Chenang Liu

• Doctor of Philosophy
• Professor (Assistant) at Oklahoma State University

This study developed a Volume of Fluid (VOF)-to-Discrete Phase Model (DPM) to simulate the generation and evolution of therapeutic aerosols in the Respimat® Soft Mist Inhaler (SMI) as a case study. Specifically, the atomization process was modeled explicitly from the initial liquid jet collision to the formation of aerosolized droplets. The simulat...

Investigating the causal relationships between characteristics (e.g., lifestyles or intervention strategies of patients) and the resulting expressions (e.g., physiological symptoms) play a critical role in healthcare analytics. Effective synthesis for the resulting expressions using given characteristics can make great contributions to health risk...

Cyber-enabled manufacturing systems become increasingly data-rich, generating vast amounts of real-time sensor data for quality control and process optimization. However, it also exposes these systems to significant cyber-physical security threats. For instance, attackers may delete, change, or replace data, leading to defective products, damaged e...

Machine learning (ML) methods are widely used in manufacturing applications, which usually require a large amount of training data. However, data collection needs extensive costs and time investments in the manufacturing system, and data scarcity commonly exists. With the development of the industrial internet of things (IIoT), data-sharing is wide...

This paper presents the first comprehensive literature review of deep learning (DL) applications in additive manufacturing (AM). It addresses the need for a thorough analysis in this rapidly growing yet scattered field, aiming to bring together existing knowledge and encourage further development. Our research questions cover three major areas of A...

Diabetic retinopathy (DR) is a serious sight-threatening diabetic complication. Having an annual eye exam, as a common recommendation, is helpful for diabetic patients to reduce the risk of DR and prevent vision loss. However, many diabetic patients do not comply with this recommendation because of the asymptomatic nature of DR in the early (non-pr...

Medical imaging is a crucial tool in clinics to monitor tumor treatment progress. In practice, many imaging tools (such as MRI and CT scans) are in general costly and may also expose patients to radiation, leading to potential side effects. Recent studies have demonstrated that ultrasound imaging, which is safe, low-cost, and easy to access, can mo...

In advanced manufacturing, the incorporation of sensing technology provides an opportunity to achieve efficient in situ process monitoring using machine learning methods. Meanwhile, the advances of information technologies also enable a connected and decentralized environment for manufacturing systems, making different manufacturing units in the sy...

Despite the rapid adoption of deep learning in additive manufacturing (AM), significant quality assurance challenges continue to persist. This is further emphasized by the limited availability of samples for complex AM fabricated builds. Thus, this study advances an emerging diffusion generative model, i.e., the denoising diffusion implicit model (...

Additive manufacturing (AM) has already proved itself to be the potential alternative to widely-used subtractive manufacturing due to its extraordinary capacity of manufacturing highly customized products with minimum material wastage. Nevertheless, it is still not being considered as the primary choice for the industry due to some of its major inh...

Recurrent respiratory papillomatosis (RRP) is a chronic condition primarily affecting children, known as juvenile onset RRP (JORRP), caused by a viral infection. Antiviral medications have been used to reduce the need for frequent surgeries, slow the growth of papillomata, and prevent disease spread. Effective treatment of JORRP necessitates target...

The integration of Application-Driven Data Analytics into Engineering and Engineering Technology courses has become increasingly important due to the growing significance of data in the modern industry. This research aims to explore the potential of introducing new application-driven data analytics modules to advance the teaching effectiveness of t...

The advancement of sensing technology enables efficient data collection from manufacturing systems for monitoring and control. Furthermore, with the rapid development of the Internet of Things (IoT) and information technologies, more and more manufacturing systems become cyber-enabled, facilitating real-time data sharing and information exchange, w...

Designing and printing metamaterials with customizable architectures enables the realization of unprecedented mechanical behaviors that transcend those of their constituent materials. These behaviors are recorded in the form of response curves, with stress-strain curves describing their quasi-static footprint. However, existing inverse design appro...

Machine learning (ML) has been extensively adopted for the online sensing-based monitoring in advanced manufacturing systems. However, the sensor data collected under abnormal states are usually insufficient, leading to significant data imbalanced issue for supervised machine learning. A common solution for this issue is to incorporate data augment...

Data quality monitoring plays a critical role in various real-world engineering system inspection problems. Anomalous or invalid inspection data commonly exist due to computer/human recording errors, sensor faults, etc. Thus, an efficient tool to detect data anomalies is critically needed. However, it is challenging due to high dimensionality, unkn...

Diabetic Retinopathy (DR) is a common microvascular diabetes complication in clinics, which may result in vision loss due to the damage of blood vessels in the back of the eye. Currently, it is also the leading cause of blindness among American adults. Thus, with the available electronic health records (EHR) data, establishing an effective classifi...

High intensity focused ultrasound (HIFU) is a promising non-invasive technique for treating solid tumors using thermal and histotripsy-based mechanical ablation. However, its clinical significance in different tumor types is not fully understood. To assess its therapeutic efficacy and immunomodulatory properties, we compared HIFU thermal ablation a...

In many healthcare applications, datasets for classification may be highly imbalanced due to the rare occurrence of target events such as disease onset. The SMOTE (Synthetic Minority Over-sampling Technique) algorithm has been developed as an effective resampling method for imbalanced data classification by oversampling samples from the minority cl...

Although data have been extensively leveraged for process monitoring and control in advanced manufacturing, it still suffers from the connection issues among sensors, machines, and computers, which may lead to significant data loss, i.e., missing region in the collected data, in the application of data-driven monitoring. To address the missing regi...

In recent decades, cardiovascular disease (CVD) has become the leading cause of death in most countries of the world. Since many types of CVD are preventable by modifying lifestyle behaviors, the objective of this paper is to develop an effective personalized lifestyle recommendation algorithm for reducing the risk of common types of CVD. However,...

Objective: Aging is a complicated process that triggers age-related disease susceptibility through intercellular communication in the microenvironment. While the classic secretome of senescence-associated secretory phenotype (SASP) including soluble factors, growth factors, and extracellular matrix remodeling enzymes are known to impact tissue h...

In advanced manufacturing, the incorporation of sensing technology provides an opportunity to achieve efficient in-situ process monitoring using machine learning methods. Meanwhile, the advances of information technologies also enable a connected and decentralized environment for manufacturing systems, making different manufacturing units in the sy...

Volume 24A provides a comprehensive review of additive manufacturing (AM) design fundamentals and applications. The primary focus of the Volume is on metallic systems with limited emphasis on polymers and ceramics where applicable. The first five divisions provide an in-depth review of each of the key aspects of the entire AM value chain. The mater...

Metal additive manufacturing (AM) has become popular in a large variety of applications due to its excellent capabilities of handling complex geometries and novel materials. However, due to its process complexity, layer-wise surface quality issue is still one of the critical concerns to further broaden adoption of metal AM, because of the impact on...

Process uncertainty induced quality issue remains the major challenge that hinders the wider adoption of additive manufacturing (AM). The defects occurred significantly compromise structural integrity and mechanical properties of fabricated parts. Therefore, there is an urgent need in fast, yet reliable AM component certification. Most finite eleme...

The optimal power flow (OPF) problem, as a critical component of power system operations, becomes increasingly difficult to solve due to the variability, intermittency, and unpredictability of renewable energy brought to the power system. Although traditional optimization techniques, such as stochastic and robust optimization approaches, could be u...

Investigating the causal relationships between characteristics and expressions plays a critical role in healthcare analytics. Effective synthesis for expressions using given characteristics can make great contributions to health risk management and medical decision-making. For example, predicting the resulting physiological symptoms on patients fro...

In many healthcare applications, datasets for classification may be highly imbalanced due to the rare occurrence of target events such as disease onset. The SMOTE (Synthetic Minority Over-sampling Technique) algorithm has been developed as an effective resampling method for imbalanced data classification by oversampling samples from the minority cl...

Nowadays, additive manufacturing (AM) has been increasingly leveraged to produce human-centered products, such as orthoses and prostheses as well as therapeutic helmets, finger splints, and other personalized devices. This study reviews the state-of-the-art research in human-centered AM with a highlight on the role of artificial intelligence (AI)....

Layer-wise surface morphology information plays a critical role in the quality monitoring and control of additive manufacturing (AM) processes. 3D scan technologies can provide effective means to obtain accurate surface morphological data. However, most of the existing 3D scan technologies are time consuming due to either contact mode or algorithm...

In the U.S., building sector is responsible for around 40% of total energy consumption and contributes about 40% of carbon emissions since 2012. Within past several years, various optimization models and control strategies have been studied to improve buildings energy efficiency and reduce operational expenses under constraints of satisfying occupa...

In recent decades, cardiovascular disease (CVD) has become the leading cause of death in most countries of the world. Since many types of CVD are preventable by modifying lifestyle behaviors, the objective of this paper is to develop an effective personalized lifestyle recommendation algorithm for reducing the risk of common types of CVD. However,...

Additive manufacturing (AM) has gained increasing popularity in a large variety of mission- critical fields, such as aerospace, medical, and transportation. The layer-by-layer fabrication scheme of the AM significantly enhances fabrication flexibility, resulting in the expanded vulnerability space of cyber- physical AM systems. This potentially lea...

In cyber-physical systems (CPS) of additive manufacturing (AM), cyber-attacks may significantly alter the design of the AM part, compromising its mechanical properties and functionalities. In-situ process authentication may assure that the AM part is fabricated as intended. Most cyber-physical attacks towards AM processes can be manifested as print...

The objective of this study is to develop an effective data-driven methodology for the online monitoring of cancer drug delivery guided by the ultrasonic images. To achieve this goal, effective image quantification and accurate feature extraction play a critical role on image-guided drug delivery (IGDD) monitoring. However, the existing image-guide...

Additive manufacturing (AM) has received an increasing attention in the manufacturing sector, owing to its high-level design freedom and enhanced capability to produce parts with complex geometries. With advances in AM technologies, the role of AM has been shifting from rapid prototyping to viable production-worthy manufacturing of functional parts...

Supervised machine learning techniques such as classification models have been widely applied to online process anomaly detection in advanced manufacturing. However, since abnormal process states rarely occur in regular manufacturing settings, the data collected for model training may be highly imbalanced, which may result in significant training b...

With the rapid development of the Internet of Things and information technologies, more and more manufacturing systems become cyber-enabled, which significantly improves the flexibility and productivity of manufacturing. Furthermore, a large variety of online sensors are also commonly incorporated in the manufacturing systems for online quality mon...

In the U.S., building sector is responsible for around 40% of total energy consumption and contributes about 40% of carbon emissions since 2012. Within the past several years, various optimization models and control strategies have been studied to improve buildings energy efficiency and reduce operational expenses under the constraints of satisfyin...

Layer-wise 3D surface morphology information is critical for the quality monitoring and control of additive manufacturing (AM) processes. However, most of the existing 3D scan technologies are either contact or time consuming, which are not capable of obtaining the 3D surface morphology data in a real-time manner during the process. Therefore, the...

Additive manufacturing (AM) has gained increasing popularity in various quality critical applications such as aerospace and healthcare due to its high flexibility in fabricating complex geometries with novel materials. However, the relatively poor layer-wise surface quality may lead to compromised property and functionality of AM products. The expe...

Additive manufacturing (AM) processes are subject to cyber-physical attacks during all the three stages including design, slicing, and manufacturing phases. In-situ process authentication is crucial for AM to ensure that the manufacturing is performed as intended. Since most of the cyber-physical attacks aiming to alter AM processes can be manifest...

As an emerging technology, additive manufacturing (AM) is able to fabricate products with complex geometries using various materials. In particular, cyber-enabled AM systems have recently become widely applied in many real-world applications. It significantly improves the flexibility and productivity of AM but poses the system under high risks of c...

As an effective dimension reduction and feature extraction technique, manifold learning has been successfully applied to high-dimensional data analysis. With the rapid development of sensor technology, a large amount of high dimensional data such as image streams can be easily available. Thus, a promising application of manifold learning is in the...

Due to its predominant flexibility in fabricating complex geometries, additive manufacturing (AM) has gain increasing popularity in various mission critical applications, such as aerospace, health care, military, and transportation. The layerby-layer manner of AM fabrication significantly expands the vulnerability space of AM cyber-physical systems...

Grid integration of the increasing distributed energy resources could be challenging in terms of new infrastructure investment, power grid stability, etc. To resolve more renewables locally and reduce the need for extensive electricity transmission, a community energy transaction market is assumed with market operator as the leader whose responsibi...

Additive manufacturing (AM) refers to a family of manufacturing technologies that fabricate parts by joining materials layer by layer. It has a high level of flexibility in design and manufacturing, which provides a unique opportunity for producing parts with complex geometries that are not feasible using conventional subtractive manufacturing. Due...

Additive manufacturing (AM) is a powerful technology for fabrication of components with complex geometries using a variety of materials. However, one of the major challenges in the AM industry is how to ensure product quality and consistency by detecting and then mitigating the defects, which otherwise can severely deteriorate the quality of AM pro...

The temporal and spatial patterns of nanoparticle that ferry both imaging and therapeutic agent in solid tumors is significantly influenced by target tissue movement, low spatial resolution, and inability to accurately define regions of interest (ROI) at certain tissue depths. These combine to limit and define nanoparticle untreated regions in tumo...

The objective of this work is to model and quantify the layer-wise spatial evolution of porosity in parts made using additive manufacturing (AM) processes. This is an important research area because porosity has a direct impact on the functional integrity of AM parts such as their fatigue life and strength. To realize this objective, an augmented l...

Additive manufacturing (AM) is a powerful technology for fabrication of components with complex geometries using a variety of materials. One of the major challenges in the AM industry is how to guarantee product quality and consistency by minimizing the defects. Although AM quality improvement can be achieved by optimizing machine parameter setting...

This work addresses the following open research question: how to assess the surface finish of a workpiece in situ during conventional machining? The goal is to track variations in surface finish during conventional machining without stopping the machine tool so that quick compensatory action can be taken in case of a process drift. In pursuit of th...