This study evaluates the introduction of Carbon Capture and Utilization (CCU) process in two Colombian refineries, focusing on their potential to reduce CO2 emissions and their associated impacts under a scenario aligned with the Net Zero Emissions by 2050 Scenario defined in the 2023 IEA report. The work uses a MILP programming tool (Linny-R) to model the operational processes of refinery sites, incorporating a net total cost calculation to optimize process performance over five-year intervals. This optimization was constrained by the maximum allowable CO2 emissions. The methodology includes the calculation of surplus refinery off-gas availability, the selection of products and CCU technologies, and the systematic collection of data from refinery operations, as well as scientific and industrial publications. The results indicate that integrating surplus refinery fuel gas (originally used for combustion processes) and HTL bio-crude off-gas (as a source of biogenic CO2) can significantl... [more]

In Quebec, the chemical sector is rapidly changing, with old facilities closing and new ones opening. Similar situation is happening in other geographies as well. Utilities need to understand the energy needs of these industries, particularly as they transition towards decarbonization. By studying existing data, they can estimate energy requirements and identify alternative technologies such as heat pumps, electric boilers, biomass boilers, and green hydrogen. Two key indicators to measure decarbonization performance: the Decarbonization Efficiency Coefficient and the GHG Performance Indicator. Decarbonizing could significantly reduce energy use, depending on the selected technologies, leading to variations of 6.1 TWh for electricity and 3.5 TWh for biomass.

This study proposes a model-based approach utilizing a hybrid population balance model (PBM) to optimize temperature profiles for minimizing agglomeration and enhancing crystal growth. The PBM incorporates key mechanisms—nucleation, growth, dissolution, agglomeration, and deagglomeration—and is ap-plied to the crystallization of an industrial active pharmaceutical ingredient (API), Compound K. Parameters were estimated through prior design of experiments (DoE) and refined via additional thermocycle experiments. In-silico DoE simulations demonstrate that the hybrid PBM outperforms traditional methods in assessing process performance under agglomeration-prone conditions. Results confirm that thermocycles effectively reduce agglomeration and promote bulk crystal formation, though their efficiency plateaus be-yond a certain cycle number. This model-based approach provides a more robust strategy for agglomeration control compared to conventional methods, offering valuable insights for indus... [more]

Predicting the critical micelle concentration (CMC) of surfactants is essential for optimizing their applications in various industries, including pharmaceuticals, detergents, and emulsions. In this study, we investigate the per-formance of graph-based machine learning models, specifically Graph Convolutional Networks (GCN), Graph At-tention Networks (GAT), and a graph-transformer model, PharmHGT, for predicting CMC values. We aim to de-termine the most effective model for capturing the structural and physicochemical properties of surfactants. Our results provide insights into the relative strengths of each approach, highlighting the potential advantages of transformer-based architectures like PharmHGT in handling molecular graph representations compared to traditional graph neural networks. This comparative study serves as a step towards enhancing the accuracy of CMC predictions, contributing to the efficient design of surfactants for targeted applications.

The escalating urgency to address climate change has driven carbon capture (CC) technologies into the spotlight, particularly for large-scale emitters, which benefit from economies of scale. However, small-scale emitters account for a significant share of CO2 emissions, yet such applica-tions remain largely overlooked in the literature. While CC cost is often used as a key perfor-mance indicator (KPI) for CC technologies, the lack of standardized cost estimation methods leads to inconsistencies, complicating comparisons, and hindering the deployment of CC sys-tems. This study addresses these challenges by developing flexible short-cut correlations for selected CC technologies, providing estimates of the total equipment cost (TEC) and energy consumption specific to small-scale applications across various CO2 inlet concentrations (mol%) and capture scales (10 – 100 kt/y). The flexibility of the correlations enables the integration of various cost estimation methods available in the liter... [more]

The growing size and complexity of energy system optimization models, driven by high-resolution spatial data, pose significant computational challenges. This study introduces methods to reduce model’s size and improve computational efficiency while preserving solution accuracy. First, a composite-curve-based approach is proposed to aggregate granular data into larger resolutions without averaging out specific properties. Second, a general clustering method groups geographically proximate fields, replacing multiple transportation arcs with a single arc to reduce transportation-related variables. Lastly, a two-step algorithm that decomposes the sup-ply chain design problems into two smaller, more manageable subproblems is introduced. These methods are applied to a case study of switchgrass-to-biofuels network design in eight U.S. Midwest states, demonstrating their effectiveness with realistic and detailed spatial data.

This is an Aspen Plus V14 model of a furnace process. Natural gas is combusted in excess air to produce heat. A heat exchanger model simulates the boiling of boiler feed water near 29 bar pressure to produce steam at about 235 deg C. Design specs are used to ensure certain process conditions and scales are met. This is supplementary material for the paper Adams TA. Exergy in Chemical Engineering Education, submitted to the ESCAPE 35 conference.

The transition to renewable energy sources, such as biogas, requires purification processes to separate methane from carbon dioxide, with adsorption-based methods being widely employed. Accurate simulations of these systems, governed by coupled PDEs, ODEs, and algebraic equations, critically depend on precise parameter determination. While traditional approaches often result in significant errors or complex procedures, optimization algorithms provide a more efficient and reliable means of parameter estimation, simplifying the process, improving simulation accuracy, and enhancing the understanding of these systems.
This work introduces an Artificial Intelligence-based methodology for estimating the isotherm parameters of a mathematical phenomenological model for fixed-bed experiments. The separation of CO₂ and CH₄ is used as case study. This work develops an algorithm for parameter estimation for the system's mathematical model. The results show that the validated model has a close fi... [more]

The document is the digital supplementary material for the article titled "Application of Artificial Intelligence in process simulation tool", submitted to the ESCAPE 35 conference. It contains additional information and figures.

Contains optimized design data, aspen simulation files for the three chemical heat pumps namely:
Isopropanol–acetone–hydrogen
2-Butanol–methyl ethyl ketone–hydrogen
2-Pentanol–methyl propyl ketone–hydrogen.
Optimization code (written in python) is also provided.

In this file can be found:
- Energy demands and scope 1 CO2 emissions for different lime production routes
- Assumptions underlying the price scenarios
- Commodities prices used for cost estimation

The classifier is an essential tool for the development of contemporary engineering technology. The application of classifiers is to categorize mixed-sized particles into multi-stage uniform particle sizes. In current studies, the particles in the classifier obtain their initial velocity when feeding. The classification effect is impacted by the inability to precisely control the initial state of the particles. To solve this problem, a pusher feed classifier was designed in this study, and a numerical simulation was performed to investigate its flow field characteristics and classification performance using the RNG-DPM method. A pusher is utilized to achieve particle feeding without initial velocity and to precisely control the initial state of the particles in the classification flow field. A newly developed two-way air inlet structure is designed to provide a superimposed flow field and enable the five-stage classification. Our results show that this pusher feed classifier has the be... [more]

While technical optimization focuses on maximizing the annual energy yield of utility-scale PV parks, the ultimate goal for power plant owners is to maximize investment profit. This paper aims to bridge the gap between technical and economic approaches by using simulation data from a real-case utility-scale PV park. It analyzes how changes in configuration parameters such as the DC−AC ratio and string length and PV technologies like solar tracking systems and bifacial modules impact the economic metrics of the project, i.e., net present value (NPV) and internal rate of return (IRR). PVSyst software was utilized as a simulation tool, while in-house developed software implementing appropriate technical and economic models served as a comparison platform and was used to validate the outputs generated through PVSyst. Results indicate that the commonly used horizontal single-axis tracking configuration may economically underperform compared with fixed-tilt setups. The optimal DC−AC ratio fe... [more]

Wobble-plate axial piston pumps, characterized by the lack of a slipper mechanism, experience reduced leakage in comparison to their swash-plate counterparts, which contributes to their higher volumetric efficiency. Presently, the primary focus of the research conducted by scholars both domestically and internationally is concentrated on wobble-plate axial piston pumps. The performance studies within this field are predominantly focused on investigating flow pulsation. They also investigate pressure pulsation. Additionally, they investigate cavitation phenomena. Research on inclined-axis axial piston pumps has been limited. This study focused on analyzing the operational form of the piston within an inclined-axis axial piston pump. A correction factor k was introduced based on the motion characteristics of the piston. The application of this factor significantly improved the accuracy of the simulations when compared to the experimental results. Specifically, at a load pressure of 10 MP... [more]

CO2-enhanced coalbed methane recovery (CO2-ECBM) has been demonstrated as an effective enhanced oil recovery (EOR) technique that enhances the production of coalbed methane (CBM) while achieving the goal of CO2 sequestration. In this paper, the grand canonical Monte Carlo simulation is used to investigate the dynamic mechanism of CO2-ECBM in anthracite pores. First, an anthracite pore containing both organic and inorganic matter was constructed, and the adsorption and diffusion characteristics of CO2 and CH4 in the coal pores under different temperature and pressure conditions were studied by molecular dynamics (MD) simulations. The results indicate that the interaction energy of coal molecules with CO2 and CH4 is positively associated with pressure but negatively associated with temperature. At 307.15 K and 101.35 kPa, the interaction energies of coal adsorption of single-component CO2 and CH4 are −1273.92 kJ·mol−1 and −761.53 kJ·mol−1, respectively. The interaction energy between ant... [more]

In recent years, with the rapid development of salt cavern gas storage reservoir construction in China, the characteristics of salt rock reservoirs with strong non-homogeneity and many interlayers have brought challenges to the dynamic prediction of water solution cavity construction. Aiming to solve this problem, this paper constructs a three-dimensional non-homogeneous salt cavern reservoir water-soluble cavity building prediction model, which takes into full consideration the non-homogeneity of salt rock reservoirs, interlayers, reservoir temperatures, and water injection process parameters, among other factors. By comparing the calculation results of the software compiled by the model with those of other numerical simulation software, we show that the model can accurately reflect the influence of geological parameters on the cavity morphology under the condition of non-uniform geological parameters, with higher simulation accuracy, and ultimately analyze individual examples. It can... [more]

Maximizing the yield of bioactive molecules extracted from plant materials requires the investigation of extraction process variables; therefore, in this research, a traditional aqueous solid−liquid extraction method was employed on two distinct grape pomace skin samples. The grape skin pomace represents a potentially valuable source of biologically active compounds, particularly polyphenols. Experiment 1 utilized ground grape pomace skin, whereas experiment 2 utilized grape pomace skin that had been both dried and ground beforehand. Employing a Box−Benkhen experimental design and response surface modeling in the Statistica 14.0 software package, this study evaluated the impact of temperature, extraction time, solid-to-liquid ratio (S/L), and mixing speed on extraction efficiency. The extracted compounds were assessed for both physical properties (conductivity, total dissolved solids, and pH) and chemical properties (total polyphenol content and antioxidant activity using 2,2-Diphenyl-... [more]

An ARM Cortex simulation system for collaborative welding robots is presented in this paper. The components of the ARM Cortex SoC for embedded robot control, an OpenGL ES with image rendering, and a 3D geometry engine OpenCasCade for modeling are integrated for the purposes of simulating system self-controllability and cost effectiveness. This simulation of a collaborative welding robot achieved convenience while meeting the performance requirements; meanwhile, the auxiliary design was able to mark the trajectory of the robot’s end effector and reveal the collaborative robot’s inverse kinematic parameters, namely the position and Euler angle. An ARM Linux X11 Window environment that was set to create a 3D simulation rendering algorithm was built simultaneously. Then, the STEP model of the robot was loaded by using the OpenCasCade functionality. After that, the robot model and complex spline surface could be visualized by using the Qt QGLWidget. Finally, the correctness of the kinematic... [more]

Vertical-axis wind turbines (VAWTs) are receiving more and more attention as they involve simple design, cope better with turbulence, and are insensitive to wind direction, which has a huge impact on their cost since a yaw mechanism is not needed. However, VAWTs still suffer from low conversion efficiency. As a result, tremendous efforts are being exerted to improve their efficiency, which mainly focus on two methods, regardless of whether the study is a CFD simulation, a field test, or a lab test experiment. An active approach involves modification of the rotor itself, such as the blade design, the angle, the trailing and leading edges, the inner blades, the chord thickness, the contra-rotating rotor, etc., while the second approach involves passive techniques where the flow is directed to optimally face the downwind rotor by mounting guiding vanes such as a diffuser or other shapes at the upwind position of the rotor. Among all the techniques undertaken, the counter-rotating wind tur... [more]

In order to explore the wind load characteristics acting on solar photovoltaic panels under extreme severe weather conditions, based on the Shear Stress Transport (SST) κ-ω turbulence model, numerical calculations of three-dimensional incompressible viscous steady flow were performed for four installation angles and two extreme wind directions of the solar photovoltaic panels. The wind load characteristics on both sides of the photovoltaic panels were obtained, and the vortex structure characteristics were analyzed using the Q criterion. The results indicate that, under different installation angles, the windward side pressure of the solar photovoltaic panel is generally higher than the leeward side. The leeward side is prone to forming larger vortices, increasing the fatigue and damage risk of the material, which significantly impacts the solar photovoltaic panel. As the installation angle increases, the windward side pressure of the solar photovoltaic panel also gradually increases.... [more]

The additive manufacturing (AM) field is rapidly expanding, attracting significant scientific attention. This family of processes will be widely used in the evolution of Industry 4.0, particularly in the production of customized components. However, as the complexity and variability of additive manufacturing processes increase, there is an increasing need for advanced techniques to ensure quality control, optimize performance, and reduce production costs. Multiple tests are required to optimize processing variables for specific equipment and processes, to achieve optimum processing conditions. The application of digital twins (DTs) has significantly enhanced the field of additive manufacturing. A digital twin, abbreviated as DT, refers to a computer-generated model that accurately depicts a real-world object, system, or process. A DT comprises the complete additive manufacturing process, from the initial conception phase to the final manufacturing phase. It enables the manufacturing pr... [more]

Severe blockages of tunnel drainage systems greatly affect the lining structure of the tunnels, thus jeopardizing their stability and safety. In order to study the blockages of tunnel drainage pipes, the flow rate of a calcium carbonate crystal tunnel was measured in the mountainous area of Southwest China. According to the actual flow velocity results, numerical simulation was combined with finite element software (ANSYS Fluent). This analyzed the calcium carbonate crystallization near the interface of the tunnel drainage pipe. The results are as follows: (1) for both the Y-shaped three-way pipe and the T-shaped pipe, the values of maximum water velocity are similar but occur at different locations. At the interface of the transverse drainage pipes, flow velocity is the highest; (2) at the three-way joint segment, the water that flows in the longitudinal drainage blind tube is influenced by the water coming from the annular drainage blind tube. At the interface of the transverse drain... [more]

The bubbling flow plays a key role in gas−liquid−solid fluidized beds. To understand the intrinsic fluidization behaviors at the discrete bubble and particle scale, coupled simulations with the volume of fluid model and the discrete element method are performed to investigate the effects of the gas inlet velocity, particle properties and two-orifice bubbling flow on particle fluidization. Three-dimensional simulations are carried out to accurately capture the dynamic changes in the bubble shape and trajectory. A bubbling flow with a closely packed bed is simulated to study the onset of particle fluidization. The obvious phenomena of particle fluidization are presented by both the experiment and simulation. Although an increasing gas inlet velocity promotes particle fluidization, the good fluidization of particles cannot be achieved solely by increasing the gas inlet velocity. When the channel is packed with more particles, the bubbles take a longer time to pass through the higher parti... [more]

This study examined the multi-phase flow field for a single object and two parallel/series objects under different incoming angles of lateral flow. The volume of fluid model, the Sauer−Schnerr cavitation model, and the six degrees of freedom (DOF) method were adopted to consider simulations of multi-phase flow, phase change, and object movement, respectively. The results show that, for a single object, the degree of asymmetry in the cavity profile depends on the component (the z-component) of the lateral inflow velocity in the direction perpendicular to the initial velocity of the object. As this component increases, the asymmetry of the cavity increases. The cavity length is related to the relative axial speed between the object and the water. For parallel objects, the cavity asymmetry is determined by the superimposed influence of the z-component of the lateral incoming speed and the high-pressure zone induced by the nearby object. The object located downstream relative to the latera... [more]

In inertial confinement fusion, the sub-atmospheric purging through microcapillaries is of great importance to the high gas purity inside the cryogenic target and the low failure rate of experiments. In this study, a non-continuous flow model is developed for this sub-atmospheric purging process and verified through National Ignition Facility experiments to study the evolution of parameters such as pressure and gas composition that are not possible to measure directly. The effects of microcapillary structures and sizes on the transient evacuation−filling behaviors are analyzed, and the periodic purging scheme is optimized. The results show that the extension of evacuation and filling time caused by the elongated microtube can be described as a linear function of microtube length or an exponential decay function of microtube diameter, and the change of the inner diameter has a more drastic effect. The conical-straight composite can effectively reduce the evacuation and filling time whil... [more]