Engineering Commons^™

Study Of The Application Of Blender For Simulation Of A Closed-Loop Image-Based Greenhouse Supplemental Lighting Control, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Image-based control and sensing has been applied in a wide variety of next generation manufacturing fields. Utilizing methods of simulating closed-loop image-based control may be advantageous for improving control performance and design without the need for an experimental setup. One software capable of these simulations is the open-source 3D modeling software Blender, which has many capabilities aided by a Python API. This work explores the use of Blender as an image-based control test bed, where both the process and the controller are simulated, in the context of a greenhouse supplemental lighting control system.

Safety With Non-Deterministic Control Action Selection Using Quantum Devices, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Recent increasing interest in quantum computers has spurred research into practical engineering applications for quantum algorithms. One potential application is process control. The unique quantum phenomena involved with quantum computing brings up interesting considerations for control. This work focuses on non-determinism, first through a motivating simulation utilizing a continuous stirred-tank reactor. Following this, two methods of potentially ensuring system stability in the presence of non-determinism are discussed. The first involves including an additional gate to the modified Grover’s algorithm presented in our previous work, which is designed to prevent a qubit state corresponding to an undesired control input from being …

Computational Fluid Dynamics Modeling Of A Wafer Etch Temperature Control System, Henrique Oyama, Kip Nieman, Anh Tran, Bernard Keville, Yewei Wu, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Next-generation etching processes for semiconductor manufacturing exploit the potential of a variety of operating conditions, including cryogenic conditions at which high etch rates of silicon and very low etch rates of the photoresist are achieved. Thus, tight control of wafer temperature must be maintained. However, large and fast changes in the operating conditions make the wafer temperature control very challenging to be performed using typical etch cooling systems. The selection and evaluation of control tunings, material, and operating costs must be considered for next-generation etching processes under different operating strategies. These evaluations can be performed using digital twin environments (which …

Development Of Directed Randomization For Discussing A Minimal Security Architecture, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Akkarakaran Francis Leonard, Kip Nieman, Helen Durand, Katie Tyrrell, Katrina Hinzman, Michael Williamson

Chemical Engineering and Materials Science Faculty Research Publications

Strategies for mitigating the impacts of cyberattacks on control systems using a control-oriented perspective have become of greater interest in recent years. Our group has contributed to this trend by developing several methods for detecting cyberattacks on process sensors, actuators, or both sensors and actuators simultaneously using an advanced optimization-based control strategy known as Lyapunov-based economic model predictive control (LEMPC). However, each technique comes with benefits and limitations, both with respect to one another and with respect to traditional information technology and computer science-type approaches to cybersecurity. An important question to ask, therefore, is what the goal should be of …

Cybersecurity And Dynamic Operation In Practice: Equipment Impacts And Safety Guarantees, Kip Nieman, Dominic Messina, Matthew Wegener, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Though dynamic operation of chemical processes has been extensively explored theoretically in contexts such as economic model predictive control or even considering the potential for cyberattacks on control systems creating non-standard operating policies, important practical questions remain regarding dynamic operation. In this work, we look at two of these with particular relevance to process safety: (1) evaluating dynamic operating policies with respect to process equipment fidelity and (2) evaluating procedures for determining the parameters of an advanced control law that can promote both dynamic operation as well as safety if appropriately designed. Regarding the first topic, we utilize computational fluid …

Control Implemented On Quantum Computers: Effects Of Noise, Nondeterminism, And Entanglement, Kip Nieman, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Quantum computing has advanced in recent years to the point that there are now some quantum computers and quantum simulators available to the public for use. In addition, quantum computing is beginning to receive attention within the process systems engineering community for directions such as machine learning and optimization. A logical next step for its evaluation within process systems engineering is for control, specifically for computing control actions to be applied to process systems. In this work, we provide some initial studies regarding the implementation of control on quantum computers, including the implementation of a single-input/single-output proportional control law on …

Actuator Cyberattack Handling Using Lyapunov-Based Economic Model Predictive Control, Keshav Kasturi Rangan, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Cybersecurity has gained increasing interest as a consequence of the potential impacts of cyberattacks on profits and safety. While attacks can affect various components of a plant, prior work from our group has focused on the impact of cyberattacks on control components such as process sensors and actuators and the development of detection strategies for cybersecurity derived from control theory. In this work, we provide greater focus on actuator attacks; specifically, we extend a detection and control strategy previously applied for sensor attacks and based on an optimization-based control technique called Lyapunov-based economic model predictive control (LEMPC) to detect attacks …

Test Methods For Image-Based Information In Next-Generation Manufacturing, Henrique Oyama, Dominic Messina, Renee O'Neill, Samantha Cherney, Minhazur Rahman, Keshav Kasturi Rangan, Govanni Gjonaj, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Typical control designs in the process systems engineering literature have assumed that the primary sensing methodologies are traditional instruments such as thermocouples. Dig- italization is changing the landscape for manufacturing, and data-based sensing modalities (e.g., image-based sensing) are becoming of greater interest for plant control. These considerations require novel test/evaluation solutions. For example, process systems engineering researchers may wish to test image-based sensors in simulation. In this work, we provide preliminary thoughts on how image-based technologies might be evaluated via simulation for process systems.

Quantum Computing And Resilient Design Perspectives For Cybersecurity Of Feedback Systems, Keshav Kasturi Rangan, Jihan Abou Halloun, Henrique Oyama, Samantha Cherney, Ilham Azali Assoumani, Nazir Jairazbhoy, Helen Durand, Simon Ka Ng

Chemical Engineering and Materials Science Faculty Research Publications

Cybersecurity of control systems is an important issue in next-generation manufac- turing that can impact both operational objectives (safety and performance) as well as process designs (via hazard analysis). Cyberattacks differ from faults in that they can be coordinated efforts to exploit system vulnerabilities to create otherwise unlikely hazard scenarios. Because coordination and targeted process manipulation can be characteristics of attacks, some of the tactics previously analyzed in our group from a control system cybersecurity perspective have incorporated randomness to attempt to thwart attacks. The underlying assumption for the generation of this randomness has been that it can be achieved …

Challenges And Opportunities For Next-Generation Manufacturing In Space, Kip Nieman, A. F. Leonard, Katie Tyrell, Dominic Messina, Rebecca Lopez, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

With commercial space travel now a reality, the idea that people might spend time on other planets in the future seems to have greater potential. To make this possible, however, there needs to be flexible means for manufacturing in space to enable tooling or resources to be created when needed to handle unexpected situations. Next-generation manufacturing paradigms offer significant potential for the kind of flexibility that might be needed; however, they can result in increases in computation time compared to traditional control methods that could make many of the computing resources already available on earth attractive for use. Furthermore, resilience …

On-Line Process Physics Tests Via Lyapunov-Based Economic Model Predictive Control And Simulation-Based Testing Of Image-Based Process Control, Henrique Oyama, A. F. Leonard, Minhazur Rahman, Govanni Gjonaj, Michael Williamson, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Next-generation manufacturing involves increasing use of automation and data to enhance process efficiency. An important question for the chemical process industries, as new process systems (e.g., intensified processes) and new data modalities (e.g., images) are integrated with traditional plant automation concepts, will be how to best evaluate alternative strategies for data-driven modeling and synthesizing process data. Two methods which could be used to aid in this are those which aid in testing data-based techniques on-line, and those which enable various data-based techniques to be assessed in simulation. In this work, we discuss two techniques in this domain which can be …

On-Line Process Physics Tests Via Lyapunov-Based Economic Model Predictive Control And Simulation-Based Testing Of Image-Based Process Control, Henrique Oyama, Akkarakaran Francis Leonard, Minhazur Rahman, Govanni Gjonaj, Michael Williamson, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Next-generation manufacturing involves increas- ing use of automation and data to enhance process efficiency. An important question for the chemical process industries, as new process systems (e.g., intensified processes) and new data modalities (e.g., images) are integrated with traditional plant automation concepts, will be how to best evaluate alternative strategies for data-driven modeling and synthesizing process data. Two methods which could be used to aid in this are those which aid in testing data-based techniques on-line, and those which enable various data-based techniques to be assessed in simulation. In this work, we discuss two techniques in this domain which can …

Quantum Computing And Resilient Design Perspectives For Cybersecurity Of Feedback Systems, Keshav Kasturi Rangan, Jihan Abou Halloun, Henrique Oyama, Samantha Cherney, Ilham Azali Assoumani, Nazir Jairazbhoy, Helen Durand, Simon Ka Ng

Chemical Engineering and Materials Science Faculty Research Publications

Cybersecurity of control systems is an important issue in next-generation manufac- turing that can impact both operational objectives (safety and performance) as well as process designs (via hazard analysis). Cyberattacks differ from faults in that they can be coordinated efforts to exploit system vulnerabilities to create otherwise unlikely hazard scenarios. Because coordination and targeted process manipulation can be characteristics of attacks, some of the tactics previously analyzed in our group from a control system cybersecurity perspective have incorporated randomness to attempt to thwart attacks. The underlying assumption for the generation of this randomness has been that it can be achieved …

Lyapunov-Based Economic Model Predictive Control For Detecting And Handling Actuator And Simultaneous Sensor/Actuator Cyberattacks On Process Control Systems, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

The controllers for a cyber-physical system may be impacted by sensor measurement cyberattacks, actuator signal cyberattacks, or both types of attacks. Prior work in our group has developed a theory for handling cyberattacks on process sensors. However, sensor and actuator cyberattacks have a different character from one another. Specifically, sensor measurement attacks prevent proper inputs from being applied to the process by manipulating the measurements that the controller receives, so that the control law plays a role in the impact of a given sensor measurement cyberattack on a process. In contrast, actuator signal attacks prevent proper inputs from being applied …

Lyapunov-Based Economic Model Predictive Control For Online Model Discrimination, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Economic model predictive control (EMPC) is a flexible control design strategy that can be modified to achieve many operating goals while also ensuring safe operation (e.g., by adding Lyapunov-based stability constraints to form Lyapunov-based EMPC, or LEMPC). Prior works have investigated LEMPC capabilities for achieving goals online beyond optimizing process economics, including aiding in model structure selection to benefit model-based control system design since the accuracy and quality of the process model are important for achieving an expected performance from such systems. This work further probes the capabilities of LEMPC to accomplish multiple objectives during process operation, including aiding in …

Integrated Cyberattack Detection And Resilient Control Strategies Using Lyapunov-Based Economic Model Predictive Control, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

The use of an integrated system framework, characterized by numerous cyber/physical components (sensor measurements, signals to actuators) connected through wired/wireless networks, has not only increased the ability to control industrial systems, but also the vulnerabilities to cyberattacks. State measurement cyberattacks could pose threats to process control systems since feedback control may be lost if the attack policy is not thwarted. Motivated by this, we propose three detection concepts based on Lyapunov‐based economic model predictive control (LEMPC) for nonlinear systems. The first approach utilizes randomized modifications to an LEMPC formulation online to potentially detect cyberattacks. The second method detects attacks when …

Interactions Between Control And Process Design Under Economic Model Predictive Control, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

conomic model predictive control (EMPC) is a model-based control scheme that integrates process control and economic optimization, which can potentially allow for time-varying operating policies to maximize economic performance. The manner in which an EMPC operates a process to optimize economics depends on the process dynamics, which are fixed by the process design. This raises the question of how process and EMPC designs interact. Works which have addressed process and control design interactions for steady-state operation have sought to simultaneously develop process designs and control law parameters to find the most profitable way to operate a process that is able …

Mitigating Safety Concerns And Profit/Production Losses For Chemical Process Control Systems Under Cyberattacks Via Design/Control Methods, Helen Durand, Matthew Wegener

Chemical Engineering and Materials Science Faculty Research Publications

One of the challenges for chemical processes today, from a safety and profit standpoint, is the potential that cyberattacks could be performed on components of process control systems. Safety issues could be catastrophic; however, because the nonlinear systems definition of a cyberattack has similarities to a nonlinear systems definition of faults, many processes have already been instrumented to handle various problematic input conditions. Also challenging is the question of how to design a system that is resilient to attacks attempting to impact the production volumes or profits of a company. In this work, we explore a process/equipment design framework for …

Responsive Economic Model Predictive Control For Next-Generation Manufacturing, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

There is an increasing push to make automated systems capable of carrying out tasks which humans perform, such as driving, speech recognition, and anomaly detection. Automated systems, therefore, are increasingly required to respond to unexpected conditions. Two types of unexpected conditions of relevance in the chemical process industries are anomalous conditions and the responses of operators and engineers to controller behavior. Enhancing responsiveness of an advanced control design known as economic model predictive control (EMPC) (which uses predictions of future process behavior to determine an economically optimal manner in which to operate a process) to unexpected conditions of these types …

Process Data Analytics Using Deep Learning Techniques, Majid Moradi Aliabadi

Wayne State University Theses

In chemical manufacturing plants, numerous types of data are accessible, which could be process operational data (historical or real-time), process design and product quality data, economic and environmental (including process safety, waste emission and health impact) data. Effective knowledge extraction from raw data has always been a very challenging task, especially the data needed for a type of study is huge. Other characteristics of process data such as noise, dynamics, and highly correlated process parameters make this more challenging.

In this study, we introduce an attention-based RNN for multi-step-ahead prediction that can have applications in model predictive control, fault diagnosis, …

Ac Conductivity Studies Of Polyethylene-Oxide-Garnet Type Li7la3zr2o12 Hybrid Composite Solid Polymer Electrolyte For Li-Ion Battery, Parisa Bashiri

Wayne State University Dissertations

Solid electrolytes including ceramics and polymers are considered to be the ultimate substitute for organic liquid electrolytes currently used in commercialized lithium ion batteries to address the safety concerns due to Li dendrite growth and internal short circuiting. However, low ionic conductivity due to high grain boundary resistance in ceramics and semi-crystalline nature of polymers has held back the solid electrolytes from being used in Li-ion batteries. Polyethylene oxide (PEO), complexed with a Li-salt, is a well-studied polymer electrolyte showing ionic conductivity properties at room temperature. However, the coexistence of amorphous and crystalline regions at room temperature (< Tm, the melting temperature) has

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Enabling 3d Printing Technologies For Artificial Compound Eye System And Penetrating Neural Probes, Boshen Zhang

Wayne State University Dissertations

3D printing has become a useful and transformative method and has applications in many different fields, including organ printing, aerospace applications, and medical devices. With higher resolution, faster production speed, and more design flexibility, 3D printing technologies can lead to more novel devices and systems. In this research, two new techniques have been developed to enable 3D printing technologies for artificial compound eye system and penetrating glassy carbon neural electrode array.

This work focuses on developing new applications based on the SLA 3D printing process, which uses the liquid resin to create a solid 3D structure. The limitation of SLA …

Seed-Mediated Crystallization Of Charge-Transfer Complexes And Their Applications For Gas Sensing, Xuecheng Yu

Wayne State University Dissertations

The dissertation focused on controllable seed-mediated nucleaton of charge transfer complex, namely tetrathiafulvalene bromide ((TTF)Br) and Krogmann’s salts (KCP), and their applications in sensing. On gold nanoparticle (AuNP) decorated highly oriented pyrolytic graphite (HOPG) substrate, the presence of AuNP promotes the formation of charge transfer salt nanowires. The size of these nanowires, both (TTF)Br and KCP, were found to be confined by the size of AuNPs, shown by SEM and AFM characterization. On micro-disk electrodes, charge transfer salt nanowires were found to own a linear time dependency, by both SEM and in-situ optical microscopy. The micro-disk electrodes promoted higher crystallization …

Advanced Electrodes And Electrolytes For Long-Lived And High-Performance Lithium-Sulfur Batteries, Deepesh Gopalakrishnan

Wayne State University Dissertations

ABSTRACT

ADVANCED ELECTRODES AND ELECTROLYTES FOR LONG-LIVED AND HIGH-PERFORMANCE LITHIUM-SULFUR BATTERIES

by

DEEPESH GOPALAKRISHNAN

August 2020

Advisor: Dr. Leela Mohana Reddy Arava

Major: Mechanical Engineering

Degree: Doctor of Philosophy

Lithium – Sulfur (Li-S) batteries have received much attention and considered as a promising candidate for next generation energy storage devices because of their high theoretical energy density (≈2600 Wh kg‒1) and environmental friendliness. However, the uncontrollable growth of lithium dendrites in the lithium metal anode and the fatal effect of polysulfide shuttle hinder their practical applications. The formation of dendrites during repeated Li plating/stripping processes results in: reduced Li availability …

Process/Equipment Design Implications For Control System Cybersecurity, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

An emerging challenge for process safety is process control system cybersecurity. An attacker could gain control of the process actuators through the control system or communication policies within control loops and potentially drive the process state to unsafe conditions. Cybersecurity has traditionally been handled as an information technology (IT) problem in the process industries. In the literature for cybersecurity specifically of control systems, there has been work aimed at developing control designs that seek to fight cyberattacks by either giving the system appropriate response mechanisms once attacks are detected or seeking to make the attacks difficult to perform. In this …

On Accounting For Equipment-Control Interactions In Economic Model Predictive Control Via Process State Constraints, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Traditionally, chemical processes have been operated at steady-state; however, recent work on economic model predictive control (EMPC) has indicated that some processes may be operated in a more economically-optimal fashion under a time-varying operating policy. It is unclear how time-varying operating policies may impact process equipment, which must be investigated for safety and profit reasons. It has traditionally been considered that constraints on process states can be added to EMPC design to prevent the controller from computing control actions which create problematic operating conditions for process equipment. However, no rigorous investigation has yet been performed to analyze whether, when a …

Multi-Responsive Macromolecular Coacervate Complexes For Efficient Biomolecular Encapsulation And Controlled Release, Adrian Lorenzana

Research Opportunities for Engineering Undergraduates (ROEU) Program 2018-19

The project investigates the mechanistic (entropic) formation of organic-inorganic coacervates with improved mechanical strength. We seek to control and modify material properties and stimuli-responsive characteristics of hybrid coacervates, and to explore new practical applications of organic-inorganic coacervate complexes, i.e. (bio)separation, wastewater treatment, drug delivery, battery electrolyte and electrodes.

Engineering Of Gold Nanoparticles For Drug Delivery, Fangchao Liu

Wayne State University Dissertations

Due to their ease of synthesis, versatile surface chemistry, ease of imaging, and biocompatibility, gold nanoparticles (AuNPs) are employed as drug delivery devices in the treatment of respiratory problems associated with spinal cord injury (SCI). We have developed a method for the synthesis of a tripartite nanoconjugate comprised of an AuNP drug carrier chemically conjugated to a transporter protein (wheat germ agglutinin coupled to horseradish peroxidase or WGA-HRP) and to potent SCI drugs. The therapeutic efficacy and biodistribution were studied in a validated animal model. Our results show that a single administration of the nanoconjugate improved diaphragmatic activity at a …

Self-Delivery Drug Amphiphilies In Chemotherapy And Immunotherapy, Jingchao Xi

Wayne State University Dissertations

Eliminating the need for external delivery systems, self-delivery drug amphiphiles represent a simple yet effective approach designed to overcome the various biological barriers for drug delivery. The ability to program the molecular structures and the physicochemical properties, which control the interactions between the drug amphiphiles and their biological surroundings has attracted significant research interests. In this work, we constructed several amphiphilic drugs including chemotherapeutic and immunotherapeutic agents. These amphiphiles exhibited interesting interactions with their biological surroundings. Amphiphiles self-assemble into spherical micelle structures in aqueous solution. However, in the presence of complexed biological fluids, they also possess a strong affinity toward …

Force Field Optimization, Advanced Sampling, And Free Energy Methods With Gpu-Optimized Monte Carlo (Gomc) Software, Mohammad Soroush Barhaghi

Wayne State University Dissertations

In this work, to address the sampling problem for systems at high densities and low temperatures, a generalized identity exchange algorithm is developed for grand canonical Monte Carlo simulations. The algorithm, referred to as Molecular Exchange Monte Carlo (MEMC), is implemented in the GPU-Optimized Monte Carlo (GOMC) software and may be applied to multicomponent systems of arbitrary molecular topology, and provides significant enhancements in the sampling of phase space over a wide range of compositions and temperatures. Three different approaches are presented for the insertion/deletion of the large molecules, and the pros and cons of each method are discussed. Next, …