Process Industries Research Articles

Analysis of thermal significances of nanofluids in inclined magnetized flow with Joule heating source and slip effects

The growing need for effective thermal management systems in engineering applications will improve performance by using nanofluids. Nanofluids, which show enhanced thermal characteristics compared to typical fluids, offer an effective way for heat transmission processes in industries. This study is particularly useful for systems where traditional fluids are insufficient for improving thermal performance. Understanding the overall impacts of Joule heating, magnetic fields, and slip conditions would be beneficial in fields such as aircraft, microelectronics, and biomedical engineering.The thermal significances of nanofluids in an inclined magnetized flow are analyzed in this work, taking slip effects and the Joule heating source into account. The motivation behind the current research is to investigate the flow and heat transfer behavior of magnetohydrodynamic (MHD) nanofluid under the influence of Joule heating in the presence of slip conditions.Based on conservation laws and suitable boundary conditions, the governing formulas for mass, momentum, energy, and nanoparticle concentration are developed. In this thermal investigation, unsteady nanofluid flow in two dimensions via a nonlinear stretched configuration is studied numerically together with an example of a non-uniform heat source. Using similarity transformation, the governing partial differential equation for chemical radiation and slip effects parameters for hydromagnetic flow is transformed into a set of ordinary differential equation (ODE). To solve these equations, a numerical method is applied. This study found that the velocity, mass transfer, temperature, concentration, heat transfer, and skin friction coefficient are significantly influenced by the chemical reaction, radiation parameter, and velocity slip. A graphical representation of the parameters influencing the heat transfer and the velocity changes in calculation is observed.

An Improved Non-dominated Sorting Genetic Algorithm II for Distributed Heterogeneous Hybrid Flow-shop Scheduling with Blocking Constraints

Distributed manufacturing is a new trend to accommodate the economic globalization, which means multiple geographically-distributed factories can collaborate to meet urgent delivery requirements. However, such factories may vary due to layout adjustments and equipment aging, thus the production efficiency greatly depends on the allocation of orders. This scenario is frequently found in energy-intensive process industries, e.g., chemical and pharmaceutical and industries, where the lack of buffers usually results in extra non-blocking constraints and makes the production scheduling even harder. Therefore, this paper investigates a distributed heterogeneous hybrid blocking flow-shop scheduling problem (DHHBFSP) for minimizing the makespan and total energy consumption simultaneously, and proposes an improved non-dominated sorting genetic algorithm II (INSGA-II) to address the problem. First, two heuristic algorithms, i.e., bi-objective considered heuristic (BCH) and similarity heuristic (SH), are developed for the population initialization. Then, to speed-up the local search, a comparison method for non-dominated solutions is proposed to reserve more solutions that are likely to be further improved. Afterwards, a probabilistic model is developed to eliminate unnecessary operations during local search processes. Finally, the proposed INSGA-II is tested on benchmark instances and a real-world case for the validation. Numerical experiments suggest that the SH can generates high-quality solutions within a very short period of time, and the BCH has significantly improved average IGD and HV values for the initial population. Besides, the probabilistic model saves considerable computational time for the local search without compromising the solution quality. With the help of these strategies, the proposed INSGA-II improves average IGD and HV values by 68% and 57% for the basic NSGA-II respectively, and obtains better Pareto fronts compared to existing multi-objective algorithms on the majority of test instances. Moreover, the industrial case study shows that the proposed INSGA-II is capable of providing solid scheduling plans for a pharmaceutical enterprise with large-scale orders.

An investigative study on the effective utilization of process hazard analysis (PHA) and safety instrumentation system (SIS) in chemical process industries

AbstractThis research paper focuses on effectiveness of process hazard analysis (PHA) and safety instrumented systems (SIS) interventions during process design and implementation which prevents accident and loss in chemical process industries. An initial preview was conducted to analyze the accidents and incidents in case of industrial and chemical process industries which enabled to define the research question in a scientific way. The research was conducted using a survey questionnaire developed with the help of focus group and was based on theoretical and conceptual framework developed for the study. The survey received responses from 36 participants who met the inclusion and exclusion criteria. The validity and reliability were established using confirmatory factor analysis, convergent validity, and Cronbach’s Alpha. The data analysis methods were used to answer the research questions to test the hypotheses. From the results it is observed that PHA and SIS were in an agreeable range. However, the performance factors grouped based on barrier controls and organizational behavior were have moderate positive relationship. This showed there exists a gap in the PHA and SIS contributing factors which may directly or indirectly cause industrial accidents in the chemical process industries.

Centrifugal Compressor Surge in Innovative Heat Pump: Fluid Dynamic and Vibrational Analysis

Abstract In the current energy scenario, it is necessary to reduce fossil fuel consumption to achieve the far-sighted and stringent decarbonization goals. To date, heat is mainly produced through fossil fuels. Alternatively, electrically driven heat pumps can exploit renewable power to recover environmental and waste heat, offering energy efficient and environmentally friendly heating and cooling for applications ranging from domestic and commercial buildings to process industries. For this reason, they are expected to play a primary role in complementing or displacing natural gas boilers in the residential and industrial sectors in the near future. Centrifugal compressors are already used as prime movers of the working fluid in heat pumps, thanks to their industrial replicability, compact size, affordable costs, and good performance in terms of efficiency and low noise. However, they are subject to instabilities such as surge and stall like any other dynamic compressor and these phenomena develop quite differently than in classic open-loop systems such as gas turbines. In fact, such peculiarity is mainly due to the closed-loop configuration with real gases in two-phase conditions, occurring in typical heat pump cycles. In addition, heat exchangers also contribute to make these phenomena different from what is commonly studied. Compressor surge in closed-loop heat pump systems has received lower attention than other applications by the engineering community, lacking dedicated experimental characterization, and clear exposition of the phenomenon. The aim of this paper is to experimentally investigate the behavior of a centrifugal compressor installed into an innovative close loop heat pump system under stable and unstable conditions from both vibrational and fluid-dynamic points of view. The impact of the main process parameters on the evolution of the instability is shown, highlighting how surge cycles change by varying system operating conditions. The energy contents of surge cycles and pressure fluctuations are highlighted, using data postprocessing techniques such as fast Fourier transform and phase locked average. The vibro-acoustic analysis enrich the comprehension of the phenomena. The experimental results shown in this paper can be a basis for the future development of validated mathematical models of closed-loop heat pumps systems equipped with dynamic compressors operating under stable and unstable operating conditions.

Managing human-AI collaborations within Industry 5.0 scenarios via knowledge graphs: key challenges and lessons learned

In this paper, we discuss technologies and approaches based on Knowledge Graphs (KGs) that enable the management of inline human interventions in AI-assisted manufacturing processes in Industry 5.0 under potentially changing conditions in order to maintain or improve the overall system performance. Whereas KG-based systems are commonly based on a static view with their structure fixed at design time, we argue that the dynamic challenge of inline Human-AI (H-AI) collaboration in industrial settings calls for a late shaping design principle. In contrast to early shaping, which determines the system's behavior at design time in a fine granular manner, late shaping is a coarse-to-fine approach that leaves more space for fine-tuning, adaptation and integration of human intelligence at runtime. In this context we discuss approaches and lessons learned from the European manufacturing project Teaming.AI, https://www.teamingai-project.eu/, addressing general challenges like the modeling of domain expertise with particular focus on vertical knowledge integration, as well as challenges linked to an industrial KG of choice, such as its dynamic population and the late shaping of KG embeddings as the foundation of relational machine learning models which have emerged as an effective tool for exploiting graph-structured data to infer new insights.

Novel RP-HPLC method for simultaneous determination of dapagliflozin and teneligliptin in tablet formulation and identification of degradation products by LC-MS/MS

Abstract Background Diabetes mellitus affects millions globally, necessitating effective management strategies. Glenmark Pharmaceutical Limited introduced a fixed-dose combination of teneligliptin and dapagliflozin in 2022 to address this need. However, existing methods for their simultaneous detection are limited, lacking forced degradation studies essential for assessing drug stability. Results A stability-indicating RP-HPLC method was developed for the simultaneous determination of dapagliflozin and teneligliptin in pharmaceutical formulations. The separation was efficiently achieved employing a Zorbax Eclipse Plus C18 column (150 mm × 4.6 mm, 5 µm). The mobile phase comprised a mixture of 10 mM ammonium acetate buffer in water, methanol, and acetonitrile in a suitable proportion and delivered at a flow rate of 0.6 mL/min. Detection of the isocratic eluents was performed at 224 nm using a photodiode array (PDA) detector. Validation against various stress conditions, as per ICH guidelines, revealed significant degradation of teneligliptin primarily under acidic, basic, and oxidative stress. Moreover, liquid chromatography tandem mass spectrometry (LC-MS/MS)-based characterization was conducted for the primary degradation products of teneligliptin generated under acidic, basic, and oxidative conditions. Conclusions The developed RP-HPLC method with a stability-indicating approach provides an efficient means for the simultaneous determination of dapagliflozin and teneligliptin in pharmaceutical formulations. The significant degradation was observed under various stress conditions and also successfully separated the degradation products by this method. The proposed method directly applied for the characterization of degradation products and based on LC-MS/MS data the structure of degradation products was generated and also degradation pathways under various stress conditions were predicted. The proposed method ensured accurate and precise results in quality control process in pharmaceutical industry, and adherence to ICH validation guidelines affirms its reliability in assessing the stability of these compounds.

Study on the Development of an Oyster Shell-Based Clarifier for Enhancing Sugar Industry Processes

Study on the Development of an Oyster Shell-Based Clarifier for Enhancing Sugar Industry Processes

Knowledge Graph Modeling-Driven Large Language Model Operating System (LLM OS) for Task Automation in Process Engineering Problem-Solving

We present the Process Engineering Operations Assistant (PEOA), an AI-driven framework designed to solve complex problems in the chemical and process industries. The framework employs a modular architecture orchestrated by a meta-agent, which serves as the central coordinator, managing an action generator and instruction-tuned small-scale language models (expert models). The action generator decomposes complex problems into sub-tasks and identifies suitable expert models to execute each, delivering precise solutions for multi-step problem-solving. Key techniques include advanced knowledge modeling using property graphs for improved information retrieval, facilitating more accurate and contextually relevant solutions. Additionally, the framework utilizes a teacher-student transfer-learning approach with GPT-4 (Omni) to fine-tune the action generator and expert models for domain adaptation, alongside an iterative problem-solving mechanism with sophisticated error handling. Custom datasets were developed to evaluate the framework against leading proprietary language models on various engineering tasks. The results demonstrate the framework’s effectiveness in automating calculations, accelerating prototyping, and providing AI-augmented decision support for industrial processes, marking a significant advancement in process engineering capabilities.

The role of the construction industry in the recovery of processing enterprises during the crisis

The article discusses the consequences of the crisis period for the work of processing enterprises in Ukraine. It is established that hostilities on the territory of our state and general instability lead to a decrease in production and force processing enterprises to cease their activities. Many enterprises are experiencing serious financial difficulties due to work restrictions, problems with the supply of raw materials, and the loss of industrial facilities. In the summer of 2022, the percentage of companies that closed or were in the process of ceasing operations was 46.8 %. A significant consequence of the war for the Ukrainian economy at the moment is the rapid changes in the territorial location and the change in the symmetry of the processing industry of Ukraine. The war also affected the sectoral structure of the processing industry, producing significant shifts and changes in the volume of products sold. The current political situation in Ukraine and the severance of business chains with the temporarily occupied territories require processing enterprises to search for new markets for products, sources of supply of raw materials, change logistics links, increase the production of raw materials and their own products. During the study, it was found that certain key aspects of the impact on the activities of processing enterprises were previously insufficiently studied. It is determined that the construction industry is of critical importance for the processing industry of the State during the crisis, which is designed to contribute to the recovery of this industry: to develop infrastructure, to build and modernize production facilities, which allows to introduce new technologies and optimize production processes, to improve the conditions of production itself, to build energy facilities to provide processing enterprises with stable and affordable energy supply, to apply modern construction technologies that will create environmentally friendly and energy-efficient production. For the restoration and development of the processing industry of Ukraine, taking into account the impact of the construction industry, we propose to apply the following measures: widespread implementation of the enterprise relocation program with the expansion of state support; the use of state programs for the reconstruction of property and lending, the development of international communications and the European vector for the recovery of the post-war industry based on the ESG concept and the principles of building back better, compliance with the principles of energy efficiency and energy saving, and the application of decarbonization measures. These tools are designed to provide stimulating processes in the processing industry to achieve and exceed the prewar level of the volume of competitive and high-quality products. The development of the construction industry plays an important role in the restoration of processing enterprises in Ukraine, so it is important to create favorable conditions for their cooperation, to develop comprehensive development strategies aimed at ensuring sustainable economic growth and support.

Analyzing Morphology and Composition of Coarse Aerosol Particles in Bangkok, Thailand: Implications to Sources and Impacts of Aged Aerosols on Ecosystem Health and Climate Dynamics

AbstractDuring dry seasons, elevated aerosol levels across Thailand pose nationwide problems. Understanding and addressing this issue is challenging due to the dynamic nature of aerosol modification and generation during transport. This study investigates the morphology and elemental compositions of coarse aerosol particles in Bangkok, Thailand, during the dry seasons of 2020/21. Through scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectrometry (EDS), the study reveals a complex mixture of anthropogenic, mineral, biogenic, and marine aerosols. Anthropogenic sources, including biomass burning, vehicular emissions, and industrial activities, contribute to carbonaceous particles like soot aggregates and tar balls. Mineral dust particles, predominantly calcium-rich and aluminosilicate, originate from various sources including construction, industry, and natural processes. Aging processes alter the composition and properties of both carbonaceous and mineral particles, influencing nutrient deposition, carbon sequestration, cloud condensation nuclei formation, and light scattering. These processes have multifaceted impacts on ecosystem health and climate dynamics, highlighting the need for further research and mitigation strategies to address the environmental consequences of aged aerosol particles in urban environments like Bangkok.

Laminar burning velocity of ethanol-ethyl acetate mixtures in air

Alcohols, esters, and their mixtures are ubiquitous in the process industry. However, safety data remain limited, especially for mixtures. In this work, the laminar burning velocity, Sl, of ethanol-ethyl acetate mixtures in air was investigated (at 90 °C and atmospheric pressure) through computations performed using three different detailed chemical kinetic mechanisms, and measurements obtained from pressure time histories recorded during closed vessel explosion experiments. Computations were run varying the equivalence ratio, φ, from 0.6 to 1.7, and the mole fraction of ethanol in the fuel mixture from 0 (only ethyl acetate) to 1 (only ethanol). For all systems, explosion experiments were carried out at φ = 1.1, i.e., the composition at which, according to calculations, Sl achieves its maximum value. Regardless of the kinetic mechanism, reasonable agreement is found between computed and experimental data, including experimental data retrieved from the literature for ethanol and ethyl acetate. Results show that the behavior of ethanol-ethyl acetate is bounded between the behaviors of ethanol and ethyl acetate, approaching the former/latter as the mixture is enriched in ethanol/ethyl acetate. Over the whole range of equivalence ratios explored, the values of Sl for ethanol-ethyl acetate are smaller than those obtained by averaging the corresponding values of ethanol and ethyl acetate according to their mole proportions in the fuel mixture. This is also confirmed experimentally. A simple Le Chatelier’s mixing rule-like formula is proved to predict values of Sl that closely match both computed and experimental data, suggesting that the nature of the interaction between ethanol and ethyl acetate is predominantly thermal rather than chemical.

Exploration of the advantages of targeted isolation of deep-sea microorganisms and genetically engineered strains.

Oil, mineral processing and environmental restoration can be dangerous processes. Attempts are often made to apply microorganisms to reduce the risks, but the adaptability of terrestrial organisms is often weak. Although genetically engineered strains can improve their environmental adaptability through targeted modification, there are problems such as metabolite accumulation, poor plasmid stability and potential pathogenicity. Screening of extremophiles from the natural environment has become an inevitable choice. The special environment in the deep sea (high pressure, low temperature, low nutrition, high salinity) is a natural place for extremophiles to grow and survive, thus screening of extremophiles from the deep sea is conducive to the green and sustainable development of industry. In this paper, the application status and problems of genetically engineered strains are reviewed based on the microorganisms needed for extreme industry. This paper focuses on the application status and advantages of deep-sea microorganisms. It is found that their advantages are strong adaptability, stable gene, friendly environment, simple and convenient technology (compared with genetic engineering), which has a broad industry processes application prospect. This review broadens the scope of microbial applications.

Integrated physical safety–cyber security risk assessment based on layers of protection analysis

The extensive application of information technology in process industries has increased production efficiency but has also introduced new risks. Therefore, it is necessary to systematically analyse the risks within factories to ensure the stable operation of their production systems. This study proposes an integrated risk assessment method based on layers of protection analysis (LOPA), which combines physical safety and cyber security analyses to provide comprehensive risk assessments for the process industry. The method first identifies the hazardous scenarios and protection layers relevant to a process facility. It then identifies potential cyberattack types and existing countermeasures. Subsequently, the functional impacts of attacks on protection layers and potential coupling relationships are discussed. Using common vulnerability scoring system (CVSS) and semi-quantitative methods, the probability of attack is determined to optimize the probability of failure on demand (PFD) of the protection layers. Finally, a case study of a steam separator in a catalytic cracking unit is used to quantitatively explore the potential attacks and risks of coupled protection layers. The application of Bayesian network (BN) is used for further validation of the method. This study offers a novel quantitative tool for risk assessment in the process industry, which can enhance the security and reliability of industrial production and control systems.

Perceptions of decarbonisation challenges for the process industry in Sweden and Norway

The energy-intensive process industries (EPIs) account for a high share of global carbon emissions but have so far been slow to decarbonise. One of the reasons for the slow pace is that central problems and solutions are contested among stakeholders. To develop effective and inclusive transition policy, a better understanding of different perspectives on decarbonisation challenges is needed. In this paper, we use Q methodology to address this gap with an analysis of EPI decarbonisation in Sweden and Norway. The research draws on 50 interviews where different types of stakeholders sorted and reflected upon statements that describe potential decarbonisation challenges. Through factor analysis, we identify four salient narratives in each country, which emphasise different problems and trade-offs. However, we also find similarities across the narratives, both within and across countries. A key challenge that is emphasized in both countries is to ensure a sufficient supply of electricity at competitive prices. Ultimately, we demonstrate how these findings are important for providing policy recommendations.

Extra-framework cations promoted zeolite-encaged cobalt catalysts towards efficient ethylbenzene dehydrogenation

The transformation of ethylbenzene to styrene through direct dehydrogenation is essential process in chemical industry, indispensable for the synthesis of polymers and plastics. Herein, faujasite zeolite encaged cobalt catalyst with potassium ion as the extraframework cations, namely K-Co@Y, is reported to be a robust catalyst for ethylbenzene direct dehydrogenation, showing ethylbenzene conversion of ∼45 % and styrene selectivity of ∼95 % simultaneously under employed conditions. The superior performance of K-Co@Y in comparison with Na-Co@Y is attributed to the effective modulation of zeolite-encaged Co2+ species by extraframework K+ ions, which increases the electron density of cobalt sites and facilitates CH bond activation. Although coke deposits cause gradual deactivation, the structural integrity of K-Co@Y can be well preserved during the dehydrogenation reaction and the performance can be full restored via a simple calcination regeneration step, making K-Co@Y an eligible catalyst for long-term running in the continuous regeneration mode. This study highlights the vital role of extraframework cations in zeolite-encaged single-site catalysts for target chemical transformations and opens up a new way to modulate the performance of zeolite catalysts.

Exploring ultrasonic and resistance welding for thermoplastic composite structures: Process development and application potential

Thermoplastic composites outperform in aerospace applications compared to thermoset composites due to their weldability, a key advantage. This feature streamlines manufacturing, allowing for precise assembly of complex shapes, reducing costs, and accelerating production. Additionally, it simplifies maintenance, enabling easy repair or replacement of damaged parts, thereby extending vehicle lifespan and minimizing downtime. With exceptional strength-to-weight ratio and resistance to corrosion and fatigue, weldable thermoplastic composites ensure reliable performance in the demanding aerospace environment. Overall, their weldability enhances efficiency, versatility, and safety in aerospace applications. This paper first presents an overview of various welding processes and discusses the special challenges of assembly processes in the aviation industry. This work then focuses from the authors’ perspective with regard to industrializability on the two most promising processes, resistance and ultrasonic welding.

Design and optimization of stirrer and mixer design for the correct mixing of pharmaceutical powders through DEM

Mixing of granular materials is an important process for pharmaceutical industries. In this study, a quantifiable calculation method was suggested to determine the final mixing degree of the mixture. Based on that, the effect of the stirrer design, rotational speed, powder density, cohesivity, material ratios, and particle movement in the chamber guided through different designs of deflectors on the final mixing quality is examined. The results show that increasing the stirring speed, generates better mixing quality. However, introducing a varying rotational speed mode improves the mixing degree specially for binary mixtures with high relative densities. The improvement of the mixing with the number of contacting blades is observed. Finally, the introduction of a simple deflector drastically enhances the mixing quality and enables the feeding into the chamber, which is key for continuous operation with cohesive powders, making the process more stable and efficient by using more of the mixing volume.

Eulerian multi-fluid simulations of local liquid distribution in a bed packed with cylindrical particles

Packed bed reactors (PBRs) are extensively used in chemical process industries to perform solid-catalyzed gas–liquid reactions. Their performance is significantly influenced by liquid distribution which is a strong function of particle shape and size. In the present work, we simulated the steady-state local liquid distribution, pressure drop (ΔP/L), and overall liquid holdup (〈εL〉) for the beds packed with spherical and cylindrical particles using a three-dimensional (3D) Eulerian multifluid model and validated the predictions using corresponding high-speed imaging measurements performed in pseudo-2D packed beds. We showed that the Eulerian model with existing closures significantly underpredicts the liquid distribution for the bed randomly packed with cylindrical particles. To address this, we proposed a modification in existing mechanical dispersion force (F→D) model as a function of average particle orientation angle (θ). The modification significantly improved agreement between the predictions and the corresponding measurements. Using the modified model, we showed that the increased magnitude of F→D in the lateral direction leads to higher lateral liquid spreading for cylindrical particles as compared to that for the spherical particles. Importantly, the modified model also predicted the local liquid distribution and ΔP/L for beds packed manually with cylindrical particles oriented at different θ in a satisfactory agreement with the corresponding measurements. On increasing θ, the F→D in lateral direction (i.e., perpendicular to flow) as well as liquid–solid interaction force (F→LS) in axial direction (i.e., parallel to flow) found to increase significantly. As a result, the lateral liquid spreading as well as ΔP/L decrease substantially on increasing θ.

Multiple effects of high efficiency solid inertants on fire hazard of the accumulated Mg dust layer

Due to low melting and boiling points and extreme reactivity in the chemical reaction of Mg powder, inert powders that have a significant inerting effect on Mg dust clouds can cause significant combustion enhancement of the accumulated Mg dust layer. To circumvent this unforeseen fire hazard, this research selects five types of inertants that have been demonstrated to exert an inerting effect on metal dust clouds and possess a potential flame-retardant effect on Mg dust layers. This research aims to investigate the effect of inert powders on Mg dust layers to identify an efficient inerting mechanism for Mg dust layers. The results indicate that the selection of inertants for Mg dust must be based on a comprehensive evaluation of their physical and chemical properties. The presence of substances with strong decomposition and decomposition products that readily produce gases will destroy the oxide crust on the surface of the accumulated Mg dust layer, thereby causing violent gas-phase combustion. In the case of highly chemically stable substances, the melting point is of primary importance. The formation of cracks in the oxide crust is also a consequence of the higher melting point of inertants, resulting in a combustion enhancement of the mixed dust layer. Inertants with a low melting point and a high boiling point demonstrate a high degree of inerting efficiency for Mg dust layers. The melting of the inert substances forms a liquid film, which prevents the Mg powder from coming into contact with the air surrounding and within the combustion zone. The results of this research are both instructive and valuable for preventing explosions in the process industry involving metal dust materials.

Three-phase CFD-DEM study on the hydrodynamics of a riser system with liquid injection

Riser reactors are frequently applied in the process industry for highly important catalytic processes. In this work, a computational fluid dynamics- discrete element method (CFD-DEM) for a riser with liquid injection was developed. This model treats the gas as a continuous phase whereas the liquid droplets and catalyst particles are treated as discrete elements. The presence of droplets causes particles to be wet, which is taken into account via coverage models of the particles. In addition, the liquid on the particles will change the collision behavior, which is included using an energy balance approach. This CFD-DEM study is conducted simulating a lab-scale pseudo-2D riser. Based on the comparison, the assumption of fully covered particles results in a significant increase in the solids holdup and clustering behavior of the riser which, especially at the low liquid flow rate, results in an over-prediction. The partial coverage simulations show that only half of the particles are covered, which has a major effect on the collisions.