Model-driven Workflow Research Articles

Error analysis model-driven workflow for self-calibration stitching testing of X-ray flat surfaces

Self-calibration stitching test is widely utilized for testing X-ray flat surfaces. Various factors, including environment disturbances, motion errors, misalignments, overlapping ratios, and sub-aperture sizes can affect the accuracy. Previous studies have shown that motion errors can introduce slope errors in the test surface, and higher overlapping ratios can increase the test error. However, these error analyses have not been comprehensive or quantitatively sufficient for practical applications. For X-ray flat surfaces with specific accuracy requirements, the necessary control levels for error sources and the optimal test parameters remain unclear. To this end, an error analysis model-driven workflow for self-calibration stitching testing of X-ray flat surfaces is proposed. This model allows for the systematic evaluation of how different error sources and test parameters affect test accuracy. Further, it can guide the determination of the control levels of error sources and test parameters, moving beyond the reliance on empirical experience as seen in previous studies. A flat X-ray mirror with clear aperture of 250 mm × 30 mm and 0.2 nm (50 nrad) RMS accuracy requirement was utilized to demonstrate the procedures of the workflow. Verification experiments demonstrated that this workflow can serve as a standard model for evaluating test accuracy and guiding test procedures to achieve the desired accuracy in self-calibration stitching of X-ray flat mirrors.

Mechanistic modeling of twin screw wet granulation for pharmaceutical formulations: Calibration, sensitivity analysis, and model-driven workflow

Wet granulation, a particle size enlargement process, can significantly enhance the critical quality attributes of powders and improve the ability to form tablets in pharmaceutical manufacturing. In this study, a mechanistic-based population balance model is applied to twin screw wet granulation. This model incorporated a recently developed breakage kernel specifically designed for twin screw granulation, along with nucleation, layering, and consolidation. Calibration and validation were performed on Hydrochlorothiazide and Acetaminophen formulations, which exhibit different particle size and wettability characteristics. Utilizing a compartmental experimental dataset, a comprehensive global sensitivity analysis identified critical inputs impacting quality attributes. The study revealed that the nucleation rate process model, effectively represented particle size distributions for both formulations. Adjustments to nucleation and breakage rate parameters, influenced by material properties and screw configuration, improved the model’s accuracy. A model-driven workflow was proposed, offering step-by-step guidelines and facilitating PBM model usage, providing essential details for future active pharmaceutical ingredient (API) formulations.

Integration of a model-driven workflow into an industrial pharmaceutical facility: supporting process development of API crystallisation

Integration of a model-driven workflow into an industrial pharmaceutical facility: supporting process development of API crystallisation

Developing a model-driven workflow for the digital design of small-scale batch cooling crystallisation with the antiviral lamivudine

A model-driven workflow that uses digital tools and small-scale experiments to maximise the efficiency in achieving a desired set of crystallisation responses, kinetics and objectives.

Regional-scale 3D modelling in metamorphic belts: An implicit model-driven workflow applied in the Pennine Alps

Leveraging a high resolution geological and structural dataset acquired over decades of fieldwork, we build the 3D structural model of a portion of the highly deformed core of the Alpine orogen, in the Northern Aosta Valley. The model represents tectonic contacts separating the tectono-metamorphic units outcropping along the section between Mont Blanc and Monte Rosa, and it covers an area of ca. 1500 km2. The input source data include original 1:10,000 geological surveys synthetised in a 1:75,000 tectonic map, and a dense database of structural stations. After a first orientation statistics study of the structural field database, our workflow develops through structural interpretation in vertical cross-sections that allow including in the modelling process structural drivers such as crosscutting relationships, interference patterns, kinematic constraints and fold morphology from detailed field studies. Three-dimensional interpolation on a tetrahedral mesh using the implicit Discrete Smooth Interpolator method follows, using also foliation and fold axes data as interpolation constraints. After describing the workflow and the model, we discuss the difficulties of modelling in polydeformed metamorphic complexes. In particular, we address the issue of modelling shear zones, refolded, isoclinal and/or recumbent folds and dense networks of faults, that characterise the geology of the Northern Aosta Valley.

Scientific workflow execution in the cloud using a dynamic runtime model

To explain specific phenomena, scientists perform a sequence of tasks, e.g., to gather, analyze and interpret data, forming a scientific workflow. Depending on the complexity of the workflow, scientists require access to various kinds of tools, applications and infrastructures for individual tasks. Current approaches are often limited to managing these resources at design time, requiring the scientist to preemptively set up applications essential for their workflow. Therefore, a dynamic provisioning and configuration of computing resources are required that fulfills these needs at runtime. In this paper, we present a dynamic runtime model that couples workflow tasks with their individual applications and infrastructure requirements. This runtime model is used as a knowledge base by a model-driven workflow execution engine orchestrating the sequence of tasks and their infrastructure. We exhibit that the simplicity of the runtime model supports the creation of highly tailored infrastructures, the integration of self-developed applications, as well as a human-in-the-loop allowing scientists to monitor and interact with the workflow at runtime. To tackle the heterogeneity of cloud provider interfaces, we implement the workflow runtime model by extending the Open Cloud Computing Interface cloud standard, which provides an extensible data model as well as a uniform interface to manage cloud resources. We demonstrate the applicability of our approach using three case studies and discuss the benefits of the runtime model from a user and system perspective.

Model-driven experimental design workflow expands understanding of regulatory role of Nac in Escherichiacoli.

The establishment of experimental conditions for transcriptional regulator network (TRN) reconstruction in bacteria continues to be impeded by the limited knowledge of activating conditions for transcription factors (TFs). Here, we present a novel genome-scale model-driven workflow for designing experimental conditions, which optimally activate specific TFs. Our model-driven workflow was applied to elucidate transcriptional regulation under nitrogen limitation by Nac and NtrC, in Escherichia coli. We comprehensively predict alternative nitrogen sources, including cytosine and cytidine, which trigger differential activation of Nac using a model-driven workflow. In accordance with the prediction, genome-wide measurements with ChIP-exo and RNA-seq were performed. Integrative data analysis reveals that the Nac and NtrC regulons consist of 97 and 43 genes under alternative nitrogen conditions, respectively. Functional analysis of Nac at the transcriptional level showed that Nac directly down-regulates amino acid biosynthesis and restores expression of tricarboxylic acid (TCA) cycle genes to alleviate nitrogen-limiting stress. We also demonstrate that both TFs coherently modulate α-ketoglutarate accumulation stress due to nitrogen limitation by co-activating amino acid and diamine degradation pathways. A systems-biology approach provided a detailed and quantitative understanding of both TF's roles and how nitrogen and carbon metabolic networks respond complementarily to nitrogen-limiting stress.

Applying Model-Driven Engineering to Stimulate the Adoption of DevOps Processes in Small and Medium-Sized Development Organizations

Microservice architecture (MSA) denotes an increasingly popular architectural style in which business capabilities are wrapped into autonomously developable and deployable software components called microservices. Microservice applications are developed by multiple DevOps teams each owning one or more services. In this article, we explore the state of how DevOps teams in small and medium-sized organizations (SMOs) cope with MSA and how they can be supported. We show through a secondary analysis of an exploratory interview study comprising six cases, that the organizational and technological complexity resulting from MSA poses particular challenges for small and medium-sized organizations (SMOs). We apply model-driven engineering to address these challenges. As results of the second analysis, we identify the challenge areas of building and maintaining a common architectural understanding, and dealing with deployment technologies. To support DevOps teams of SMOs in coping with these challenges, we present a model-driven workflow based on LEMMA—the Language Ecosystem for Modeling Microservice Architecture. To implement the workflow, we extend LEMMA with the functionality to (i) generate models from API documentation; (ii) reference remote models owned by other teams; (iii) generate deployment specifications; and (iv) generate a visual representation of the overall architecture. We validate the model-driven workflow and our extensions to LEMMA through a case study showing that the added functionality to LEMMA can bring efficiency gains for DevOps teams. To develop best practices for applying our workflow to maximize efficiency in SMOs, we plan to conduct more empirical research in the field in the future.

UsING perspectives of RESOURCES and control-flow for VERIFICATION OF WORKFLOWS

This article is devoted to the subject of automatic verification of workflows. Based on the research of existing solutions, it was found that they don't allow you to integrate different workflows perspectives, and often focused on the control-flow perspective. Based on this, we developed a method integrating different perspectives of workflows, which lets you find synchronization errors, deadlocks, and so forth. By analyzing control-flow perspectives and resources, it generated a code on PROMELA. The resulting code can be verified by using the SPIN model checker, and if an error occurs, it constructs a counterexample. For the experiments, we developed an open-source software tool. The provisions of this article may be used for further development of this approach, known as a “model-driven workflow development”. This article is of interest to specialists in the development of large software systems, as well as areas where it is necessary to create, verify and execute workflows.

Mockup-Driven Development: Providing agile support for Model-Driven Web Engineering

ContextAgile software development approaches are currently becoming the industry standard for Web Application development. On the other hand, Model-Driven Web Engineering (MDWE) methodologies are known to improve productivity when building this kind of applications. However, current MDWE methodologies tend to ignore important aspects of Web Applications development supported by agile processes, such as constant customer feedback or early design of user interfaces. ObjectiveIn this paper we analyze the difficulties of supporting agile features in MDWE methodologies. Then, we propose an approach that eases the incorporation of well-known agile practices to MDWE. MethodWe propose using User Interface prototypes (usually known as mockups) as a way to start the modeling process in the context of a mixed agile-MDWE process. To assist this process, we defined a lightweight metamodel that allows modeling features over mockups, interacting with end-users and generating MDWE models. Then, we conducted a statistical evaluation of both approaches (traditional vs. mockup-based modeling). ResultsFirst we comment on how agile features can be added to MDWE processes using mockups. Then, we show by means of a quantitative study that the proposed approach is faster, less error-prone and still as complete as traditional MDWE processes. ConclusionThe use of mockups to guide the MDWE process helps in the reduction of the development cycle as well as in the incorporation of agile practices in the model-driven workflow. Complete MDWE models can be built and generated by using lightweight modeling over User Interface mockups, and this process suggests being more efficient, in terms of errors and effort, than traditional modeling in MDWE.

The Detectability of Free-phase Migrating CO2: A Rock Physics and Seismic Modelling Feasibility Study

Subsurface monitoring is essential for the successful implementation and public acceptance of CO 2 storage. Injected CO 2 will need to be monitored to verify the successful containment within its intended formation, and to ensure no loss of containment within the storage complex. The ability for seismic techniques to monitor structurally trapped CO 2 has been successfully demonstrated due to the changes in the acoustic properties of the reservoir produced by the displacement of brine by less dense and more compressible CO 2 . However, the ability for seismic methods to detect free-phase migrating CO 2 is still moderately understood. In order to assess the feasibility for seismic monitoring of a migrating front, we estimate the time-lapse signal over a theoretical, clean, homogeneous sandstone reservoir through the application of a three-stage model-driven workflow consisting of fluid-flow, rock physics and seismic forward modelling. To capture the range of responses which could be encountered, two end-member fluid distribution models were used: uniform saturation and the modified patchy saturation model. Analysis of the time- lapse survey highlights the importance of determining and understanding the fluid distribution model impacting the range of velocities prior to generating and interpreting the seismic response. This change in velocity is shown to be directly related to the volume of CO 2 occupying the pore-space of a migrating plume front. This highlights the fact that the detectability of a migrating front is a site specific issue which not only depends on the geophysical parameters of the seismic survey but also on the geological variations and spatial distribution in the reservoir.

A model-driven workflow fragmentation framework for collaborative workflow architectures and systems

This paper focuses on a workflow distribution methodology for rationally deploying workflow models onto a distributed workflow system running on cloud computing environments, and we particularly lay a stress upon that those workflow systems operable on cloud computing environments are dubbed collaborative workflow systems, which are not only built upon the collaborative workflow architectures proposed in the paper, but pursuing the so-called collaborative computing paradigm characterized by focusing collaboration over cloud computing environments. The essential idea of the workflow distribution methodology is about how to fragment a workflow model and how to allocate its fragments to each of the architectural components configuring the underlying collaborative workflow architecture and system. As a reasonable solution to realize the essential idea, the paper proposes a model-driven workflow fragmentation framework, which provides a series of fragmentation algorithms that semantically fragmentate a workflow model by considering the semantic factors – performer, role, control-flow, data-flow, etc. – of the ICN-based workflow model as fragmentation criteria. The algorithms are classified into the vertical fragmentation approach, the horizontal fragmentation approach, and the hybrid approach of both. Conclusively, this paper conceives a possible set of collaborative workflow architectures embedding the collaborative computing paradigm, and describes the detailed formalism of the framework and about how the framework works on those collaborative workflow architectures and systems.