform

Cited by 13 publications

References 21 publications

Identification of damping ratio and its influences on wind‐ and earthquake‐induced effects for large cooling towers

Identification of damping ratio and its influences on wind‐ and earthquake‐induced effects for large cooling towers

Integrated energy simulation of a deep level mine cooling system through a combination of forward and first-principle models applied to system-side parameters

Development of Guidelines for Optimal Operation of a Cogeneration System

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