Process Flow Research Articles

Analysis of flow and energy dissipation in pump turbine with small guide vane opening

In this study, a detailed flow state analysis of a reversible pump turbine (RPT) under small guide vane opening conditions was conducted using both numerical simulation and experimental methods on three analysis planes at 0.5 span. The entropy production rate (EPR) in entropy production theory was utilized to visualize the location and magnitude of energy losses in the flow process. The focus was placed on the coherent vortex structures in the volute, stay vane, guide vane, and runner flow path. The results demonstrate that, throughout the runner’s cycle, the leading edge of the guide vane experiences low-pressure regions with uneven pressure distribution within the runner channel. Velocity streamlines reveal flow separation and vortex generation at the typical guide vane trailing edge, with a maximum velocity reaching 49.7. Analysis of radial force and torque on typical guide vanes and the runner indicates that radial force and torque on the guide vanes do not significantly change, with the radial force coefficient CF r−x varying between 0.254 and 1.3. Major energy losses are concentrated behind the trailing edge of the guide vane, primarily in the form of jet wake. Coherent vortex structures are observed in the volute, stay vane, guide vane, and runner flow path, with slight turbulent wake at the trailing edge of the stay vane, clear shedding vortex streets, and vortex build-up in the bladeless area between the guide vane and the runner.

Tunable diode laser absorption spectroscopy monitoring of the water vapor condensation process in the high-speed flow

Abstract In this work, non-invasive high-precision quantitative measurements of the water vapor condensation process have been carried out using tunable diode laser absorption spectroscopy(TDLAS) at the sub-millisecond level. The high-speed condensation of water vapor is achieved by a self-designed rarefaction wave reflection system. Combined with different sizes of experimental cavities, the condensation process is realised at various time scales of sub-milliseconds (0.2-0.66 ms). The processes of temperature and water vapor content during the high-speed condensation are measured using the water vapor absorption spectra near 7168.437 cm-1 and 7185.597 cm^-1. The experimental results show that the hypervelocity expansion flow field generated by the experimental system demonstrates good uniformity and reaches a cooling rate of 10^5 K/s, which has the same order as that of the supersonic nozzle. The condensation process is similar on different sub-millisecond timescales and the normalised temperature change curves are approximately the same. Moreover, the higher the water vapor content, the shorter the condensation time.

Development of evaluation method for radiocesium availability in soil by biomimetic approach.

Applicability of biomimetic approach with simulation of plant uptake for assessment of radiocesium availability in soil was investigated. The soil spiked with 137Cs tracer was contacted with wicking material and copper-substituted prussian blue (Cu-PB), which simulate transpirationally induced mass flow and concentration gradient-induced diffusion of radiocesiumin the soil, respectively. Comparison of the removed 137Cs to the wick and the wick + Cu-PB from the soil during the contact period of 12weeks suggested that the diffusion process has larger contribution than the mass flow process in radiocesium dynamics in root zone. The change of the removed rate of 137Cs from the soil was reflected that its availability decreased with the time elapsing and with subjecting repeated wet-dry treatment. The results suggest that the biomimetic approach can be applicable to the realistic evaluation of the availability of radiocesium in soil.

ABOUT WORK IN PROGRESS IN THE CONTEXT OF INTRALOGISTICS

The current paper attempts, briefly and in general terms, to present the need for work-in-progress for the normal flow of the production process. This ensures the rhythmicity and continuity of the flow of production. The basis for achieving these two characteristics is also the so-called reserve, which should be in sufficient quantity.

Lessons learned in 3D modelling of underground structures

Gloria Wong and Trieska Wahyudi share their experiences in the 3D modelling of underground structures (primarily stations) for design, including the key lessons they have learned and the process flows they have developed consequently.

QLTI-21. STREAMLINING THE STUDY INTAKE PROCESS AT THE CANCER CLINICAL AND TRANSLATIONAL RESEARCH OFFICE (CCTRO)

Abstract Challenges in the Protocol Intake/Activation process at the Henry Ford Cancer Center, particularly during the budget negotiation and coverage analysis (CA) phases, hamper operational efficiency and financial prospects. This study aimed to improve budget time and process efficiency. Process flow mapping, Value Stream Mapping (VSM), and cause-effect analysis using a fishbone diagram were used to identify and analyze key bottlenecks, focusing on the budget negotiation and CA phases. Budget negotiation took an average of 121.5 days in 2023 due to multiple procedures and a lack of standardized practices. Delays ranged from 127.75 days in August to a low of 69.84 days in November of 2023. The budget build process averaged 13.31 days, with an additional 7.57 days for approval, totaling 20.89 days. The CA phase had an average cycle time of 10.82 days (range 2-10 days). To improve approval times, it was recommended to implement an Electronic Document Management System to automate routing, signing, and tracking of budget and CA-related documents, standardized budget templates to streamline negotiations, a detailed electronic checklist to streamline task lists for document collection and budget negotiation, automated reminders for internal and external stakeholders to ensure timely submission of necessary documents, and timely submission policies enforced by a dedicated finance member on committees. Newly developed Key Performance Indicators (KPIs) such as ‘time to collect documents,’ ‘time between committees,’ and ‘time for budget negotiation process,’ along with a dual tracking system in Excel, were proposed to monitor and improve these metrics. The recommendations are expected to significantly enhance the efficiency of the Protocol Intake/Activation process. By reducing the budget negotiation phase to less than 60 days and optimizing the CA process, faster study initiation, better resource utilization, and improved responsiveness to research opportunities will be achieved. This study underscores the critical need to address operational challenges in clinical trial management to enhance CCTRO’s capability to conduct timely and effective research.

Stable Non-equilibrium Structures in Chiral Nematics under Microfluidic Flow.

Cholesteric liquid crystals (CLCs) are compelling responsive materials with applications in next-generation sensing, imaging, and display technologies. While electric fields and surface treatments have been used to manipulate the molecular organization and, subsequently, the optical properties of CLCs, their response to controlled fluid flow has remained largely unexplored. Here, we investigate the influence of microfluidic flow on the structure of thermotropic CLCs that can exhibit structural coloration. We demonstrate that the shear forces that arise from microfluidic flow align the helical axis of CLCs; alignment is a prerequisite for harnessing the promising photonic properties of CLCs. Moreover, we show that microfluidic flow can generate non-equilibrium structures exhibiting photonic band gaps that are inaccessible in the stationary cholesteric phase. Our findings have implications for the use of CLCs in applications involving flow processing such as additive manufacturing.

Advances in Powder-Filled Mold Processes: A Comprehensive Review and Outlook

Powder molding technology is a versatile process widely used in the pharmaceutical, ceramic, chemical, food, and powder metallurgy industries. The powder-filling mold process is a key link in powder compression molding, and the uniformity and consistency of powder filling directly affect the final quality of powder products. Powder filling of molds is a more complex flow process. This paper first reviews the methods used to test powder flow characteristics and comments on their applicability to the mold-filling process, provides an in-depth discussion of four different filling techniques, focusing on the flow behavior of the powder during the filling process, and analyzes the effects of powder characteristics and process parameters on the filling effect. By reviewing the latest advances and identifying the key challenges, a valuable reference is provided for the mold-filling process.

Simulation of landslide dam failure due to overtopping considering wide-graded soil erosion

Landslide dams, as a particular type of secondary geological disaster, can cause serious flood disasters. Therefore, accurately predicting potential dam failure processes is crucial for developing reasonable emergency response plans. Currently, several landslide dam failure models have been proposed, but most of these models do not appropriately consider the wide gradation of landslide dam materials, which is essential for accurate erosion calculations. Therefore, this research proposes a relative exposure formula under three-dimensional conditions to account for the concealment and exposure effects between large and small particles in wide-graded soil. Based on this, the incipient velocity of wide-graded soil is derived, and a mathematical model of overtopping failure of landslide dams is established. As part of the model, a numerical solution process is also developed to ensure convergence. To evaluate the performance of this new mathematical model, the discharge process of Tangjiashan landslide dam was used as a real-world case for dam failure calculation. The calculated results of key dam failure outcomes were compared with actual measurements, showing that the results of this model are largely consistent with actual measurements, with the error controlled within 10%. Additionally, the mathematical model proposed in this article was compared with two other existing dam failure models, revealing that the model proposed here has advantages in controlling the error of key dam failure outcomes, mainly due to the comprehensive consideration of erosion calculation in wide-graded soil. To further evaluate the stability of the model, the breach processes of the “11.3” Baige landslide dam and the Yigong landslide dam were also calculated, and the results showed reasonable consistency. Based on the model presented in this article, the influence of the grading width of landslide dam materials on key dam failure outcomes was discussed. It was found that grading width significantly affects the development process of breach flow. Specifically, wider grading width leads to smaller peak values of breach flow and later peak times. Additionally, the final size of the breach is affected by grading width, as it has a significant impact on erosion strength, although the sensitivity of this parameter is relatively weak. Given the significant impact of grading width on the dam failure process, especially for landslide dams containing wide-graded soil, it is essential to fully consider the wide grading of materials for accurate dam failure calculations.

Unveiling the fundamentals of flow boiling heat transfer enhancement on structured surfaces.

Micro- and nanostructured surfaces offer the potential to enhance two-phase heat transfer. However, the mechanisms behind these enhancements are not well-understood due to insufficient diagnostic methods, leading to reliance on trial-and-error surface development. We introduce in situ boroscopy to investigate microscale bubble dynamics during flow boiling nucleation and subsequent flow regime development. This method was applied in saturated flow boiling experiments within chemically etched aluminum and copper tubes. Although the surfaces have self-similar surface structures, our findings revealed varied heat transfer coefficient enhancements, with increases of up to 391% on aluminum and 41% on copper. Using boroscopy, we identified key mechanisms of heat transfer enhancement. We further used mercury porosimetry to determine the impact of pore size distribution on thermal performance. The boroscopy technique introduced here not only elucidates the underlying processes of flow boiling heat transfer enhancement but also has potential applications for the study of other two-phase phenomena.

Implementation of Artificial Intelligence Technology-Based Learning Media at SD Negeri Kotagede 1 Yogyakarta

In the digital era, the field of education is witnessing the transformation that occurs through the integration of artificial intelligence (AI). With artificial intelligence's (AI) potential to revolutionize various sectors, it presents itself as a material or tool that can enhance the teaching and learning experience. Its features align with our thinking, enabling us to progress according to our desired content. Artificial intelligence (AI) is today's most important tool in education. Artificial intelligence (AI) plays a crucial role in enabling the use of AI-based learning media, thereby facilitating the learning process in education. Artificial intelligence (AI)--based learning media in education will aid teachers and students in learning. This study aims to provide insight to all of us regarding the implementation of learning media based on artificial intelligence (AI) technology at SD Negeri Kotagede 1 Yogyakarta. This study employs a descriptive-qualitative approach. In the current educational landscape, particularly at SD Negeri Kotagede 1 Yogyakarta, artificial intelligence (AI) plays a crucial role. Artificial intelligence (AI) can facilitate the learning process flow by using learning media based on artificial intelligence technology. Teachers can utilize artificial intelligence to design programs and learning processes, while students can enhance their comprehension of the material and cultivate their critical thinking skills. Implementing learning media based on artificial intelligence (AI) technology can benefit educational institutions in a more interesting, innovative, effective, and creative learning process.

A Sensitive Frequency Band Study for Distributed Acoustical Sensing Monitoring Based on the Coupled Simulation of Gas–Liquid Two-Phase Flow and Acoustic Processes

The sensitivity of gas and water phases to DAS acoustic frequency bands can be used to interpret the production profile of horizontal wells. DAS typically collects acoustic signals in the kilohertz range, presenting a key challenge in identifying the sensitive frequency bands of the gas and water phases in the production well for accurate interpretation. In this study, a gas–water two-phase flow–acoustic coupling model for a horizontal well is developed by integrating a gas–water separation flow model with a pipeline acoustic model. The model simulates the sound pressure level (SPL) and amplitude variations of acoustic waves under different flow patterns, spatial locations, and gas–water ratio schemes. The results demonstrate that within the same flow pattern, an increase in the gas–water ratio significantly elevates acoustic amplitude and SPL peaks within the 5–50 Hz frequency band. Analysis of oil field DAS data reveals that the amplitude response range for stages with a lower gas–water ratio falls within 5–10 Hz, whereas stages with a higher gas–water ratio exhibit an amplitude response range of 10–50 Hz.

Production Technological Design for 500,000 Tonnes Per Year of Ethylene Glycol

Effective and reasonable chemical design of ethtlene glycol production process is of vital significance for the further improvement of our ethylene glycol production capacity. This paper carried out reasonable design of ethylene glycol water lawful production process, using reaction rectifying tower device, and optimizing calculation for each link of production, so as to obtain satisfactory products. In the comprehensive consideration of production efficiency and cost saving and other aspects of the relevant equipment is reasonable selection, and draw the PID process flow chart. It is expected to produce 500,000 tons of pharmaceutical grade glycol with mass fraction of 99.89%.

Comprehensive review of additive manufacturing lifecycle optimization in a cloud environment: from distributed manufacturing to postprocessing

Purpose This paper aims to offer a comprehensive review and categorization of production optimization throughout the additive manufacturing lifecycle in a cloud environment. It aims to provide a structured approach to identifying and addressing issues. Design/methodology/approach This paper systematically reviews 75 technical papers on cloud manufacturing, nesting, scheduling and postprocessing in additive manufacturing. This includes a detailed discussion of the key issues. Findings This paper introduces a production framework for the entire lifecycle of additive manufacturing in a cloud environment. This framework aids in problem identification and decision-making based on the process flow. It provides an integrated view from cloud to postprocessing, examining decision interdependencies and enhancing problem identification and organization. Originality/value To the best of the authors’ knowledge, this paper is the first to review the complete lifecycle of additive manufacturing, emphasizing the often-overlooked aspects of postprocessing and cloud manufacturing. It offers a comprehensive study of lifecycle optimization challenges and suggests ways to streamline the production process.

The Regional Scale of Landscape Planning: the Possibilities for Measuring the Effectiveness of Nature-Based Solutions

Aim: The aim of this study is to investigate the measurement of landscape integrity based on ecological support processes in the Federal District, with the aim of defining a multi-scalar and multi-functional Regional Green Infrastructure Network (IVR) based on Nature-Based Solutions (NBS). Theoretical Framework: This topic presents the main concepts and theories that underpin the research. Landscape Ecology, Restoration Ecology, Green Infrastructure and Geodesign stand out, providing a solid basis for understanding the research context. Method: The methodology adopted for this research comprises the analysis of ecological support processes in the landscape, using the multispectral “CO2flux” index, related to the photosynthetic efficiency of vegetation and a proxy for energy, carbon and biomass inputs, which, together with the “Topographic Wetness Index”, related to the flow and accumulation of water and sediment in the landscape, provided the basis for the elaboration of a Geodesign process. Data was collected using multispectral satellite scenes - “Landsat 8”, collected during the dry season. Results and Discussion: The results obtained revealed the design of a mosaic of “hotspots”, corridors and patches that consolidates and intensifies carbon flows in the Federal District's landscape, with positive impacts on territorial resilience. In the discussion section, these results are contextualized in the light of the theoretical framework, highlighting the implications and relationships identified. Possible discrepancies and limitations of the study are also considered in this section. Research Implications: The practical and theoretical implications of this research are discussed, providing “insights” into how the results can be applied, or how to influence practices in the field of landscape planning. These implications can cover the design of Nature-Based Solutions at a regional scale, climate mitigation and adaptation actions for territories, and people's access to ecosystem services. Originality/Value: This study contributes to the literature by proposing the design of a regional network of green infrastructures based on the analysis of the flow of ecological support processes in the landscape, considering different demands and goals for environmental recovery. The relevance and value of this research is evidenced by the possibility of planning and designing mosaics in the landscape based on the identification of networks with greater potential for the provision of ecosystem services and, consequently, for the adaptation and mitigation of territories to climate impacts and those resulting from human occupation.

CSF flow measurement in the mesencephalic aqueduct using 2D cine phase-contrast MRI in dogs with communicating internal hydrocephalus, ventriculomegaly, and physiologic ventricular spaces

BackgroundBrachycephalic dogs are overrepresented with ventricular enlargement. Cerebrospinal fluid (CSF) flow dynamics are not completely understood. MRI techniques have been used for the visualization of CSF dynamics including phase-contrast imaging.ObjectivesThis study aimed to determine a causality between CSF flow and ventriculomegaly or hydrocephalus and to compare CSF flow dynamics among dogs with ventriculomegaly, internal hydrocephalus, and physiologic ventricles.AnimalsA total of 51 client-owned dogs were included in the study.MethodsMagnetic resonance imaging (MRI)-based FLASH sequences and phase-contrast images of the brain were obtained, and the ROI was placed at the level of the mesencephalic aqueduct. ECG monitoring was performed parallel to MRI acquisition. Evaluation of flow diagrams and processing of phase-contrast images were performed using commercially available software (Argus VA80A, Siemens AG Healthcare Sector, Erlangen, Germany). Dogs were divided into three groups: Group 1 consisted of brachycephalic dogs with ventriculomegaly (group 1A) or internal hydrocephalus (group 1B), group 2 consisted of brachycephalic dogs with normal ventricles, and group 3 consisted of meso- to dolichocephalic dogs with normal ventricles.ResultsGroup 1 had a higher median Vrost (4.32 cm/s; CI: 2.94–6.33 cm/s) and Vcaud (−6.1 cm/s, CI: 3.99–9.33 cm/s) than group 2 (Vrost: 1.99 cm/s; CI 1.43–2.78 cm/s; Vcaud: 2.91 cm/s, CI: 2.01–4.21 cm/s; p = 0.008; p = 0.03) and group 3 (Vrost:1.85 cm/s, CI: 1.31–2.60 cm/s; Vcaud − 2.46 cm/s, CI 1.68–3.58 cm/s; p = 0.01; p = 0.02). The median Volcaud of group 1 (−0.23 mL/min, CI: 0.13–0.42 mL/min) was higher than that of group 2 (−0.09 mL/min, CI: 0.05 mL/min and 0.15 mL/min) (p = 0.03). Groups 1A and 1B did not differ in Vcaud, Vrost, Volcaud, and Volrost. Group 1A and 1B showed a higher median Vrost (4.01 cm/s, CI: 2.30–7.05 cm/s; 5.94 cm/s, CI: 2.16–7.88 cm/s) than group 2 (1.85 cm/s, CI: 1.24–2.80 cm/s.) (p = 0.03; p = 0.004).Conclusion and clinical importanceIncreased CSF flow velocities in rostral and caudal directions are present in dogs with ventriculomegaly and internal hydrocephalus compared to normal controls.

A reinforcement learning-based approach for solving multi-agent job shop scheduling problem

Wafer processing is the most expensive, time-consuming, and complex stage in semiconductor manufacturing. It varies significantly based on orders of customers (agents). Optimising the wafer processing flow in a multi-agent scenario can meet customised requirements, speed up delivery, and reduce costs. This work models wafer processing as a multi-agent job shop scheduling problem (MAJSP) with release dates. The objective is to minimise the total weighted makespan of agents. To address both dynamic and static scheduling scenarios in the MAJSP context, two deep reinforcement learning-based (DRL) methods are proposed. In a dynamic scheduling scenario, the statuses of orders and production resources can change at any moment. A DRL method called Graph Transformer Network (GTN) is proposed to rapidly generate high-quality solutions. In a static scheduling scenario, the production plan can be formulated based on predetermined demand and resource conditions. A novel hybrid method (GTN-DABC) that combines GTN with the discrete artificial bee colony algorithm (DABC) is proposed to provide high-quality production plans for manufacturers within an acceptable computation time. Experimental results demonstrate that the proposed GTN outperforms existing heuristics, and the well-designed GTN-DABC is more competitive than other meta-heuristics.

Reforming Natural Gas for CO2 Pre-Combustion Capture in Trinary Cycle Power Plant

Today, most of the world’s electric energy is generated by burning hydrocarbon fuels, which causes significant emissions of harmful substances into the atmosphere by thermal power plants. In world practice, flue gas cleaning systems for removing nitrogen oxides, sulfur, and ash are successfully used at power facilities but reducing carbon dioxide emissions at thermal power plants is still difficult for technical and economic reasons. Thus, the introduction of carbon dioxide capture systems at modern power plants is accompanied by a decrease in net efficiency by 8–12%, which determines the high relevance of developing methods for increasing the energy efficiency of modern environmentally friendly power units. This paper presents the results of the development and study of the process flow charts of binary and trinary combined-cycle gas turbines with minimal emissions of harmful substances into the atmosphere. This research revealed that the net efficiency rate of a binary CCGT with integrated post-combustion technology capture is 39.10%; for a binary CCGT with integrated pre-combustion technology capture it is 40.26%; a trinary CCGT with integrated post-combustion technology capture is 40.35%; and for a trinary combined-cycle gas turbine with integrated pre-combustion technology capture it is 41.62%. The highest efficiency of a trinary CCGT with integrated pre-combustion technology capture is due to a reduction in the energy costs for carbon dioxide capture by 5.67 MW—compared to combined-cycle plants with integrated post-combustion technology capture—as well as an increase in the efficiency of the steam–water circuit of the combined-cycle plant by 3.09% relative to binary cycles.

Optimizing Hierarchical Condition Category-Risk Adjustment Factor Management in Population Health Using Rapid Process Improvement Methods.

Centers for Medicare & Medicaid Services provides reimbursement through Hierarchical Condition Category (HCC) coding. Medical systems strive toward risk adjustment optimization, often implementing costly chart review processes. Previously, our organization implementing countermeasures through workflows was complex and performed in silos. Our goal was to put in place HCC-Risk Adjustment Factor (RAF) improvement tools to optimize HCC-RAF management in Population Health using rapid process improvement methods. In this quality improvement analysis (IRB#806198), we used Lean methodology to develop tools and implement streamlined processes for providers to manage, document, and code high-risk HCC conditions. Rather than applying costly countermeasures, Transformational Healthcare conducted a Rapid Process Improvement Workshop (RPIW), with workgroups implementing proposed changes, to improve processes. Each of these tools was embedded in standard work, for teams to use in practice. Tools included the development of RPIW-inspired work groups, a Provider Education website, tip sheets, clinical champions, trainings, audits, practice alerts, smart phrases, schedule view tools, severity scores, reports, dashboards, on-screen decision-support tools, coding expertise, and HCC standard work. Quantitatively, Year 1 showed enterprise HCC-RAF scores improved by 4.1%. We were able to develop tools for providers and team members to allow for more optimized pathways. Although quantitatively we realized an improvement in enterprise HCC-RAF score, our overall aim was to improve process flow and limit waste. Leveraging Lean improvement methods for the collective design of tools has supported culture change. In the end, we found that providers are indeed willing to adopt these newly built tools. These tools have optimized operations, allowing providers to work smarter, not harder.

Reproduction of the chain process of debris flow blocking river at a catchment scale: a numerical study

Reproduction of the chain process of debris flow blocking river at a catchment scale: a numerical study