Flow and Transition Analysis

⚫ Transitioning from Steady-State to Dynamic Simulation in Aspen HYSYS: A Must-Know for Process Engineers In process engineering, steady-state simulation is a fundamental approach for design, optimization, and performance evaluation. However, real-world operations are never in a true steady state—startup, shutdown, disturbances, and transient conditions must be accounted for. This is where dynamic simulation in Aspen HYSYS becomes a crucial tool for engineers aiming to enhance process safety, reliability, and efficiency. Why is Dynamic Simulation Essential? 🔹 More Accurate Process Representation – Unlike steady-state models, dynamic simulation accounts for time-dependent changes such as pressure surges, flow variations, and equipment response. 🔹 Control Strategy Development & Testing – It allows the design, implementation, and fine-tuning of PID controllers, safety valves, and pressure regulators to ensure process stability. 🔹 Operational Safety & Troubleshooting – Detects potential risks such as overpressure, flow instabilities, and equipment failures before they occur in real operations. 🔹 Startup & Shutdown Optimization – Simulates transient conditions to optimize procedures and reduce energy losses, downtime, and operational risks. 🔹 Training & Digital Twin Applications – Used in operator training, virtual commissioning, and real-time process monitoring. Key Steps for a Successful Transition to Dynamic Simulation: ✔ 1. Equipment Sizing & Dynamic Parameters Define appropriate volumes, residence times, and response characteristics for all equipment. Ensure that vessels, heat exchangers, and pipes have realistic holdup capacities. ✔ 2. Defining Process & Flow Specifications Configure pressure-flow relationships across the process. Define valve characteristics (Cv values, flow coefficients) for accurate dynamic response. ✔ 3. Implementing Control Strategies Add and tune Flow (FIC), Pressure (PIC), and Level (LIC) controllers for operational stability. Optimize PID tuning parameters to achieve smooth process response. ✔ 4. Setting Up Dynamic Simulation Parameters Enable Dynamic Mode in Aspen HYSYS. Choose a realistic time step (e.g., 0.1 to 1 second) to balance accuracy and stability. Run initial system checks to detect oscillations, instabilities, or incorrect control actions. ✔ 5. Validating & Optimizing the Dynamic Model Test system responses to small disturbances. Adjust control loops and valve performance curves for optimal results. Are you currently using Aspen HYSYS for dynamic simulation? What are the biggest challenges you've faced when transitioning from steady-state models? Let’s discuss in the comments! #AspenHYSYS #ProcessSimulation #DynamicSimulation #ProcessControl #PIDTuning #ChemicalEngineering #OilAndGas #Refining #AspenTech #DigitalTransformation #ProcessOptimization #IndustrialAutomation #ProcessEngineering #EngineeringTraining #SimulationSoftware #HSE #OperatorTraining #IndustrialSafety #EnergyTransition

🚨 New preprint! 🔬 Detecting transient events in single-cell omics data We wondered whether genes spike when cells transition from one state to another. There may be brief but crucial regulatory events that are easy to miss in single-cell data. We’re excited to share scTransient, a new trajectory-inference method that uses wavelet-based signal processing to detect these fleeting molecular surges. By scoring transient events along pseudotime, scTransient reveals short-lived gene or protein expression bursts that typical differential expression methods overlook. 💡 Highlights: • Captures transient regulators in hematopoiesis, macrophage differentiation, and the cell cycle • Integrates seamlessly into our cloud-based platform PSCS for interactive, reproducible analysis: pscs.xods.org • Open-source and ready to use: https://lnkd.in/d4_mN_tY This work is part of our broader effort to extract more dynamic insights from single-cell data—and we hope it helps others do the same. 🔍 What we did We tested scTransient across synthetic benchmarks and three diverse single-cell datasets: 🩸 Hematopoiesis (scRNA-seq): We recovered transient spikes in erythropoiesis regulators like Nfe2, Tmem14c, and Glrx5, pinpointing short-lived expression changes critical to red blood cell maturation. 🧫 Monocyte-to-macrophage differentiation (SCoPE2 proteomics): scTransient revealed clusters of proteins with sharp shifts along pseudotime not captured by standard differential expression, including components of membrane raft remodeling and S100 protein signaling. Proteomic data offered a smoother, more continuous trajectory than transcriptomics, highlighting its potential for capturing gradual transitions. 🧬 Cell cycle progression (deep single-cell proteomics of A549 cells): We uncovered transient surges in proteins involved in S-phase DNA replication and RNA processing, such as PCNA and UNG, as well as previously unreported candidates near the G1/S transition. Remarkably, many of these proteins were not known cell cycle markers, underscoring the method’s utility in uncovering new regulatory players. 🧠 Why it matters scTransient adds a quantitative lens to single-cell trajectories—helping researchers detect brief regulatory programs that would otherwise be missed. It’s available on the cloud-based PSCS platform, enabling easy, reproducible exploration of transient biology across modalities and conditions. Feedback, questions, and collaborations welcome! #SingleCell #Omics #TrajectoryInference #Proteomics #Bioinformatics #Preprint 📄 https://lnkd.in/dM2nUdUN

Velocity Profile Development vs. Flow Transmitter Installation In fluid dynamics, understanding the velocity profile is essential for knowing how fluids behave as they flow through pipes or channels. Obstructions in a flow path can significantly affect the fluid's velocity. When fluid encounters an obstruction, it can create turbulence and variations in flow speed. This means that the velocity is not uniform; certain areas may have higher or lower speeds. Fluid takes a specific distance to transition from an unstable to a stable state, which is referred to as hydraulic length. This hydraulic length is the distance over which the flow changes from a disturbed state to a stable velocity profile. It is critical for engineers to know this distance because it helps predict how long it will take for the flow to stabilize after encountering changes in the system, such as bends, valves, or other obstructions. This distance is very important for selecting the proper location for flow transmitters. To measure flow accurately, instruments should be installed upstream of the control valve or at a location where the flow is fully developed. Placing these instruments in the right location is vital for capturing the fully developed velocity profile. If measurements are taken too close to obstructions, they may not accurately reflect the true flow characteristics. as depicted in below photo The velocity profile develops through three main stages: the rotational flow region, the developing layer, and the fully developed velocity profile. Initially, in the rotational flow region, the flow is chaotic. As the fluid moves further along the pipe, it enters the developing layer, where the velocity begins to stabilize. Finally, in the fully developed velocity profile, the flow becomes uniform and predictable.