What's new in pSeven products?
Note: Detailed lists of updates can be found in the corresponding changelogs in the documentation.
pSeven Desktop
pSeven EnterpriseWhen executing a workflow in pSeven Enterprise, each block should ideally run immediately once its input data becomes available - meaning all prerequisite blocks linked to it have completed and produced their outputs. However, block startup often involves initialization delays due to resource allocation for containers, network latencies and other overhead.
pSeven Enterprise offers multiple block execution strategies, each designed to optimize workflow runtime and cluster resource consumption differently. Let's explore how these strategies work using a simple workflow with three sequential blocks.
1. All-at-once: All blocks start simultaneously with the workflow run. Most blocks become ready to process input data by the time it's available, which minimizes inter-block delays. Total workflow runtime then approaches the sum of individual block execution times. Conversely, this leads to excessive cluster load as all blocks reserve required resources upfront.
2. On-demand: Blocks start only when their input data becomes available. Due to initialization delays, blocks cannot immediately start processing input data during the workflow run, which can significantly increase inter-block delays and total workflow runtime. However, this approach minimizes the load by allocating resources only when needed and is recommended for overloaded clusters.
3. On-demand with predictive initialization: The new optimized scheduling strategy (now enabled by default) builds on the on-demand strategy. Using workflow run statistics, it predicts and compensates for block initialization delays. Given accurate timing estimates from previous runs, this strategy ensures each block is ready to execute precisely when its input data (outputs from all prerequisite blocks) becomes available. The updated run strategy maintains low computational overhead comparable to the original on-demand strategy, while achieving runtimes that nearly match the all-at-once strategy. Performance improvements are most significant in workflows with long chains of sequential blocks, while a little less noticeable in highly parallel workflows.
The Model builder block enables predictive modeling in pSeven Enterprise. Data collected from simulations and physical tests can be transformed into an executable model that quickly computes results for any new inputs, accelerating complex simulations by orders of magnitude. For example, such models can be used to run full-factorial experiments and select candidate optimal design parameters, which are then verified using more precise methods.
The process of creating a model is called training, while using a model to compute results for new inputs is called prediction. The overall approach is known as predictive modeling, also referred to as metamodeling, surrogate modeling, response surface modeling (RSM), reduced-order modeling (ROM), machine learning (ML), etc.
Creating a model with sufficiently accurate predictions (good predictive power) requires selecting the most suitable modeling technique for the specific problem and dataset, plus extensive parameter tuning - often through trial and error. In pSeven products, a special technique called SmartSelection automates this entire process without requiring additional configuration or expertise from the user. It automatically searches for an optimal technique and parameter settings to balance computational efficiency and model accuracy based on the training data characteristics.
The Model builder block primarily serves as a SmartSelection launcher within pSeven Enterprise:
- Provide a CSV file path or Table value to the Training sample input.
- Optionally pass an existing model to the Initial model input as a baseline.
- Control the process by specifying high-level settings for training and validation, known sample properties and additional model requirements - needing only general methodological knowledge, no deep expertise in mathematics, modeling algorithms or specialized domains.
- Save trained models in native format or export them to source formats, including C source code and MATLAB-compatible - models are not locked into pSeven Enterprise.
Model builder offers quick setup through direct access to all settings in the Block properties pane, requiring no separate UI configuration. The block also features seamless integration with the Design space exploration block, allowing generated DoE to pass directly from the Result designs output to the Training sample input. This integration enables automatic detection of inputs/outputs, names, and properties without requiring additional setup.
For more experienced users, Model builder provides access to the most granular training settings through pSeven Core options. This enables full control over technique selection and parameter configuration. Experts can use Model builder for conventional training workflows while maintaining complete control over the process.
Go to page navigate_nextInput data file handling
Engineering simulations often require big files as inputs and in many cases they are needed only as a reference – therefore, there is no need to create a copy of these files in each run.
In recent pSeven Enterprise version we introduced an explicit control over input file handling – users now can decide, which files should be automatically transferred to every Run folder and which they would like to keep at the level of the workflow and access from Runs directly (typically as read-only source of data).
Such control option is also useful when users want to deal with huge files directly on Windows extension node and the transfer is handled by the corresponding integration block – therefore, there is no need for an additional intermediate copy to the Run folder.
Results files access control
Another option to control files access is related to the collaborative nature of the platform. Imagine you published a web app for a wide audience – however, you don’t want the end users to be able to access the internal files of underlying workflow – only the allowed list of result files.
pSeven Enterprise now provides flexible control over such file's exposure, based on an explicit control list - “App result rules”. With this option, authors of the web apps can directly specify which files or folders they want to include or exclude to or from public results.
Integrating pSeven Enterprise into an external system — such as SPDM — often requires custom metadata for the input and output ports of automated workflows, which act as run-ready processes.
For the connection to be convenient for the user and ensure proper data exchange, it may require clear marking of mandatory and auxiliary inputs, expected units and types, and even the purpose of inputs or outputs, such as "File with load conditions".
In a recent release, we introduced the ability to add custom, user-defined labels to the input and output ports of workflows. Furthermore, the deployment administrator can create presets for these labels, allowing users to select the relevant one and only enter the necessary values.
These labels are visible in the platform's UI and are available via the REST API for parsing and use in external systems.
Before pSeven v2025.02 we recommended our users to integrate Simcenter Amesim using exposed parameters in the simulation model and batch-mode execution. Despite being a valid and generic approach, it still may not be convenient enough for daily usage.
Addressing the growing number of requests, we introduce a new Amesim block, which streamlines the integration to literally several clicks.
Just specify your Amesim project in the block and it will extract the whole tree of input and output parameters automatically – simply choose what you want to use in your workflow and your model is ready for automated execution, for example, in optimization studies.
Simcenter Amesim – is a mechatronic systems simulation platform by Siemens that allows design engineers to virtually assess and optimize the systems’ performance.
Go to page navigate_nextAs a cloud-native collaborative platform, from day one pSeven Enterprise allows users to share their workflows with each other – to use “as is” in Run-only mode, modify them together in real time or build bigger stories, using shared workflows as references.
But what if a big team is working on one or several complex projects and person-to-person sharing is not enough? In recent releases we introduced Workspaces – a shared space on the platform, where members can truly collaborate.
With granular setup of permissions, you can now organize group work and enable many scenarios, like:
- Separating access and organizing collection of Apps and workflows for different groups of users – everyone will see and use only what they need.
- Using Workspace as a centralized storage for a project – and even with people joining and leaving all workflows and results will stay available and traceable. And when the project is over, simply archive or even remove the data to save the space.
- Providing your users with examples or run-ready workflows for them to build their own stories in personal workspace - with read-only permission you can be sure nobody will alternate your collection.
- Inspecting and debugging the workflows developed by your users together with them – even in live mode.
It is also important to mention that workspaces not only allow you to group users – they provide control over resources associated with the group. For example, you can set storage quota for each workspace, ensuring that it won’t occupy more than expected amount of the storage space on the server.
Go to page navigate_nextIn our daily engineering routines, we often use external resources, like:
- remote machines for specific simulation tools;
- HPC servers to offload heavy tasks;
- PLM and SPDM systems to get inputs or store results;
- other databases and web-services to retrieve data;
- etc.
And all of those resources may be used in automated workflows. Despite being different in purpose, they all have something in common – the user needs to provide credentials to access them: passwords, authentication keys etc.
pSeven Enterprise provides not only secure mechanics to store credentials but also allows to use them in the connector blocks in the workflows. Dedicated “Secret” datatype allows users to simply type their personal credentials as a string or select a previously used values that are stored in personal protected vaults.
However, the collaborative nature of pSeven Enterprise implies even more control over such settings. Imagine that you share a workflow with such credentials with your colleagues – you not only don’t want them to see your password (even if it's encrypted) and username, but you also want to force them to specify their own.
With the Personal Parameter (PP) setting you can mark any port of any block as your private setting and anyone who works with the same workflow in the shared mode will be forced to specify their own values for their own runs. Everyone will see and use only their own values, while using the same shared workflow!
Go to page navigate_nextAppsHub in pSeven Enterprise enables ultimate democratization of engineering routines. It is a corporate collection of workflow-powered web apps, which can be executed via user interface in your browser or via API to be used as simulation web services.
Release 2025.02 concludes the series of updates in Appshub, intended to address various topics:
- Custom web app development simplification:
- pSeven Enterprise automatically generates default user interface for your web apps. It provides all basic controls and required options, like file upload. But we often want to have something fancier or case-specific – and in pSeven Enterprise you can develop your own UI for any Web app. With recent update such customization is even more convenient than before – now the platform takes care of all basic features, like log display or run buttons, allowing you to focus only on your custom elements and implement them easily with new web app API.
- File navigation and access:
- We are often interested not only in values of some parameters as simulation results, but also in files. Updates in AppsHub introduce convenient navigation over folders and files of the web app, allowing users to browse and download what they need. Moreover, users now can easily explore different runs of the web app and access their results with a dedicated navigation tab.
- Security updates and controls:
- AppsHub is a powerful tool to share engineering methods, captured as automated processes, with a wide audience. But it also means that you may not only provide access but protect the embedded know-how or ensure different users won’t interfere.
- With recent updates, web apps provide full security even if exposed to external users. Special settings allow author to specify if he allows the workflow behind the web app to be accessible or provide a whitelist of resulting files, which can be downloaded.
The new block enables direct integration of FORGE into pSeven workflows. You only should specify FORGE project, and the block will automatically extract available input parameters and results and present them in the UI.
Choose which of them to be used and your FORGE simulation is ready to be linked with for example Design Space Exploration block for parametric studies and optimization or other simulation and post-processing tools.
FORGE – is a software solution for the simulation of hot and cold forming processes. It has been the flagship product of Transvalor for almost 35 years and is used by customers throughout the world. FORGE fulfills the needs of companies producing forged parts for a variety of industrial sectors.
Before pSeven v2025.02 we recommended our users to integrate Simcenter Amesim using exposed parameters in the simulation model and batch-mode execution. Despite being a valid and generic approach, it still may not be convenient enough for daily usage.
Addressing the growing number of requests, we introduce a new Amesim block, which streamlines the integration to literally several clicks.
Just specify your Amesim project in the block and it will extract the whole tree of input and output parameters automatically – simply choose what you want to use in your workflow and your model is ready for automated execution, for example, in optimization studies.
Simcenter Amesim – is a mechatronic systems simulation platform by Siemens that allows design engineers to virtually assess and optimize the systems’ performance.
Go to page navigate_next
The new block enables direct integration of FORGE into pSeven workflows. You only should specify FORGE project, and the block will automatically extract available input parameters and results and present them in the UI.
Choose which of them to be used and your FORGE simulation is ready to be linked with for example Design Space Exploration block for parametric studies and optimization or other simulation and post-processing tools.
FORGE – is a software solution for the simulation of hot and cold forming processes. It has been the flagship product of Transvalor for almost 35 years and is used by customers throughout the world. FORGE fulfills the needs of companies producing forged parts for a variety of industrial sectors.
Direct integration blocks were updated to support most recent versions:
- STAR-CCM+ block was updated to support newer versions, explicitly tested with version 2302 and should work with all versions above.
- FloEFD block was updated for compatibility with up-to-date versions of Siemens FloEFD.
When executing a workflow in pSeven Enterprise, each block should ideally run immediately once its input data becomes available - meaning all prerequisite blocks linked to it have completed and produced their outputs. However, block startup often involves initialization delays due to resource allocation for containers, network latencies and other overhead.
pSeven Enterprise offers multiple block execution strategies, each designed to optimize workflow runtime and cluster resource consumption differently. Let's explore how these strategies work using a simple workflow with three sequential blocks.
1. All-at-once: All blocks start simultaneously with the workflow run. Most blocks become ready to process input data by the time it's available, which minimizes inter-block delays. Total workflow runtime then approaches the sum of individual block execution times. Conversely, this leads to excessive cluster load as all blocks reserve required resources upfront.
2. On-demand: Blocks start only when their input data becomes available. Due to initialization delays, blocks cannot immediately start processing input data during the workflow run, which can significantly increase inter-block delays and total workflow runtime. However, this approach minimizes the load by allocating resources only when needed and is recommended for overloaded clusters.
3. On-demand with predictive initialization: The new optimized scheduling strategy (now enabled by default) builds on the on-demand strategy. Using workflow run statistics, it predicts and compensates for block initialization delays. Given accurate timing estimates from previous runs, this strategy ensures each block is ready to execute precisely when its input data (outputs from all prerequisite blocks) becomes available. The updated run strategy maintains low computational overhead comparable to the original on-demand strategy, while achieving runtimes that nearly match the all-at-once strategy. Performance improvements are most significant in workflows with long chains of sequential blocks, while a little less noticeable in highly parallel workflows.
The Model builder block enables predictive modeling in pSeven Enterprise. Data collected from simulations and physical tests can be transformed into an executable model that quickly computes results for any new inputs, accelerating complex simulations by orders of magnitude. For example, such models can be used to run full-factorial experiments and select candidate optimal design parameters, which are then verified using more precise methods.
The process of creating a model is called training, while using a model to compute results for new inputs is called prediction. The overall approach is known as predictive modeling, also referred to as metamodeling, surrogate modeling, response surface modeling (RSM), reduced-order modeling (ROM), machine learning (ML), etc.
Creating a model with sufficiently accurate predictions (good predictive power) requires selecting the most suitable modeling technique for the specific problem and dataset, plus extensive parameter tuning - often through trial and error. In pSeven products, a special technique called SmartSelection automates this entire process without requiring additional configuration or expertise from the user. It automatically searches for an optimal technique and parameter settings to balance computational efficiency and model accuracy based on the training data characteristics.
The Model builder block primarily serves as a SmartSelection launcher within pSeven Enterprise:
- Provide a CSV file path or Table value to the Training sample input.
- Optionally pass an existing model to the Initial model input as a baseline.
- Control the process by specifying high-level settings for training and validation, known sample properties and additional model requirements - needing only general methodological knowledge, no deep expertise in mathematics, modeling algorithms or specialized domains.
- Save trained models in native format or export them to source formats, including C source code and MATLAB-compatible - models are not locked into pSeven Enterprise.
Model builder offers quick setup through direct access to all settings in the Block properties pane, requiring no separate UI configuration. The block also features seamless integration with the Design space exploration block, allowing generated DoE to pass directly from the Result designs output to the Training sample input. This integration enables automatic detection of inputs/outputs, names, and properties without requiring additional setup.
For more experienced users, Model builder provides access to the most granular training settings through pSeven Core options. This enables full control over technique selection and parameter configuration. Experts can use Model builder for conventional training workflows while maintaining complete control over the process.
Go to page navigate_nextInput data file handling
Engineering simulations often require big files as inputs and in many cases they are needed only as a reference – therefore, there is no need to create a copy of these files in each run.
In recent pSeven Enterprise version we introduced an explicit control over input file handling – users now can decide, which files should be automatically transferred to every Run folder and which they would like to keep at the level of the workflow and access from Runs directly (typically as read-only source of data).
Such control option is also useful when users want to deal with huge files directly on Windows extension node and the transfer is handled by the corresponding integration block – therefore, there is no need for an additional intermediate copy to the Run folder.
Results files access control
Another option to control files access is related to the collaborative nature of the platform. Imagine you published a web app for a wide audience – however, you don’t want the end users to be able to access the internal files of underlying workflow – only the allowed list of result files.
pSeven Enterprise now provides flexible control over such file's exposure, based on an explicit control list - “App result rules”. With this option, authors of the web apps can directly specify which files or folders they want to include or exclude to or from public results.
Integrating pSeven Enterprise into an external system — such as SPDM — often requires custom metadata for the input and output ports of automated workflows, which act as run-ready processes.
For the connection to be convenient for the user and ensure proper data exchange, it may require clear marking of mandatory and auxiliary inputs, expected units and types, and even the purpose of inputs or outputs, such as "File with load conditions".
In a recent release, we introduced the ability to add custom, user-defined labels to the input and output ports of workflows. Furthermore, the deployment administrator can create presets for these labels, allowing users to select the relevant one and only enter the necessary values.
These labels are visible in the platform's UI and are available via the REST API for parsing and use in external systems.
As a cloud-native collaborative platform, from day one pSeven Enterprise allows users to share their workflows with each other – to use “as is” in Run-only mode, modify them together in real time or build bigger stories, using shared workflows as references.
But what if a big team is working on one or several complex projects and person-to-person sharing is not enough? In recent releases we introduced Workspaces – a shared space on the platform, where members can truly collaborate.
With granular setup of permissions, you can now organize group work and enable many scenarios, like:
- Separating access and organizing collection of Apps and workflows for different groups of users – everyone will see and use only what they need.
- Using Workspace as a centralized storage for a project – and even with people joining and leaving all workflows and results will stay available and traceable. And when the project is over, simply archive or even remove the data to save the space.
- Providing your users with examples or run-ready workflows for them to build their own stories in personal workspace - with read-only permission you can be sure nobody will alternate your collection.
- Inspecting and debugging the workflows developed by your users together with them – even in live mode.
It is also important to mention that workspaces not only allow you to group users – they provide control over resources associated with the group. For example, you can set storage quota for each workspace, ensuring that it won’t occupy more than expected amount of the storage space on the server.
Go to page navigate_nextIn our daily engineering routines, we often use external resources, like:
- remote machines for specific simulation tools;
- HPC servers to offload heavy tasks;
- PLM and SPDM systems to get inputs or store results;
- other databases and web-services to retrieve data;
- etc.
And all of those resources may be used in automated workflows. Despite being different in purpose, they all have something in common – the user needs to provide credentials to access them: passwords, authentication keys etc.
pSeven Enterprise provides not only secure mechanics to store credentials but also allows to use them in the connector blocks in the workflows. Dedicated “Secret” datatype allows users to simply type their personal credentials as a string or select a previously used values that are stored in personal protected vaults.
However, the collaborative nature of pSeven Enterprise implies even more control over such settings. Imagine that you share a workflow with such credentials with your colleagues – you not only don’t want them to see your password (even if it's encrypted) and username, but you also want to force them to specify their own.
With the Personal Parameter (PP) setting you can mark any port of any block as your private setting and anyone who works with the same workflow in the shared mode will be forced to specify their own values for their own runs. Everyone will see and use only their own values, while using the same shared workflow!
Go to page navigate_nextAppsHub in pSeven Enterprise enables ultimate democratization of engineering routines. It is a corporate collection of workflow-powered web apps, which can be executed via user interface in your browser or via API to be used as simulation web services.
Release 2025.02 concludes the series of updates in Appshub, intended to address various topics:
- Custom web app development simplification:
- pSeven Enterprise automatically generates default user interface for your web apps. It provides all basic controls and required options, like file upload. But we often want to have something fancier or case-specific – and in pSeven Enterprise you can develop your own UI for any Web app. With recent update such customization is even more convenient than before – now the platform takes care of all basic features, like log display or run buttons, allowing you to focus only on your custom elements and implement them easily with new web app API.
- File navigation and access:
- We are often interested not only in values of some parameters as simulation results, but also in files. Updates in AppsHub introduce convenient navigation over folders and files of the web app, allowing users to browse and download what they need. Moreover, users now can easily explore different runs of the web app and access their results with a dedicated navigation tab.
- Security updates and controls:
- AppsHub is a powerful tool to share engineering methods, captured as automated processes, with a wide audience. But it also means that you may not only provide access but protect the embedded know-how or ensure different users won’t interfere.
- With recent updates, web apps provide full security even if exposed to external users. Special settings allow author to specify if he allows the workflow behind the web app to be accessible or provide a whitelist of resulting files, which can be downloaded.