Search Results (22)

Energy-intensive refrigeration systems require predictive models that remain informative under counterfactual control trajectories, not only on archived operation. This paper develops a control-oriented multi-step state model and a nonlinear model predictive control framework for an indoor ice-rink refrigeration system. Historical state, control, and exogenous variables are encoded jointly with an admissible future control trajectory, and a normalized thermal-balance residual is added to the training objective. A lightweight conditioned transformer predicts ice temperature, return-glycol temperature, supply-glycol temperature, and compressor power over a 30 min horizon. The selected weakly regularized model with regularization coefficient ${\lambda }_{phys}= 0.001$ decreases the normalized thermal-balance root-mean-square error on the horizon tail by 30.29% relative to the base model while increasing the average ice-temperature root-mean-square error by only 1.90%. In a surrogate-based counterfactual four-day evaluation, the resulting nonlinear model predictive controller reduces predicted daily energy by 4.84%, terminal violation share by 17.32%, mean absolute terminal ice-temperature deviation by 18.74%, and the mean objective value by 30.82% relative to historical admissible setpoint tracking. The mean full control cycle time is 0.0311 s, confirming real-time feasibility for a 5 min supervisory update interval. All controller results are surrogate-based rather than field-deployed and therefore represent receding-horizon benchmark results under learned-model evaluation, not realized field savings. Full article

Real-time trajectory forecasting for curling stones is essential for on-ice decision support, yet prior work often emphasizes offline analysis, fixed-window predictors, or physics-driven models that require additional measurements, and it rarely reports end-to-end feasibility under edge-computing constraints (latency and memory). This leaves a practical gap between accurate trajectory reconstruction and deployable rink-side guidance. To bridge this gap, we propose an online forecaster based on low-dimensional $(x,y)$ coordinate streams and a lightweight attention-enhanced Long Short-Term Memory (LSTM) architecture optimized for edge devices. The model uses a four-second sliding window (240 frames at 59.94 Hz) to predict fifteen seconds of future positions (900 frames) in a single multi-step forward pass, and an overlapping publication scheme is adopted to retain longer temporal context and stabilize continuous updates. We further provide a TensorFlow Lite (TFLite) conversion and quantization workflow to support on-device inference. Quantitatively, experiments on the CurlTracer dataset (1033 throws at 59.94 Hz) show that the proposed attention–LSTM achieves trajectory-level MAE/MdAE of 0.25/0.22 m over the full prediction horizon, improving over a plain LSTM (0.30/0.24 m) and a physics-based pivot-slide baseline (3.52/3.54 m). At two checkpoints, the first-step MAE/MdAE are 0.14/0.11 m and the mid-step MAE/MdAE are 0.21/0.18 m. For real-time feasibility, on a Raspberry Pi 4B the per-window latency is approximately 0.25 s (including I/O and post-processing), while CPU benchmarks show that TFLite variants provide 7–8× speedups over the original Keras runtime with only minor accuracy loss (e.g., window-level MAE 0.30–0.41 m across FP32/DRQ/FP16/INT8). Qualitatively, representative trajectory visualizations show good agreement in near/mid horizons and reasonable stopping-region guidance, supporting integration with a stone-mounted interface for actionable feedback. Full article

The reduction in energy use in buildings remains a major challenge. In the European Union, buildings account for approximately 40% of the total energy consumption, with sports facilities alone responsible for around 10% of annual use. These facilities are characterised by specific indoor environmental requirements, and ice rink arenas, in particular, represent substantial energy consumers due to the demands of ventilation and dehumidification processes. This paper investigates strategies for maintaining adequate air parameters in an ice rink arena, based on an experimentally verified numerical model of the facility. The research focused on: (1) assessing the energy consumption of different ventilation and air distribution system configurations, and (2) evaluating potential reductions achievable through the implementation of recirculation, heat recovery, and various air handling unit (AHU) configurations, while ensuring appropriate thermal and humidity conditions within the arena. Multi-variant simulations of AHU energy consumption were performed in IDA ICE 4.8 software for both day and night operation over the entire ice rink season. The results showed that the choice and operation of AHU configurations significantly influenced energy consumption as well as the thermal–humidity conditions of the facility, with annual savings of up to 67%. Full article

Outdoor ice rinks have long been a staple for inexpensive exercise and entertainment in cold environments. However, the possible deterioration of or impact on outdoor ice rinks from a changing climate is poorly understood due to no or little monitoring of data of such facilities. To investigate long-term changes in ice rinks over recent decades, an energy-balance-based ice rink model (with three versions considering precipitation and melt) was applied to a simulated ice rink for two representative area—Dorset of south-central Ontario and the Experimental Lakes Area (ELA) of northwestern Ontario, Canada. The model was calibrated and tested using four-year ice rink data (since limited data are available) and applied to a 40-year period starting in 1978 to reproduce the dates of rink-on and rink-off, rink duration in a season, and ice water equivalent under daily climate inputs, and to illustrate any changing trend in these variables, i.e., the ice rink responses to changed climate. Results showed no clear trend in any ice rink features over four decades, attributed to winter temperature that did not increase substantially (a weak driver), no change in events of rain-on-ice and snowfall-on-rink, and reduced wind speed (possibly slowing ice melting). This is the first trial of a physically based rink model to evaluate outdoor ice rinks. More in situ monitoring and in-depth modelling are necessary, and this model can help guide the monitoring. Full article

Ice is a common natural phenomenon in cold areas, which plays an important role in the construction of cold areas and the design of artificial ice rinks. To supplement our knowledge of ice mechanics, this paper investigates the mechanical properties of granular snow ice. The factors influencing the flexural strength of granular snow ice are analyzed through a three-point bending test. It is found that flexural strength is affected by strain rate. At low strain rates, flexural strength increases with increasing strain rate, whereas at high strain rates, flexural strength decreases with increasing strain rate. As temperature decreases, the flexural strength value of ice increases, but its brittleness becomes more pronounced, indicating that the strain rate corresponding to the maximum flexural strength is lower. Within the test temperature range, the tough-brittle transition range is from 6.67 × 10⁻⁵ s⁻¹ to 3.11 × 10⁻⁴ s⁻¹. At −5 °C, the strain rate corresponding to the maximum bending strength is 3.11 × 10⁻⁴ s⁻¹, while at −10 °C, it is only 6.67 × 10⁻⁵ s⁻¹. Flexural strength is influenced by crystal structure. At −20 °C, the average flexural strength of granular snow ice is 2.85 MPa, compared to 1.93 MPa for columnar ice at the same temperature. Through observation, we found that there are straight cracks and oblique cracks. The fracture toughness of granular snow ice was investigated by cutting prefabricated cracks at the bottom of the ice beam and employing a three-point bending device. It is found that fracture toughness decreases with increasing strain rate. Temperature also affects granular snow ice. At −15 °C, fracture toughness is 181.60 kPa·m^1/2, but at −6 °C, it decreases to 147.28 kPa·m^1/2. However, at varying temperatures and strain rates, there is no significant difference in the fracture patterns of ice samples, which predominantly develop upward along the prefabricated cracks. Full article

The differentiated physical environment requirements within the internal space of ice rinks in cold regions result in a complex heat exchange process, which becomes the primary cause of high energy consumption. Therefore, analyzing the impact mechanisms of spatial layout parameters on the energy consumption of ice rinks is crucial during the early design stages. This study employed the Delphi method to identify the key parameters affecting the total energy consumption of ice rinks. It conducted single-factor experiments using building performance simulations to quantify the relationship between each layout parameter and the energy consumption. Based on the single-factor experiment results, orthogonal experiments were conducted to develop an energy-efficient spatial layout combination. The study indicates that the height-to-width ratio and the mixed area width are the most significant parameters. By adjusting the values of these parameters, the total energy consumption can be reduced by approximately 18% to 31%. The spatial layout strategy for ice rinks in cold regions proposed in this study will help architects make more effective decisions during the early design stages. Full article

In the midst of today’s energy crisis, carbon emissions from ice rinks in cold regions present a significant environmental challenge. The shape of an ice rink’s roof significantly influences these emissions. This study developed a methodology to quantify the carbon emissions of ice rinks and explained how their roof shapes impact emissions during the operational phase. Roof shapes were divided into the following three categories: flat, curved, and combined torsion shell. Carbon emission modeling was established and calibrated using the Ladybug + Honeybee platform, followed by regression analyses on the slope and curvature of each roof type. The findings indicate a robust correlation between the carbon emissions of an ice rink and the slope and curvature of its roof. Roof shape influences approximately 2% of carbon emissions during the operational phase of an ice rink. Among the various roof shapes, the curved dome roof demonstrates the most effective overall carbon savings, at a rate of 0.93% compared to the flat roof. Selecting an appropriate roof shape has significant carbon-saving potential for ice rinks. The findings of this study may serve as a valuable reference for the formulation of energy-saving design standards in cold regions. Full article

This study is about a COVID-19 outbreak and ventilation measures taken against COVID-19 transmission through the air occurred at an ice arena in Japan. The ice arena has been known to have a deterioration of indoor air quality affected by CO, NO₂ and so on, and a total of 172 persons were infected with SARS-CoV-2, including the players and the spectators related to an ice hockey game in 2022. Given the suspected transmission through the air as one of infection routes, the primary objective of this study was to investigate the COVID-19 outbreak to verify the ventilation characteristics and aerosol diffusion characteristics. Additionally, the possibility of COVID-19 transmission through the air and the potentially effective ventilation measures in an ice arena are discussed. It was determined that the virus-containing aerosol was released from a player in the ice rink and accumulated in the cold air spot. After that, it was highly possible that it diffused from the player benches to the spectator seats due to the players’ movements under this unique air-conditioning and ventilation system. Judging from the results of genomic analysis, ventilation characteristics, and aerosol diffusion characteristics, the possibility of COVID-19 transmission through the air cannot be ruled out in an ice arena. The results of ventilation measures implemented in response to this problem confirmed that the integration of a lower-level exhaust fan based on cold air characteristics into the existing ventilation system is a relatively straightforward solution with the potential to be highly effective. While there is an option to refrain from using the ice arena in the event of an increased risk of mass infection during a pandemic, the findings of this study will contribute to an option to facilitate the smooth operation of ice arenas while implementing ventilation measures. Full article

During curling sports, the movement of the stone is affected by the quality of the ice. Therefore, the delivery team led by the ice maker hopes that the quality of the ice surface will be stable and that the athletes will always ‘read the ice’ and pay attention to the small changes in the ice surface. This phenomenon is the charm of curling. Many friction models have been proposed to describe the regularity of the curling motion. In the curling competitions of the 2022 Beijing Winter Olympic Games, the 2021 World Wheelchair Curling Championships, and the warm-up competition before, the research team installed a video image capture system in the arena to capture and record the data of the curling motion by using the depth neural network and object tracking algorithm. Further motion data research verifies the relationship between the friction coefficient and the speed. The quality control parameter of ice rink α is proposed, which is related to the influencing factors of the ice surface temperature, the ice hardness, the size of the pebble point, and the width of the curling friction band. The quality of the curling ice rink can be evaluated accurately and comprehensively by using parameter α. Based on the relationship between the friction coefficient and the speed, a physical model of horizontal sliding of the curling stone is established, which agrees well with the results of data obtained from video acquisition. Therefore, the movement distance along the rink can be accurately predicted. This paper analyzes the relationship between the long-time (the time it takes for the curling stone to travel between the two hog lines) and the stop position and that between the long-time and the split-time (the time it takes for the curling stone to travel from the back line to the hog line). Based on this result, a ruler can be established to assist athletes in estimating the sliding distance of the stone before curling throwing. This research also studies the relationship between three factors (the sliding speed in the x-direction, the angular speed, and a tiny lateral deflection speed in the y-direction) and the deviation of the stone. At the same time, there are also some interesting phenomena of the lateral deflection of the stone, such as the relationship between the lateral deflection angle tanθ and the initial lateral speed. As a result, the prediction of the curling stone’s exact final location can be realized. In summary, this article proposes an indicator for evaluating the quality of ice rinks and a physical model of curling based on the curling friction model, which is validated by data obtained from a video capture system of the 2022 Beijing Winter Olympics. The results described above have been applied in the post-match operation of the National Aquatics Center to guide the production of Olympic-grade ice surfaces and to guide athletes to “read ice” accurately during training. Full article

In China, the post-Winter Olympics era has seen the rapid development and promotion of ice rinks with air-supported membrane structures. With the rise of large indoor spectator areas in ice rinks, thermal comfort needs in spectator areas are receiving more and more attention. The satisfaction of thermal comfort needs is crucial to people’s health and well-being, so further study of the issue of thermal comfort in such spectator areas is needed. Unfortunately, models currently used to evaluate the thermal comfort of traditional building envelopes are not applicable to air-supported membrane-envelope ice rinks. Researchers need to focus on the internal thermal comfort needs of air-supported membrane envelopes for spectator areas. The aim of this research was to establish a thermal comfort model to provide exact temperature-range recommendations for spectator areas in air-supported membrane ice rinks. The indoor thermal-environment parameters of the ice rink in Harbin were measured from 2 January to 15 January 2023. To elicit data on spectators’ actual thermal sensations in the ice rink, a field questionnaire was administered. By modifying the expectancy factor, an extended predicted thermal comfort model was established. The results suggested that the operative temperature required to meet spectators’ thermal comfort needs in the case study ice rink ranged from 17 °C to 26 °C. The results of the study offer specific insights into the indoor thermal comfort needs of air-supported ice rinks and provide a more accurate temperature-setting reference for the healthy and energy-efficient development of such rinks. Full article

The ice-making process is an important factor that affects the ice quality and the energy consumption of ice rinks. An unsteady heat transfer model is established and validated for the ice-making process. The transient temperature variation and ice thickness growing characteristics during the ice-making process are analyzed. The freezing time of a water layer and the final temperature of the stabilized ice layer are quantified. The effects of ice rink structural parameters on the ice-making process are studied. The results show that the water temperature variations during the process go through three stages. The ice-growing process mainly occurs in the second stage. The ice-making process takes about 305 min–420 min for a water layer of 5 mm thickness. The reduction in the ice-making time and the decrease in the final temperature of the stabilized ice layer can be attained by reducing the water layer thickness, the surface heat flux, the cooling pipe spacing, the fluid temperature in the cooling pipe, or the top concrete thickness. Among them, the influences of the thickness of the water layer, the surface heat flux, and the fluid temperature in the cooling pipe are more significant. As the thickness of the water layer decreases from 7 mm to 3 mm, the total ice-making time decreases by about 37.6%. The ice-making time is reduced by 17.1% with the surface heat flux decreasing from 330 W/m² to 250 W/m². The ice-making time is reduced by 21.4% with the cooling pipe temperature decreasing from −15.5 °C to −19.5 °C. Full article

With the coming of the 2022 Beijing Winter Olympic Games, China’s artificial ice rink construction will be in rapid development. A parametric evaluation of the cooling pipe in a direct evaporation rink was performed by numerical simulation. The results showed that the influence of the temperature of the antifreeze pipe on the ice surface temperature can be ignored. The evaporation temperature of the working medium in the cooling pipe is between −32 °C and −22.4 °C to ensure the ice surface temperature is between −5 °C and −3 °C. With the increase in the cooling pipe spacing, the required evaporation temperature of the working medium in the cooling pipe and the uniformity of the ice surface temperature decreased. The required evaporation temperature of the working medium in the cooling pipe decreases by 1.2–1.5 °C for every 10 mm increment of spacing. With the increase in the cooling pipe diameter, the required evaporation temperature of the working medium in the cooling pipe and the uniformity of the ice surface temperature increase. The required evaporation temperature of the working medium in the cooling pipe increases by 2.2–2.9 °C for every 5 mm increment of diameter. The maximum temperature difference of ice surface temperature ranged from 0.004 °C to 0.111 °C. Full article

In the curling sport, the coefficient of friction between the curling stone and pebbled ice is crucial to predict the motion trajectory. However, the theoretical and experimental investigations on stone–ice friction are limited, mainly due to the limitations of the field measurement techniques and the inadequacy of the experimental data from professional curling rinks. In this paper, on-site measurement of the stone–ice friction coefficient in a prefabricated ice rink for the Beijing Winter Olympics curling event was carried out based on computer vision technology. Firstly, a procedure to determine the location of the curling stone was proposed using YOLO-V3 (You Only Look Once, Version 3) deep neural networks and the CSRT Object tracking algorithm. Video data was recorded during the curling stone throwing experiments, and the friction coefficient was extracted. Furthermore, the influence of the sliding velocity on the friction coefficient was discussed. Comparison with published experimental data and models and verification of the obtained results, using a sensor-based method, were conducted. Results show that the coefficient of friction (ranging from 0.006 to 0.016) decreased with increasing sliding velocity, due to the presence of a liquid-like layer. Our obtained results were consistent with the literature data and the friction model of Lozowski. In addition, the experimental results of the computer vision technique method and the accelerometer sensor method showed remarkable agreement, supporting the accuracy and reliability of our proposed measurement procedure based on deep learning. Full article

The 2022 Beijing Winter Olympics has created unprecedented opportunities for China’s commercial ice rinks, where improving consumers’ repurchase intention is essential for their high-quality development. This paper explores the mediation effect of community interactions between perceived value and commercial ice rink consumers’ repurchase intention based on the theory of perceived value. Through a questionnaire survey, we collected 347 valid questionnaire from consumers of commercial ice rinks. Based on a structural equation model, the results show that consumers’ perceived risk value significantly impacts community interactions and consumers’ repurchase intention. Perceived functional, social, and emotional values positively affect community interactions but have an insignificant impact on the consumers’ repurchase intention. Community interactions play a full mediation role between perceived emotional and social values and consumers’ repurchase intention; they play partially mediating role between consumers’ perceived risk value and repurchase intention and do not have mediating role between perceived functional value and consumers’ repurchase intention. Therefore, we provide some practical suggestions: extending commercial ice rink product lines, creating unique intellectual property systems, improving consumer sports career planning, and enhancing risk management. Full article

The construction of a prefabricated ice rink has recently attracted considerable interest owing to its detachability, short building period, and high cooling efficiency, among other benefits. Characterizing the compressive properties of an artificial ice sheet is crucial in the design, operation, and maintenance stages of the rink. Several uniaxial compressive tests were conducted in the present work to better understand the mechanical behavior of artificial ice in winter sports rinks. The artificial ice was produced using homemade equipment to simulate the real ice-making conditions in the rink. Comprehensive conditions such as strain rate, ice temperature, ice-making method, water quality, air temperature and humidity were considered in the experiments. The obtained results show that the compressive behavior of artificial ice is considerably affected by the strain rate and ice temperature, and slightly affected by the ice-making method and water quality, whereas the effects of air temperature and humidity are inconclusive. The identified range of strain rate for ductile-brittle transition was within 8.3 × 10⁻⁵ s^–1 and 8.3 × 10⁻⁴ s⁻¹, in which the strength reaches a maximum value at 1.7 × 10^–4 s⁻¹. The influencing factors on the compressive strength and effective modulus were analyzed based on the experimental observations, and fitting functions were established to describe the relationships. The results of this study will hopefully provide a reference for the design and optimization of ice rinks, particularly for prefabricated rinks. Full article