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This study investigates image-data-driven deep learning in the stability analysis of geosystems. For the purpose, the recent breakthrough in computer vision represented by the Convolutional Neural Network (CNN), which was later used as a core technique in developing Google’s AlphaGo, was studied for its capacity in assessing the stability of retaining walls. The concept used in the famous Dogs vs. Cats Kaggle challenge, in which machine learning algorithms are used to classify whether an image contains a dog or a cat, was employed. A CNN was used to analyze images for retaining walls to tell whether a wall is “cat” (safe) or “dog” (failed). For quantitative analysis, 2D images for retaining walls, organized as datasets of sizes from 500 to 200,000, were generated using a stochastic method and labeled using a traditional mechanistic method. An accuracy of 97.94% was achieved for predicting whether the retaining wall is safe via binary classifications with the CNN. Testing via the analysis of 20,000 additional images, which were independent and identically distributed, confirmed the results. Further investigations into the dataset sizes and computational power yielded quantitative insights into the influence of data and computing resources on the application of deep learning in the stability analysis of geosystems. The study, for the first time, proves the feasibility of stability analysis of geosystems with image data and provides a potential big data solution for geotechnical engineering as well as other civil engineering areas.
Zhen Liu; Shiyan Hu; Ye Sun; Behnam Azmoon. An Exploratory Investigation into Image-Data-Driven Deep Learning for Stability Analysis of Geosystems. Geotechnical and Geological Engineering 2021, 1 -16.
AMA StyleZhen Liu, Shiyan Hu, Ye Sun, Behnam Azmoon. An Exploratory Investigation into Image-Data-Driven Deep Learning for Stability Analysis of Geosystems. Geotechnical and Geological Engineering. 2021; ():1-16.
Chicago/Turabian StyleZhen Liu; Shiyan Hu; Ye Sun; Behnam Azmoon. 2021. "An Exploratory Investigation into Image-Data-Driven Deep Learning for Stability Analysis of Geosystems." Geotechnical and Geological Engineering , no. : 1-16.
This paper presents a comparison study between methods of deep learning as a new category of slope stability analysis, built upon the recent advances in artificial intelligence and conventional limit equilibrium analysis methods. For this purpose, computer code was developed to calculate the factor of safety (FS) using four limit equilibrium methods: Bishop’s simplified method, the Fellenius method, Janbu’s simplified method, and Janbu’s corrected method. The code was verified against Slide2 in RocScience. Subsequently, the average FS values were used to approximate the “true” FS of the slopes for labeling the images for deep learning. Using this code, a comprehensive dataset of slope images with wide ranges of geometries and soil properties was created. The average FS values were used to label the images for implementing two deep learning models: a multiclass classification and a regression model. After training, the deep learning models were used to predict the FS of an independent set of slope images. Finally, the performance of the models was compared to that of the conventional methods. This study found that deep learning methods can reach accuracies as high as 99.71% while improving computational efficiency by more than 18 times compared with conventional methods.
Behnam Azmoon; Aynaz Biniyaz; Zhen Liu. Evaluation of Deep Learning against Conventional Limit Equilibrium Methods for Slope Stability Analysis. Applied Sciences 2021, 11, 6060 .
AMA StyleBehnam Azmoon, Aynaz Biniyaz, Zhen Liu. Evaluation of Deep Learning against Conventional Limit Equilibrium Methods for Slope Stability Analysis. Applied Sciences. 2021; 11 (13):6060.
Chicago/Turabian StyleBehnam Azmoon; Aynaz Biniyaz; Zhen Liu. 2021. "Evaluation of Deep Learning against Conventional Limit Equilibrium Methods for Slope Stability Analysis." Applied Sciences 11, no. 13: 6060.
This study addresses a key issue that prevents the wide application of the novel predominant natural frequency (PNF)‐based method for bridge scour monitoring, which is also applicable to the frequency‐based health monitoring of other structures with soil–structure interaction. This issue is that no theory or method is currently available to guide the prediction of scour depths based on measured PNFs. The most feasible way is to first measure a few scour depths and their corresponding PNFs for obtaining the PNF–scour depth relationship, which is termed the bridge scour characteristic curve (BSCC) in this study, and then use this BSCC to predict future scour depths with measured PNFs. This study provides a comprehensive investigation into the BSCC and proposes a simulation‐based optimization approach, in which the whole BSCC, that is, from light to severe scour conditions, can be predicted with a few measured scour depth–PNF data points (e.g., 2–4) within a small scour depth range (e.g., 0.2–0.5 m). The proposed approach integrates the Winkler‐based numerical model into a global optimization technique to predict the whole BSCC to avoid the use of a closed‐form BSCC function, which may not exist. Additionally, the approach can be used to estimate the modulus of subgrade reaction, which is very hard to obtain at real bridges. The performance of the proposed approach was evaluated using several practical scenarios with realistic multilayered soil conditions. We found that the proposed approach is accurate for predicting the whole BSCC with four measured points or even less, regardless of the scour severity for the measurements and the number of the soil layer. For applications, the influence of random errors in the measurements of PNFs and scour depths was investigated and concluded to be negligible. This study sets a solid cornerstone for the maturation of the PNF‐based scour monitoring method and other frequency‐based structural health monitoring methods with soil–structure interaction.
Ting Bao; Zhen (Leo) Liu. Bridge scour characteristic curve for natural frequency‐based bridge scour monitoring using simulation‐based optimization. Structural Control and Health Monitoring 2021, 28, e2773 .
AMA StyleTing Bao, Zhen (Leo) Liu. Bridge scour characteristic curve for natural frequency‐based bridge scour monitoring using simulation‐based optimization. Structural Control and Health Monitoring. 2021; 28 (8):e2773.
Chicago/Turabian StyleTing Bao; Zhen (Leo) Liu. 2021. "Bridge scour characteristic curve for natural frequency‐based bridge scour monitoring using simulation‐based optimization." Structural Control and Health Monitoring 28, no. 8: e2773.
Pavement conditions including pavement temperatures, freezing and thawing depths, and the consequent mechanical performance are the key to the performance and longevity of the pavement. For example, thaw-weakening is a major cause of pavement damage in seasonally-frozen areas covering half of the U.S., leading to huge financial costs for taxpayers. In recent years, the damage has been lessened due to improved practices with Spring Load Restriction (SLR) policies. However, prevalent SLR date prediction methods/tools are still primitive from the perspective of information technology. Such methods/tools are obtained and/or implemented manually with small amounts of data, labor-intensive observations, and/or subjective experience. The paper reports what has been learned from a recent project supported by the Michigan Department of Transporation for the development of a web-based pavement condition prediction and SLR decision support tool: a web-based app called MDOTSLR. MDOTSLR enables access to much more data with little latency and automates data acquisition, processing, and decision making. In this paper, the data innovations and new models that support the functions of the tool will be first introduced. Followed will be the major functions (or services) of the app including software engineering details. Compared with traditional tools without web delivery, this web-based tool automates the acquisition and processing of weather data, GIS data, road weather information system data, and field measurements in real time and thus enables more accurate and convenient SLR predictions. The tool can be easily extended or modified for other road agencies for immediate financial savings in road maintenance and less disturbance to local transportation and economy.
Zhen (Leo) Liu; John Bland; Ting Bao; Michael Billmire; Aynaz Biniyaz. Real-time computing of pavement conditions in cold regions: A large-scale application with road weather information system. Cold Regions Science and Technology 2021, 184, 103228 .
AMA StyleZhen (Leo) Liu, John Bland, Ting Bao, Michael Billmire, Aynaz Biniyaz. Real-time computing of pavement conditions in cold regions: A large-scale application with road weather information system. Cold Regions Science and Technology. 2021; 184 ():103228.
Chicago/Turabian StyleZhen (Leo) Liu; John Bland; Ting Bao; Michael Billmire; Aynaz Biniyaz. 2021. "Real-time computing of pavement conditions in cold regions: A large-scale application with road weather information system." Cold Regions Science and Technology 184, no. : 103228.
Spring Load Restriction (SLR) policies have been widely implemented in many countries to reduce the cost of road repair for freeze-thaw induced damages in cold regions occurring in the spring thawing season. In most SLR policies, accurate predictions of the Freezing Depth (FD) and Thawing Depth (TD) are very critical because both FD and TD directly determine the dates for the SLR initiation and removal. In this study, we propose a new constrained optimization approach to predict FD and TD and evaluate this approach for making SLR decisions with field measurements collected at four sites during two adjacent year cycles. The evaluation results showed that constrained optimization can not only accurately predict FD and TD with a determination coefficient of higher than 0.91 for most sites, but enable FD to meet TD in the thawing season for accurate SLR-decision making, which, however, cannot be achieved using non-constrained optimization widely adopted in the literature. We also discuss the accuracy of using a Thawing Index (TI)/Freezing Index (FI) ratio of 0.3 that still has been used by several agencies in the U.S. to determine the removal date of SLR. Our results indicated that on the true SLR removal dates, a TI/FI ratio is not equal even close to 0.3 for most sites. By comparison, a TI/FI ratio of 0.3 will be less accurate than the FD and TD prediction model for SLR decision-making. The methodology reported in this study is easy to use and implement for road engineers and the insights will help make accurate SLR decisions to prevent roads in cold regions from freeze-thaw induced damages.
Ting Bao; Behnam Azmoon; Zhen (Leo) Liu. Freeze-thaw depth prediction with constrained optimization for spring load restriction. Transportation Geotechnics 2020, 26, 100419 .
AMA StyleTing Bao, Behnam Azmoon, Zhen (Leo) Liu. Freeze-thaw depth prediction with constrained optimization for spring load restriction. Transportation Geotechnics. 2020; 26 ():100419.
Chicago/Turabian StyleTing Bao; Behnam Azmoon; Zhen (Leo) Liu. 2020. "Freeze-thaw depth prediction with constrained optimization for spring load restriction." Transportation Geotechnics 26, no. : 100419.
Geothermal applications with waste water in abandoned mines are a sustainable way of recycling wastes in abandoned facilities for utilizing clean energy. Thermohaline stratification in mine water is significant to this energy application, because it dominates the heat and mass transport in the mine-water-geologic-formation system and consequently determines the efficiency and sustainability of geothermal energy systems. This study addresses six unresolved issues for understanding the formation and evolution of thermohaline stratification via multiphysics simulations, including effects of key transport parameters on thermohaline stratification; mechanisms underlying layer-merging; effects of the buoyancy ratio on thermohaline stratification, and predictions of the initial distributions of temperature and salinity for thermohaline stratification. Our results showed that the effective kinematic viscosity is the most dominant transport parameter to determine the layer-merging speed and layer number of thermohaline stratification, where seven more thermohaline stratification layers could be observed if two orders of magnitude of this parameter are increased. For layer-merging, relatively “weak” interfaces, which have a small buoyancy ratio across the neighboring layers, disappear and are eroded first. Our results also revealed that the buoyancy ratio determines the layer number, where increasing the buoyancy ratio from 2.16 to 4 can induce twenty more layers. The initially linear temperature and salinity distributions in mine water are needed for predicting the present and future thermohaline stratification, especially the energy recovery. To meet this need, an approach was proposed to accurately predict such initial distributions via back-calculating field measurements. This study provides insights into understanding the key energy transport mechanisms in mine water and recommendations for facilitating future implementations of geothermal energy recovery with mine water dominated by thermohaline stratification.
Ting Bao; Han Cao; Yinghong Qin; Guosheng Jiang; Zhen (Leo) Liu. Critical insights into thermohaline stratification for geothermal energy recovery from flooded mines with mine water. Journal of Cleaner Production 2020, 273, 122989 .
AMA StyleTing Bao, Han Cao, Yinghong Qin, Guosheng Jiang, Zhen (Leo) Liu. Critical insights into thermohaline stratification for geothermal energy recovery from flooded mines with mine water. Journal of Cleaner Production. 2020; 273 ():122989.
Chicago/Turabian StyleTing Bao; Han Cao; Yinghong Qin; Guosheng Jiang; Zhen (Leo) Liu. 2020. "Critical insights into thermohaline stratification for geothermal energy recovery from flooded mines with mine water." Journal of Cleaner Production 273, no. : 122989.
This paper reports a comprehensive study including detailed experimental, theoretical, and numerical analyses to evaluate the performance of two predominant soil-structure interaction models, that is, the Winkler model and Pasternak model, in predicting the predominant natural frequency (PNF) of structures partially embedded in soils. For the evaluation, PNF-based scour detection, a nondestructive testing technique that has been receiving increasing attention, was adopted. First, a series of lab experiments was conducted using idealized piers partially embedded in two representative soils, that is, a sand and a clay, to measure the PNF-scour depth relationship. Next, a mathematical model was established and numerically implemented to predict the PNF of the idealized piers for scour detection. The soil-structure interaction was formulated using the Winkler model, which only considers the modulus of subgrade reaction for soils, and the Pasternak model, which considers the shear interaction in addition to the modulus. The numerically computed PNFs were then compared with those from the experiments in this study and a documented field test. Our results clearly show that when structures are partially embedded in soils, the Winkler model yields a better PNF prediction than the Pasternak model, regardless of the types of test piers and soils. This finding is different from those obtained in the dynamic response of structures resting on or fully embedded in an elastic foundation (i.e., not partially embedded), where the Pasternak model yields more realistic results than the Winkler model because of its consideration of the continuity of foundation media via the shear interaction. Because of the shear interaction, the PNFs predicted with the Pasternak model in this study are about 24%–38% and 31%–39% higher than the predictions with the Winkler model and the measured PNFs, respectively.
Ting Bao; Zhen Liu. Evaluation of Winkler Model and Pasternak Model for Dynamic Soil-Structure Interaction Analysis of Structures Partially Embedded in Soils. International Journal of Geomechanics 2020, 20, 04019167 .
AMA StyleTing Bao, Zhen Liu. Evaluation of Winkler Model and Pasternak Model for Dynamic Soil-Structure Interaction Analysis of Structures Partially Embedded in Soils. International Journal of Geomechanics. 2020; 20 (2):04019167.
Chicago/Turabian StyleTing Bao; Zhen Liu. 2020. "Evaluation of Winkler Model and Pasternak Model for Dynamic Soil-Structure Interaction Analysis of Structures Partially Embedded in Soils." International Journal of Geomechanics 20, no. 2: 04019167.
Understanding the soil heat and moisture transport is significant for assessing the living condition of vegetation and microorganisms in soils. Numerous studies have been conducted to understand the coupled soil heat and moisture transport under “normal” environmental conditions; while this coupled transport under extremely high-temperature conditions caused by surface wildfires is little understood. Particularly, 3D modeling of such coupled transport is absent. Here, we develop a 3D model to understand more realistic characteristics of the soil heat and moisture transport beneath a surface fire. With the 3D model, we investigate the lateral transport of soil heat and moisture in a 3D space, the influence of a surface fire on soil moisture and temperature conditions in neighboring regions without fires, and the effect of initial water contents on the delay of soil heating. The modeling results showed that the lateral transport leads to an obvious difference in soil temperature and moisture between the inside and border area of the fire region. Such a difference cannot be considered with a 1D model widely used in existing studies. For the initial water content effect, we confirmed that a high initial water content delays the soil heating to cooler regions at deeper soil depths during the late stage of soil heating. Our results also showed that a surface fire significantly changes soil heat and moisture in the no-fire region neighboring to the simulated fire. At the location 50 m away from the fire region, the soil temperature and moisture in upper soil layers can increase to over 85 °C and decrease to 0.006 m3 m−3 within 5 h, respectively. This study provides important insights, which are useful for fire management but have not been reported before, for understanding more physically realistic characteristics of the 3D soil heat and moisture transport beneath a surface fire in both the fire and no-fire regions.
Ting Bao; Si Liu; Yinghong Qin; Zhen (Leo) Liu. 3D modeling of coupled soil heat and moisture transport beneath a surface fire. International Journal of Heat and Mass Transfer 2019, 149, 119163 .
AMA StyleTing Bao, Si Liu, Yinghong Qin, Zhen (Leo) Liu. 3D modeling of coupled soil heat and moisture transport beneath a surface fire. International Journal of Heat and Mass Transfer. 2019; 149 ():119163.
Chicago/Turabian StyleTing Bao; Si Liu; Yinghong Qin; Zhen (Leo) Liu. 2019. "3D modeling of coupled soil heat and moisture transport beneath a surface fire." International Journal of Heat and Mass Transfer 149, no. : 119163.
Ting Bao; Zhen Liu; John Bland. A multivariate freezing-thawing depth prediction model for spring load restriction. Cold Regions Science and Technology 2019, 167, 1 .
AMA StyleTing Bao, Zhen Liu, John Bland. A multivariate freezing-thawing depth prediction model for spring load restriction. Cold Regions Science and Technology. 2019; 167 ():1.
Chicago/Turabian StyleTing Bao; Zhen Liu; John Bland. 2019. "A multivariate freezing-thawing depth prediction model for spring load restriction." Cold Regions Science and Technology 167, no. : 1.
Geothermal energy from flooded mines is a high-potential clean energy resource that can provide heating to large communities with power comparable to small-scale power plants. The transient energy recovery process for utilizing this energy resource, however, has not been well understood, especially those involving the heat transfer in mine water with the widely-observed layering phenomenon where the temperature and salinity are stratified. To better understand the transient energy recovery process considering such a layering phenomenon, this study presents a numerical analysis of transient heat extraction from a flooded mine shaft with mine water dominated by thermohaline stratification. The numerical analysis is conducted based on a realistic case using an open-loop heat pump system. The simulation results show that, when normal pumping rates are used, the water temperature available to heat pumps almost keeps unchanged because the transient energy recovery using an open-loop system only leads to a temperature reduction of 0.2–0.3 K. By comparison, the simulation results in this study are consistent with those measured from real demonstration projects, showing the accuracy of the simulations and confirming the high efficiency and reliability of this energy innovation. The modeling results in this study also reveal that heat extraction does not affect the stability of thermohaline stratification when normal pumping rates, e.g.,0.0014–0.03 m3/s, are adopted, but will break thermohaline stratification with pumping rates over a hundred times of the commonly-used ones. These findings provide guidelines for future applications at different scales, and the methodology reported in this study can be used to assist the design of the energy recovery systems.
Ting Bao; Zhen (Leo) Liu. Geothermal energy from flooded mines: Modeling of transient energy recovery with thermohaline stratification. Energy Conversion and Management 2019, 199, 111956 .
AMA StyleTing Bao, Zhen (Leo) Liu. Geothermal energy from flooded mines: Modeling of transient energy recovery with thermohaline stratification. Energy Conversion and Management. 2019; 199 ():111956.
Chicago/Turabian StyleTing Bao; Zhen (Leo) Liu. 2019. "Geothermal energy from flooded mines: Modeling of transient energy recovery with thermohaline stratification." Energy Conversion and Management 199, no. : 111956.
Water-retaining pavements are optional and effective to mitigate urban heat island as they stay cool by holding rainwater at the surface layer for evaporation cooling. However, excessive rainfall falling on such pavements will overflow and thus contribute to flooding. Here, we report a novel drainable water-retaining paver block for mitigating urban heat island and simultaneously reducing runoff. The albedo, temperature, water-retaining capacity, and outflow sensible heat of this novel paver block were measured and compared with those of a dense block and a pervious block. The permeability of the water-retaining block was also measured to examine whether this paver block can avoid overflow during heavy rain. Our results showed that the temperature of the water-retaining block in the wet condition can be reduced by 13 °C in the daytime and 3 °C at night, which indicates its good performance of cooling the local air temperature. Our results also indicated that the permeability of the water-retaining block is two orders higher than the precipitation rate of heavy rain, which reveals the excellent performance of quickly draining the excessive water in case of heavy rain.
Ting Bao; Zhen (Leo) Liu; Xingui Zhang; Yuhui He. A drainable water-retaining paver block for runoff reduction and evaporation cooling. Journal of Cleaner Production 2019, 228, 418 -424.
AMA StyleTing Bao, Zhen (Leo) Liu, Xingui Zhang, Yuhui He. A drainable water-retaining paver block for runoff reduction and evaporation cooling. Journal of Cleaner Production. 2019; 228 ():418-424.
Chicago/Turabian StyleTing Bao; Zhen (Leo) Liu; Xingui Zhang; Yuhui He. 2019. "A drainable water-retaining paver block for runoff reduction and evaporation cooling." Journal of Cleaner Production 228, no. : 418-424.
Geothermal energy recovery from abandoned flooded mines provides a viable high-tech solution to reuse the abandoned mines for meeting humanity’s energy needs worldwide in an environmental, economic, and reliable way. This unique energy application with mine water in the U.S., however, has not been reported. This study reports on a real geothermal energy application in the U.S. for the use of water in flooded mines for house heating. First, the site exploration of a typical flooded copper mine in the Upper Peninsula of Michigan is presented to discuss three essential components of the proposed large-scale energy application, i.e., bedrock geology, mining background, and energy reserve analyses. Then, the key technical details and data monitoring of a demonstration project for the use of mine water for heating a 15,000 ft2 (1394 m2) building are introduced. For the energy reserve, energy reserve analyses were conducted considering the renewability of the thermal energy in the natural system, which was usually neglected in the literature. The analyses revealed that the annual extractable energy from the explored flooded mine with the energy replenishment is comparable to the annual energy generated by a small-scale power station, which can support over 82,000 households. The results from the demonstration project indicated that house heating with geothermal energy via the mine water is the most efficient and the second most economical heating option in very unfavorable conditions with a high electricity price and a low annual average air temperature. The intention of this study is to share the background and practical knowledge that has been learned from this ongoing project to guide future real installations in other mining areas with deep flooded mines in the U.S. and around the world.
Ting Bao; Jay Meldrum; Christopher Green; Stanley Vitton; Zhen Liu; Kelsey Bird. Geothermal energy recovery from deep flooded copper mines for heating. Energy Conversion and Management 2019, 183, 604 -616.
AMA StyleTing Bao, Jay Meldrum, Christopher Green, Stanley Vitton, Zhen Liu, Kelsey Bird. Geothermal energy recovery from deep flooded copper mines for heating. Energy Conversion and Management. 2019; 183 ():604-616.
Chicago/Turabian StyleTing Bao; Jay Meldrum; Christopher Green; Stanley Vitton; Zhen Liu; Kelsey Bird. 2019. "Geothermal energy recovery from deep flooded copper mines for heating." Energy Conversion and Management 183, no. : 604-616.
The concept of detecting scour severity by analyzing the change in the Predominant Natural Frequency (PNF) of a bridge pier has been gaining increasing interest in recent years. Previous studies primarily focus on this topic using less cohesive soils such as highly erodible sands, whereas no discussions have been reported on the influence of soil characteristics, especially those of cohesive soils, on the PNF. This missing knowledge gap is critical for this application as cohesive soils are an essential part of the soil-pier interaction to determine PNFs. This study aims to fill this knowledge gap by investigating three issues that are related to soil characteristics: 1) the effect of soil types on the PNF variation; 2) the questionable issue regarding the pier diameter effect for soil-pier dynamic modeling using the Vesic analytical expression; and 3) contradictory statements in the existing studies regarding the influence of the soil’s elastic modulus on the PNF variation. For the purpose, a series of lab-scale tests is first conducted, and a Winkler-based numerical model is then developed and validated against the experimental results to investigate the effect of soil characteristics on the PNFs measured from systems with cohesive soils and those with less cohesive soils. We found that the soil characteristics affect the PNF by providing a different lateral stiffness to the soil-pier interaction. The strength of the soil-pier interaction mainly depends on the lateral stiffness of each type of soils. In-depth discussions are also made to clarify the pier diameter effect on the predicted PNFs from both less cohesive and cohesive soils. It was clarified that the distribution of the soil’s elastic modulus determines whether the pier diameter effect needs to be considered using the Vesic analytical expression. Further simulations are finally conducted with more complex and realistic field soil conditions to mediate the contradictory statements regarding the influence of the soil’s elastic modulus. The simulation results indicated that the soil’s elastic modulus significantly influences the PNFs. The PNF variations differ under different elastic moduli of soils and distributions of elastic moduli with soil depths.
Ting Bao; Zhen (Leo) Liu; Kelsey Bird. Influence of soil characteristics on natural frequency-based bridge scour detection. Journal of Sound and Vibration 2019, 446, 195 -210.
AMA StyleTing Bao, Zhen (Leo) Liu, Kelsey Bird. Influence of soil characteristics on natural frequency-based bridge scour detection. Journal of Sound and Vibration. 2019; 446 ():195-210.
Chicago/Turabian StyleTing Bao; Zhen (Leo) Liu; Kelsey Bird. 2019. "Influence of soil characteristics on natural frequency-based bridge scour detection." Journal of Sound and Vibration 446, no. : 195-210.
This study addresses a key scientific issue that remains unresolved in the past three decades for recovering geothermal energy from flooded mines. This issue is that no scientific explanation is available for the layering phenomenon of both temperature and salinity in large bodies of subterranean water (e.g., mine water), i.e., thermohaline stratification, which is commonly observed in mine water. Such a layering phenomenon, however, is very significant to the geothermal application by determining the temperature distribution and consequently the energy reserve and efficiency. For this purpose, multiphysics simulation with unique non-isothermal and non-isosolutal hydrodynamics is adopted to predict the formation and evolution of thermohaline stratifications in large bodies of mine water. The multiphysics simulation, for the first time, succeeded in reproducing the formation and evolution of thermohaline stratifications with a theory assuming lateral double-diffusive intrusions to mine water. The simulation results revealed that the evolution of thermohaline stratifications involves the layer-merging event, in which several small layers gradually merge to form layers with a larger thickness. The results also indicated that the buoyancy ratio is a key parameter for producing clear thermohaline stratifications in large bodies of mine water and its critical value was suggested to be 1.0. To successfully reproduce thermohaline stratifications, the required condition was concluded to be the lateral heat flux with a difference between the lateral heat fluxes, while the lateral salinity flux was not required. It is the first time, to the best of our knowledge, that the layering phenomenon in large-scale subterranean water bodies has been successfully reproduced and explained scientifically. This study will provide a solid scientific basis for the efficient and sustainable use of large bodies of subterranean water in flooded mines for geothermal energy recovery.
Ting Bao; Zhen (Leo) Liu. Thermohaline stratification modeling in mine water via double-diffusive convection for geothermal energy recovery from flooded mines. Applied Energy 2019, 237, 566 -580.
AMA StyleTing Bao, Zhen (Leo) Liu. Thermohaline stratification modeling in mine water via double-diffusive convection for geothermal energy recovery from flooded mines. Applied Energy. 2019; 237 ():566-580.
Chicago/Turabian StyleTing Bao; Zhen (Leo) Liu. 2019. "Thermohaline stratification modeling in mine water via double-diffusive convection for geothermal energy recovery from flooded mines." Applied Energy 237, no. : 566-580.
Xian Li; Ye Sun; Zhen Liu; Matthew Portfleet. A wearable system for situational awareness estimation in underground mines. Proceedings of the 2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies 2018, 1 .
AMA StyleXian Li, Ye Sun, Zhen Liu, Matthew Portfleet. A wearable system for situational awareness estimation in underground mines. Proceedings of the 2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies. 2018; ():1.
Chicago/Turabian StyleXian Li; Ye Sun; Zhen Liu; Matthew Portfleet. 2018. "A wearable system for situational awareness estimation in underground mines." Proceedings of the 2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies , no. : 1.
This paper introduces the scientific part of a large-scale study in the Upper Peninsula (U.P.) of Michigan, a historical mining area, for exploring the water in deep abandoned copper mines as a geothermal energy resource. The main focus of the paper is placed on the scientific understanding of the natural mine water-geologic formation system, especially the transport of heat and mass in this large-scale natural system, which is critical to the efficiency and sustainability of the energy renovation. For this purpose, a field study involving measurements of temperatures and chemicals in a local mine shaft in the U.P. is conducted to reveal the major issue in recovering geothermal energy in the water from the shaft, i.e., the temperature distribution. Water samples are also collected in situ to investigate the distribution and concentrations of major chemicals. Afterward, a theoretical framework for the thermo-hydrodynamic process in the mine water coupled with heat transfer in the surrounding geologic formations is developed to outline a mathematical description for studying the scientific issue. Simulations are finally conducted, based on the real geologic information, to preliminarily investigate the quasi-equilibrium water movement in this local mine shaft due to geothermal gradients to provide insights into the phenomena observed in the field study.
Ting Bao; Zhen Liu; Jay Meldrum; Christopher Green; Pengfei Xue; Stanley Vitton. Field tests and multiphysics analysis of a flooded shaft for geothermal applications with mine water. Energy Conversion and Management 2018, 169, 174 -185.
AMA StyleTing Bao, Zhen Liu, Jay Meldrum, Christopher Green, Pengfei Xue, Stanley Vitton. Field tests and multiphysics analysis of a flooded shaft for geothermal applications with mine water. Energy Conversion and Management. 2018; 169 ():174-185.
Chicago/Turabian StyleTing Bao; Zhen Liu; Jay Meldrum; Christopher Green; Pengfei Xue; Stanley Vitton. 2018. "Field tests and multiphysics analysis of a flooded shaft for geothermal applications with mine water." Energy Conversion and Management 169, no. : 174-185.
The phase composition curve of frozen soils is a fundamental relationship in understanding permafrost and seasonally frozen soils. However, due to the complex interplay between adsorption and capillarity, a clear physically based understanding of the phase composition curve in the low temperature range, i.e.,
Chao Zhang; Zhen Liu; Peng Deng. Using molecular dynamics to unravel phase composition behavior of nano-size pores in frozen soils: Does Young–Laplace equation apply in low temperature range? Canadian Geotechnical Journal 2018, 55, 1144 -1153.
AMA StyleChao Zhang, Zhen Liu, Peng Deng. Using molecular dynamics to unravel phase composition behavior of nano-size pores in frozen soils: Does Young–Laplace equation apply in low temperature range? Canadian Geotechnical Journal. 2018; 55 (8):1144-1153.
Chicago/Turabian StyleChao Zhang; Zhen Liu; Peng Deng. 2018. "Using molecular dynamics to unravel phase composition behavior of nano-size pores in frozen soils: Does Young–Laplace equation apply in low temperature range?" Canadian Geotechnical Journal 55, no. 8: 1144-1153.
This paper reports on the first large-scale project in the U.S. for utilizing water from abandoned mines for geothermal applications. This project proved the high potential of turning water in deep abandoned mines into a renewable energy resource, which is safer, greener, and more abundant than other conventional low-enthalpy geothermal applications. In this paper, a real demonstration project is introduced for recovering geothermal energy from the mine water for heating and cooling to a 1022 m2 building in the Upper Peninsula of Michigan. A field test in a mine shaft with a depth of 1219.2 m is then presented to show the key issue in the use of the mine water as a geothermal resource: the temperature distribution. Complex multiphysics simulation with unique non-isothermal hydrodynamics is conducted to provide a physical explanation for the data obtained in the field test. Simulation results shed light on the scientific myth regarding water stratification and energy flow observed in the field study.
Ting Bao; Zhen Liu; Jay Meldrum; Christopher Green. Large-Scale Mine Water Geothermal Applications with Abandoned Mines. Proceedings of GeoShanghai 2018 International Conference: Tunnelling and Underground Construction 2018, 685 -695.
AMA StyleTing Bao, Zhen Liu, Jay Meldrum, Christopher Green. Large-Scale Mine Water Geothermal Applications with Abandoned Mines. Proceedings of GeoShanghai 2018 International Conference: Tunnelling and Underground Construction. 2018; ():685-695.
Chicago/Turabian StyleTing Bao; Zhen Liu; Jay Meldrum; Christopher Green. 2018. "Large-Scale Mine Water Geothermal Applications with Abandoned Mines." Proceedings of GeoShanghai 2018 International Conference: Tunnelling and Underground Construction , no. : 685-695.
It has been widely accepted in scientific communities that water confined in porous materials gradually freezes from large pores to small pores at subfreezing temperatures (< 0 °C), though we still describe a soil as frozen or unfrozen in engineering practice and daily life. Therefore, it is more accurate to say “how frozen” instead of “whether frozen.” This gradual freezing process is temperature-dependent because water in pores of different sizes has different energy levels, which requires different temperatures for its phase transition, leading to a relationship between unfrozen water content and temperature in soils. However, the understanding of this relationship, i.e., the Phase Composition Curves (PCC), is still incomplete, especially in the low-temperature range. We still lack answers to even the most fundamental questions for frozen soils and their PCCs: (1) How much pore water could be frozen? (2) How do capillarity and adsorption control the freezing of pore water? This study investigates two basic physical mechanisms, i.e., unfreezable threshold and adsorption, for their dominant roles in the low-temperature range of the PCC. To quantify the effects of the unfreezable threshold, molecular dynamics simulation was employed to identify the unfreezable threshold of cylindrical pores. The simulation results, for the first time, revealed that the unfreezable threshold corresponds to a pore diameter of 2.3 ± 0.1 nm and is independent of the wettability of the solid substrates. Combining this unfreezable threshold with a modified Gibbs–Thomson equation, a mathematical model was proposed to predict the melting temperature in pores of different sizes, which considers both unfreezable threshold and adsorption. Comparisons of the results calculated with the new model and other two conventional equations against experimental results indicated that the model can improve conventional equations which have been used for centuries by including the two mechanisms, which significantly improved our understanding of frozen soils.
Chao Zhang; Zhen Liu. Freezing of water confined in porous materials: role of adsorption and unfreezable threshold. Acta Geotechnica 2018, 13, 1203 -1213.
AMA StyleChao Zhang, Zhen Liu. Freezing of water confined in porous materials: role of adsorption and unfreezable threshold. Acta Geotechnica. 2018; 13 (5):1203-1213.
Chicago/Turabian StyleChao Zhang; Zhen Liu. 2018. "Freezing of water confined in porous materials: role of adsorption and unfreezable threshold." Acta Geotechnica 13, no. 5: 1203-1213.
This book summarizes, defines, and contextualizes multiphysics with an emphasis on porous materials. It covers various essential aspects of multiphysics, from history, definition, and scope to mathematical theories, physical mechanisms, and numerical implementations. The emphasis on porous materials maximizes readers’ understanding as these substances are abundant in nature and a common breeding ground of multiphysical phenomena, especially complicated multiphysics. Dr. Liu’s lucid and easy-to-follow presentation serve as a blueprint on the use of multiphysics as a leading edge technique for computer modeling. The contents are organized to facilitate the transition from familiar, monolithic physics such as heat transfer and pore water movement to state-of-the-art applications involving multiphysics, including poroelasticity, thermohydro-mechanical processes, electrokinetics, electromagnetics, fluid dynamics, fluid structure interaction, and electromagnetomechanics. This volume serves as both a general reference and specific treatise for various scientific and engineering disciplines involving multiphysics simulation and porous materials.• Presents the essential components of multiphysics along with innovative numerical modeling techniques in the context of porous materials; • Structured for a wide range of readers from those new to the field to experts, instructors, researchers, software developers, and modelers from many scientific and engineering disciplines; • Organized using a practical approach that combines a logical presentation of theories with illustrative hands-on example problems; • Reinforces multiphysics concepts with applications demonstrating the use of common software to solve representative problems.
Zhen Liu. Multiphysics in Porous Materials. Multiphysics in Porous Materials 2018, 1 .
AMA StyleZhen Liu. Multiphysics in Porous Materials. Multiphysics in Porous Materials. 2018; ():1.
Chicago/Turabian StyleZhen Liu. 2018. "Multiphysics in Porous Materials." Multiphysics in Porous Materials , no. : 1.