Browsing by Author "Liu, Jian"

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    Aging effect on successful reactive-recovery from unexpected slips: a 3D lower extremity joint moment analysis
    Liu, Jian (Virginia Tech, 2004-09-14)
    The objective of the proposed study was to perform three-dimensional (3D) inverse dynamics analysis to determine lower extremity (ankle, knee and hip) joint moments on previously collected slip perturbation experimental data. In addition, the aging effect on the joint moment generation in both normal walking and reactive-recovery conditions was examined. Dataset collected during previous slip and fall experiments, which were conducted in a typical gait analysis setting, were analyzed in current study. All the participants were subjected to the screening criteria, which defined the successful reactive-recovery (i.e. non-fall trials) based on slip distance, sliding heel velocity, whole body COM velocity, and motion pictures. Nine young and nine old healthy participants, who were identified possessing representative trials, were involved as participants in current study. A local coordinate system was constructed on each joint and each segment of the lower extremity based on available landmarks using the Gram-Schmidt orthogonalization algorithm. 3D inverse dynamics was implemented to obtained lower extremity joint moments. Magnitude and timing of obtained joint moment patterns during stance phase were subjected to one and two-way analysis of covariance (ANCOVA) with walking velocity as covariate. The aging effect and gait condition effect were evaluated. Increases in peak joint moment, peak joint power, and joint moment generation ratio were detected in successful reactive-recovery. Distinct age-related joint moment generation strategy was observed through findings of peak joint moment ratio and joint moment generation rate. The elderly, who were able to reactive recover, were found to be as rapid as their younger counterparts in terms of initiating and developing reactive joint moment. It was concluded that ankle joint was critical in balance recovery while hip joint assumed the major responsibility of balance maintenance of upper body during successful reactive-recovery. Increased demand on muscle strength during balance recovery lead to the distinct joint moment generation strategy adopted by the elderly, and confirmed the necessity of lower extremity strength training. In addition, implementation of 3D joint moment analysis was justified in current study and was suggested in future slip and fall researches.
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    Ambulatory Fall Event Detection with Integrative Ambulatory Measurement (IAM) Framework
    Liu, Jian (Virginia Tech, 2008-08-29)
    Injuries associated with fall accidents pose a significant health problem to society, both in terms of human suffering and economic losses. Existing fall intervention approaches are facing various limitations. This dissertation presented an effort to advance indirect type of injury prevention approach. The overall objective was to develop a new fall event detection algorithm and a new integrative ambulatory measurement (IAM) framework which could further improve the fall detection algorithm's performance in detecting slip-induced backward falls. This type of fall was chosen because slipping contributes to a major portion of fall-related injuries. The new fall detection algorithm was designed to utilize trunk angular kinematics information as measured by Inertial Measurement Units (IMU). Two empirical studies were conducted to demonstrate the utility of the new detection algorithm and the IAM framework in fall event detection. The first study involved a biomechanical analysis of trunk motion features during common Activities of Daily Living (ADLs) and slip-induced falls using an optical motion analysis system. The second study involved collecting laboratory data of common ADLs and slip-induced falls using ambulatory sensors, and evaluating the performance of the new algorithm in fall event detection. Results from the current study indicated that the backward falls were characterized by the unique, simultaneous occurrence of an extremely high trunk extension angular velocity and a slight trunk extension angle. The quadratic form of the two-dimensional discrimination function showed a close-to-ideal overall detection performance (AUC of ROCa = 0.9952). The sensitivity, specificity, and the average response time associated with the specific configuration of the new algorithm were found to be 100%, 95.65%, and 255ms, respectively. The individual calibration significantly improved the response time by 2.4% (6ms). Therefore, it was concluded that slip-induced backward fall was clearly distinguishable from ADLs in the trunk angular phase plot. The new algorithm utilizing a gyroscope and orientation sensor was able to detect backward falls prior to the impact, with a high level of sensitivity and specificity. In addition, individual calibration provided by the IAM framework was able to further enhance the fall detection performance.
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    Balanced asphalt mix design and pavement distress predictive models based on machine learning
    Liu, Jian (Virginia Tech, 2022-09-22)
    Traditional asphalt mix design procedures are empirical and need random and lengthy trials in a laboratory, which can cost much labor, material resources, and finance. The initiative (Material Genome initiative) was launched by President Obama to revitalize American manufacturing. To achieve the objective of the MGI, three major tools which are computational techniques, laboratory experiments, and data analytics methods are supposed to have interacted. Designing asphalt mixture with laboratory and computation simulation methods has developed in recent decades. With the development of data science, establishing a new design platform for asphalt mixture based on data-driven methods is urgent. A balanced mix design, defined as an asphalt mix design simultaneously considering the ability of asphalt mixture to resist pavement distress, such as rutting, cracking, IRI (international roughness index), etc., is still the trend of future asphalt mix design. The service life of asphalt pavement mainly depends on the properties of the asphalt mixture. Whether asphalt mixture has good properties also depends on advanced asphalt mix design methods. Scientific mix design methods can improve engineering properties of asphalt mixture, further extending pavement life and preventing early distress of flexible pavement. Additionally, in traditional asphalt mix design procedures, the capability to resist pavement distress (rutting, IRI, and fatigue cracking) of a mixture is always evaluated based on laboratory performance tests (Hamburg wheel tracking device, Asphalt Pavement Analyzer, repeated flexural bending, etc.). However, there is an inevitable difference between laboratory tests and the real circumstance where asphalt mixture experiences because the pavement condition (traffic, climate, pavement structure) is varying and complex. The successful application examples of machine learning (ML) in all kinds of fields make it possible to establish the predictive models of pavement distress, with the inputs which contain asphalt concrete materials properties involved in the mix design process. Therefore, this study utilized historical data acquired from laboratory records, the LTPP dataset, and the NCHRP 1-37A report, data analytics and processing methods, as well as ML models to establish pavement distress predictive models, and then developed an automated and balanced mix design procedure, further lying a foundation to achieve an MGI mix design in the future. Specifically, the main research content can be divided into three parts:1. Established ML models to capture the relationship between properties of the binder, aggregates properties, gradation, asphalt content (effective and absorbed asphalt content), gyration numbers, and mixture volumetric properties for developing cost-saving Superpave and Marshall mix design methods; 2. Developed pavement distress (rutting, IRI, and fatigue cracking) predictive models, based on the inputs of asphalt concrete properties, other pavement materials information, pavement structure, climate, and traffic; 3. Proposed and verified an intelligent and balanced asphalt mix design procedure by combining the mixture properties prediction module, pavement distress predictive models and criteria, and non-dominated Sorting genetic algorithm-Ⅱ (NSGA-Ⅱ). It was discovered determining total asphalt content through predicting effective and absorbed asphalt content indirectly with ML models was more accurate than predicting total asphalt content directly with ML models; Pavement distress predictive models can achieve better predictive results than the calibrated prediction models of Mechanistic-Empirical Pavement Design Guide (MEPDG); The design results for an actual project of surface asphalt course suggested that compared to the traditional ones, the asphalt contents of the 12.5 mm and 19 mm Nominal Maximum Aggregate Size (NMAS) mixtures designed by the automated mix design procedure drop by 7.6% and 13.2%, respectively; the percent passing 2.36 mm sieve of the two types of mixtures designed by the proposed mix design procedure fall by 17.8% and 10.3%, respectively.
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    Biophysics at the coffee shop: lessons learned working with George Oster
    Igoshin, Oleg A.; Chen, Jing; Xing, Jianhua; Liu, Jian; Elston, Timothy C.; Grabe, Michael; Kim, Kenneth S.; Nirody, Jasmine A.; Rangamani, Padmini; Sun, Sean X.; Wang, Hongyun; Wolgemuth, Charles (American Society for Cell Biology, 2019-07-22)
    Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition, and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.
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    Hybrid Modular Multilevel Converter Family and Modular DC Circuit Breaker for Medium-voltage DC (MVDC) Applications
    Liu, Jian (Virginia Tech, 2023-09-12)
    With the increasing maturity and flexibility of power electronics-based voltage conversion techniques, DC grids, and distribution systems have gained significant interest. These systems offer advantages such as improved power quality, efficiency, and flexibility. Medium-voltage DC (MVDC) applications, including shipboard, railway systems, distribution networks, and microgrids, are emerging as critical areas of interest. To integrate MVDC systems with existing power grids, MV AC/DC conversion techniques are crucial. Moreover, the lack of mature protection strategies and equipment, particularly DC circuit breakers (DCCB), poses a significant challenge to the development of MVDC systems. Therefore, this thesis aims to address two primary challenges in the field: the improved topologies of MV AC/DC conversion techniques for interfacing MVDC systems with power grids and the development of high power density DCCB for MVDC systems. The traditional modular multilevel converter (MMC) is widely used for medium voltage (MV) AC/DC conversion due to its modularity, scalability, and reliability. However, the presence of numerous semiconductor devices and capacitors in MMCs results in challenges such as low power efficiency and density. To enhance the performance of MMCs, this thesis proposes several novel hybrid MMC (HMMC) topologies, including the three-level HMMC, flying capacitor HMMC, and hybrid-leg MMC. These topologies aim to leverage the advantages of both conventional multilevel converters and MMCs. By replacing the low-voltage (LV) submodule (SM) in MMCs with a simple high-voltage (HV) switch, higher efficiency, a smaller footprint, and lower cost can be achieved. The HV switch operates at line frequency, simplifying device-switching and addressing the challenges of series-connected devices. The introduction of additional HV switches enables alternative connections compared to traditional MMCs, reducing the number of required SMs. Consequently, there is a significant reduction in the number of semiconductor devices, capacitor energy storage, and power losses. Furthermore, an average model is developed for the three-level HMMC to illustrate the additional power flow path between the AC and DC sides, as well as the reduced SM capacitor energy storage requirement. As a result, the proposed HMMCs exhibit substantial potential to replace traditional MMCs, offering higher efficiency and power density. Unidirectional high-voltage (HV) and medium-voltage (MV) rectifiers are essential for applications where power flows exclusively from the AC to the DC side. Examples of such applications include HVDC transmission, front-end converters for electric vehicle (EV) charging stations, and data centers. Therefore, hybrid modular multilevel rectifiers (HMMRs) are proposed for these unidirectional AC/DC applications. Instead of utilizing active devices for HV switches, the HMMR employs HV diode to achieve step-up HMMR, step-down HMMR, and flying capacitor HMMR configurations. As diodes are passive devices that do not require gate driver units, the HMMR design becomes simpler, resulting in cost and volume savings. Additionally, voltage sharing among the HV diode stack becomes more manageable as concerns regarding gate signal mismatch are eliminated. However, it is important to note that diodes lack current interruption capability. This limitation requires further investigation, particularly in non-unity power factor (PF) operations, which may impose restrictions on the operational range of the rectifiers. In terms of medium voltage (MV) DC circuit breakers (DCCB), this paper introduces the concept and design procedure of a high-power-density, modular, and scalable power electronic interrupter (PEI) for MV hybrid circuit breakers (HCB). The analysis includes trade-offs and limiting factors of various components within a single PEI module. A prototype of a 12 kV, 1 kA breaking-capable PEI is constructed, and new staged turn-off strategies are proposed to ensure the balanced distribution of metal-oxide varistor (MOV) energy. The developed PEI achieves a peak power density of 7.4 kW/cm$^3$, much higher than the solution based on the IGBT modules. After integrating the developed PEI into a full-scale HCB, the breaking capability of the developed PEI and the effectiveness of the staged turn-off strategy are validated. Furthermore, the scalability of the HCB is evaluated, which can simplify the design process from a low-voltage HCB to a higher-voltage version. For series-connected devices in SSCB or HCB configurations, the conventional gate driver structure necessitates an individual gate driver unit, fiber-optic, and isolated power supplies for each device. This design increases cost and volume, particularly for this single-pulse application. To address this issue, two new single gate driver structures are proposed to reduce component count and system complexity. The first solution, namely the MOV-coupled structure, employs a metal-oxide varistor (MOV) for the turn-off path. On the other hand, the transformer-coupled structure combines the auxiliary power and gate signal, enabling both simultaneous and staged turn-off schemes. Moreover, the cascaded high- and lower-voltage transformer structure simplifies insulation design and demonstrates improved scalability. These proposed gate driver structures aim to streamline the system, reduce component numbers, and simplify control for series-connected devices, leading to cost savings and improved overall performance.
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    Hybrid Modular Multilevel Converters for High-AC/Low-DC Medium-Voltage Applications
    Motwani, Jayesh Kumar; Liu, Jian; Boroyevich, Dushan; Burgos, Rolando; Zhou, Zhi; Dong, Dong (IEEE, 2024-02-12)
    With ever-increasing power-density requirements, technologies such as energy storage systems and electric-vehicles can benefit greatly from interfacing medium-voltage (MV)-AC grid like 13.8kV or 30kV using high-AC/low-DC voltage converter. Using modular high-AC/low-DC voltage converter can help increase power-density and efficiency, while reducing total conversion steps and providing flexibility. Full-bridge modular multilevel converters (FB-MMC) and solid-state transformers are existing solutions for such operations, but suffer from limitations of high semiconductor requirements, large submodule capacitors and/or many high-frequency transformers. Three new hybrid-MMC (HMMC) topologies are proposed in this paper as alternative solutions for such high-AC/low-DC voltage operations. Each of the three developed HMMCs utilizes a unique combination of low-frequency high-voltage switches and fast-switching lowvoltage switch based submodules to generate multilevel-AC voltage. HMMCs are compared extensively to state-of-the-art FB-MMC and are shown to have semiconductor savings of over 27%, 38% lower submodule capacitor size, and 53% lower losses for 13.8-kV-AC/6-kV-DC operation. Due to these benefits like higher efficiency, significantly smaller submodule capacitance requirements, and fewer semiconductors, HMMCs can be an excellent option for high-AC/low-DC applications. Practical considerations like snubber and DC split-capacitor requirement are also elaborated for developing and commercializing HMMCs. Comparison results are verified using a 17.5 kW three-phase MV laboratory prototype.
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    Line frequency commutated voltage source converters for multiphase modular multilevel converters
    (2022-11-29)
    Aspects are described for line frequency commutated voltage source converters for multiphase modular multilevel converters. A voltage source converter (VSC) capacitor voltage of a multiphase VSC of a multiphase power converter can be identified. The multiphase VSC can include a half-bridge circuit for each phase of the multiphase power converter. A circuit parameter can be identified and utilized to determine an arm voltage of an arm of a branch of the multiphase converter. Switch control signals can be generated to insert or bypass the VSC capacitor for the arm of the branch of the multiphase converter device, based at least in part on a comparison between the arm voltage and the VSC capacitor voltage.