Probabilistic Physics-integrated Neural Differentiable Modeling for Isothermal Chemical Vapor Infiltration Process

Chemical vapor infiltration (CVI) is a widely adopted manufacturing technique used in producing carbon-carbon and carbon-silicon carbide composites. These materials are especially valued in the aerospace and automotive industries for their robust strength and lightweight characteristics. The densification process during CVI critically influences the final performance, quality, and consistency of these composite materials. Experimentally optimizing the CVI processes is challenging due to long experimental time and large optimization space. To address these challenges, this work takes a modeling-centric approach. Due to the complexities and limited experimental data of the isothermal CVI densification process, we have developed a data-driven predictive model using the physics-integrated neural differentiable (PiNDiff) modeling framework. An uncertainty quantification feature has been embedded within the PiNDiff method, bolstering the model's reliability and robustness. Through comprehensive numerical experiments involving both synthetic and real-world manufacturing data, the proposed method showcases its capability in modeling densification during the CVI process. This research highlights the potential of the PiNDiff framework as an instrumental tool for advancing our understanding, simulation, and optimization of the CVI manufacturing process, particularly when faced with sparse data and an incomplete description of the underlying physics

On-line Process Physics Tests via Lyapunov-based Economic Model Predictive Control and Simulation-Based Testing of Image-Based Process Control

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 applied in the context of chemical process control, along with their benefits and limitations. The first is a method for testing data-driven modeling strategies on-line by postulating the experimental conditions which could reveal if a model is correct, and then attempting to collect data which could help to reveal this. The second strategy is a framework for testing image-based control algorithms via simulating both the generation of the images as well as the impacts of control on the resulting systems

A Model-Centric Framework for Advanced Operation of Crystallization Processes

Crystallization is the main physical separation process in many chemical industries. It is an old unit operation which can separate solids of high purity from liquids, and is widely applied in the production of food, pharmaceuticals, and fine chemicals. While industries in crystallization operation quite rely on rule-of-thumb techniques to fulfill their requirement, the move towards a scientific- and technological- based approach is becoming more important as it provides a mechanism for driving crystallization processes optimally and in more depth without increasing costs. Optimal operation of industrial crystallizers is a prerequisite these days for achieving the stringent requirements of the consumer-driven manufacturing. To achieve this, a generic and flexible model centric framework is developed for the advanced operation of crystallization processes. The framework deploys the modern software environment combined with the design of a state-of-the-art 1-L crystallization laboratory facility. The emphasis is on developing an economically and practically feasible implementation which can be applied for the optimal operation of various crystallization systems by pharmaceutical industries. The key developments in the framework have occurred in three broad categories: i. Modeling: Using an advanced modeling tool is intended for accurate representation of the behavior of the physical system. This is the cornerstone of any simulation, optimization or model-based control approach. ii. Monitoring: Applying a novel image-based technique for online characterization of the particulate processes. This is a promising method for direct tracking of particle size and size distribution with high adaptability for real-time application iii. Control: Proposing numerous model-based strategies for advanced control of the crystallization system. These strategies enable us to investigate the role of model complexity on real-time control design. Furthermore, the effect of model imperfections, process uncertainty and decision variables on optimal operation of the process can be evaluated. Overall, results from this work presents a robust platform for further research in the area of crystal engineering. Most of the developments described will pave the way for future set of activities being targeted towards extending and adapting advanced modeling, monitoring and control concepts for different crystallization processes

Review of Life Cycle Assessment in Agro-Chemical Processes

Life Cycle Assessment (LCA) is a method used to evaluate the potential impacts on the environment of a product, process, or activity throughout its life cycle. Today’s LCA users are a mixture of individuals with skills in different disciplines who want to evaluate their products, processes, or activities in a life cycle context. This study attempts to present some of the LCA studies on agro-chemical processes, recent advances in LCA and their application on food products and non-food products. Due to the recent development of LCA methodologies and dissemination programs by international and local bodies, use of LCA is rapidly increasing in agricultural and industrial products. The literatures suggest that LCA coupled with other environmental approaches provides much more reliable and comprehensive information to environmentally conscious policy makers, producers, and consumers in selecting sustainable products and production processes. For this purpose, a field study of LCA of biodiesel from Jatropha curcas has been taken as an example in the study. In the past, LCA has been applied primarily to products but recent literature suggests that it has also the potential as an analysis and design tool for processes and services. In general, all primary industries use energy and water resources and emit pollutants gases. LCA is a method to report on and analyze these resource issues across the life cycle of agro-chemical processes. This review has the importance as a first part of a research project to develop a life cycle assessment methodology for agro-chemical industries. It presents the findings of a literature review that focuses on LCA of agriculture and chemical engineering literatur

Life cycle assessment (LCA) applied to the process industry: a review

Purpose : Life cycle assessment (LCA) methodology is a well-established analytical method to quantify environmental impacts, which has been mainly applied to products. However, recent literature would suggest that it has also the potential as an analysis and design tool for processes, and stresses that one of the biggest challenges of this decade in the field of process systems engineering (PSE) is the development of tools for environmental considerations. Method : This article attempts to give an overview of the integration of LCA methodology in the context of industrial ecology, and focuses on the use of this methodology for environmental considerations concerning process design and optimization. Results : The review identifies that LCA is often used as a multi-objective optimization of processes: practitioners use LCA to obtain the inventory and inject the results into the optimization model. It also shows that most of the LCA studies undertaken on process analysis consider the unit processes as black boxes and build the inventory analysis on fixed operating conditions. Conclusions : The article highlights the interest to better assimilate PSE tools with LCA methodology, in order to produce a more detailed analysis. This will allow optimizing the influence of process operating conditions on environmental impacts and including detailed environmental results into process industry

Evaluation of an intensified continuous heat-exchanger reactor for inherently safer characteristics

The present paper deals with the establishment of a new methodology in order to evaluate the inherently safer characteristics of a continuous intensified reactor in the case of an exothermic reaction. The transposition of the propionic anhydride esterification by 2-butanol into a new prototype of ‘‘heatexchanger/ reactor’’, called open plate reactor (OPR), designed by Alfa Laval Vicarb has been chosen as a case study. Previous studies have shown that this exothermic reaction is relatively simple to carry out in a homogeneous liquid phase, and a kinetic model is available. A dedicated software model is then used not only to assess the feasibility of the reaction in the ‘‘heat-exchanger/reactor’’ but also to estimate the temperature and concentration profiles during synthesis and to determine optimal operating conditions for safe control. Afterwards the reaction was performed in the reactor. Good agreement between experimental results and the simulation validates the model to describe the behavior of the process during standard runs. A hazard and operability study (HAZOP) was then applied to the intensified process in order to identify the potential hazards and to provide a number of runaway scenarios. Three of them are highlighted as the most dangerous: no utility flow, no reactant flows, both stop at the same time. The behavior of the process is simulated following the stoppage of both the process and utility fluid. The consequence on the evolution of temperature profiles is then estimated for a different hypothesis taking into account the thermal inertia of the OPR. This approach reveals an intrinsically safer behavior of the OPR

Environmental Risk Analysis: Problems and Perspectives in Different Countries

The authors discuss various industrial accidents, which have led to growing concerns about the potential hazards and risks involved in chemical process industries