Maplesoft

Maple Flow provides a flexible mathematics tool for engineering projects

March 19, 2021 By Leslie Langnau Leave a Comment

Maplesoft announced Maple Flow, a mathematics tool that allows engineers to more easily brainstorm, develop, and document their mathematics and analyses. Maple Flow provides a virtual, whiteboard-style environment that automatically keeps calculations live as users refine, reposition, and develop their calculations. Maplesoft also announced a new release of the math software Maple.

Maple Flow provides an interface and workflow specifically tailored to design engineers doing calculations and quick scratchpad math, while Maple is a more general-purpose tool that supports the advanced mathematical analysis and algorithm development work done by research engineers.

By providing a flexible, whiteboard-style environment, Maple Flow allows design engineers to easily sketch out and formalize technical ideas, revising and reordering content with simple drag-and-drop behavior. Users can add math, text, and images to a live, interactive document, and Maple Flow keeps all of the mathematics automatically updated. The Maple Flow environment handles the design calculations of virtually all engineering projects, such as circuit analysis, beam loading, highway pavement design, and combustion.

The new version of Maple offers a range of enhancements across the entire product, from small productivity changes to new areas of mathematics. Improvements include a stronger math engine that can tackle even more problems, a streamlined workflow, and expanded tools for signal processing, working with thermophysical data, and physics.

Maplesoft
www.maplesoft.com/products/MapleFlow

MapleMBSE release from Maplesoft expands support to include Capella

August 5, 2020 By Leslie Langnau Leave a Comment

Maplesoft announced a new release of MapleMBSE, the software that enables companies to implement Model-Based Systems Engineering (MBSE) processes without requiring every stakeholder on the project to be an expert in complex MBSE tools. The release of MapleMBSE 2020.2 now supports the MBSE platform Capella, in addition to improved performance and usability.

MapleMBSE provides an intuitive, Excel-based interface to the systems model with optimized, task-specific views for editing the model directly, all while keeping the central model updated for use by all stakeholders. By eliminating the need to funnel all MBSE tasks through a small number of systems engineering tool experts, MapleMBSE democratizes the engineering process and significantly reduces the overhead, time, and errors that can arise when every stakeholder must use their primary MBSE tool. The new release of MapleMBSE adds support for Capella, a powerful MBSE platform from the Eclipse Foundation. Organizations using Capella can now edit models within MapleMBSE, allowing them to simplify MBSE tasks and increase engagement with MBSE processes at their company. For all MapleMBSE users, the new release brings a variety of performance improvements for loading and interacting with systems models, as well as new usability features to make tracking model revisions easier.

“Most project stakeholders aren’t experts in MBSE tools, so they are hesitant to engage with the overall systems engineering processes at their company. Modern engineering projects have made systems engineering processes vitally important to success, requiring all stakeholders to be in collaboration. With MapleMBSE, it is easy for all stakeholders to contribute to the systems engineering process,” says Paul Goossens, Vice President of MBSE Solutions at Maplesoft. “This new release brings MapleMBSE to even more systems engineers, and promises to make stakeholder engagement even easier than before.”

In addition to supporting Capella, the new release of MapleMBSE allows engineers to easily manage project traceability and realizations using matrices. Users of other MBSE platforms, including IBM Engineering Systems Design Rhapsody and Cameo Systems Modeler by No Magic, will benefit from improved performance across MapleMBSE, especially when importing and editing large models. When working with systems models, MapleMBSE now includes a revision browser to view comments and changes made to the systems model by other stakeholders. The new version also allows users to include predicate filtering in their model queries, allowing for faster and more automated ways to ensure model details are accurate.

Maplesoft
www.maplesoft.com

MapleSim Insight simplifies machine-level controller testing

July 28, 2020 By WTWH Editor Leave a Comment

Maplesoft announced the release of MapleSim Insight, a software product that gives machine builders powerful, simulation-based debugging and 3-D visualization capabilities that directly connect to their automation tools. As a result, engineers can perform simulation-based testing of their controller easily and efficiently.

Simulation-based testing of machine control strategies is a key element of virtual prototyping and using digital twins for virtual commissioning. However, this step can be cumbersome, as many automation tools provide limited options for machine-level, simulation-based controller testing, and these options often require moving development to an entirely new platform. By providing a real-time connection to most common automation platforms, MapleSim Insight shows machine designers exactly how their control strategies will impact the machine. Adjustments and fine-tuning of the design can happen virtually, reducing the number of expensive physical prototypes that will be required.

MapleSim Insight works with any automation tool that supports compiled Function Mock-up Units (FMUs), such as the Rockwell Studio 5000 Environment or MathWorks Simulink. The machine model is first developed in MapleSim, the advanced system-level modeling tool from Maplesoft, and then exported as an FMU, an open standard format for sharing models. MapleSim Insight connects to the automation tool, and displays visual results in real-time to show how the model behaves as the controller is running. MapleSim Insight provides both 3-D visualizations for quick visual feedback, and 2-D plots to get precise answers for testing and debugging, so the engineer can always get the level of detail required.

“Digital models are invaluable for the design and testing of a system, acting as a virtual test bench for the machine’s control software. But hooking the model into your preferred controller platform can be very difficult, and often one of the critical pieces for debugging – the visualization of the mechanism itself – is lost,” said Chad Schmitke, Senior Director, Product Development, Maplesoft. “Now, with MapleSim Insight, visualizing and interrogating your model is as simple as running an FMU in your preferred automation environment. You get the robust back-end code to emulate the physics, coupled with the plotting and visualization necessary to interpret what is happening. ”

MapleSim Insight is part of the MapleSim family of modeling and simulation products from Maplesoft. The newly released MapleSim 2020 lets you build and test models more quickly than ever, providing faster simulations, powerful new tools for machine builders, and expanded modeling capabilities. The MapleSim 2020 product family also includes the new MapleSim Ropes and Pulleys Library add-on, which allows engineers to easily incorporate winch and pulley systems in their machine models.

Maplesoft
www.maplesoft.com

Maple 2020 includes problem-solving capabilities and developer tools

March 12, 2020 By Leslie Langnau Leave a Comment

Maple 2020, based on Maple mathematical software, offers a collection of enhancements for both long-time customers and those new to the program.

Maple 2020 delivers a more powerful math engine, new and improved tools for interactive problem solving, application development, student learning, document creation, and programming.

Highlights include:
• Greater problem-solving abilities with new algorithms and solving techniques in differential equations, calculus, abstract algebra, integral transforms, graph theory, physics, and other areas of math, science, and engineering.
• Enhanced programming tools that help users find and fix problems in their own code.
• Additional clickable math tools, improved tutors, and an expanded Student package to support teaching and learning linear algebra.
• Enhanced signal processing abilities for the exploration of signals of all types, including data, image, and audio processing.
• More flexibility and improved output for printing, export to PDF, and LaTeX export, making content easier to share and use outside of Maple.

Maple 2020 includes many new features to help new users become productive faster. It provides new, more easily accessible Getting Started resources for an efficient introduction to fundamental Maple concepts. Additional improvements include new warnings that help users avoid common beginner mistakes, and improved messages to help users diagnose and recover from errors quickly.
Maple is available in several languages including French, Spanish, Simplified Chinese, and Brazilian Portuguese. A Japanese version of Maple 2020 will be available in a few weeks.

Maplesoft
www.maplesoft.com/products/maple/new_features

Latest MapleMBSE release democratizes systems engineering process

September 23, 2019 By Leslie Langnau Leave a Comment

Maplesoft announced a new release of MapleMBSE, the software that enables companies to employ a Model-Based Systems Engineering (MBSE) process within their design projects without requiring every stakeholder on the project to be an expert in complex MBSE tools. The latest release, MapleMBSE 2019.1, offers enhanced modeling support, making it easier to build and investigate model structures, as well as new integration options with model management systems.

MapleMBSE provides a streamlined, Excel-based interface to the systems model with task-specific views for editing the model directly, thereby ensuring consistent information and knowledge sharing across the design group. The familiar Excel interface enables subject matter experts to obtain and analyze the information they need to make decisions, and to feed the results back into the model. By eliminating the need to funnel everything through a small number of systems engineering tool experts, MapleMBSE reduces the overhead, time, and errors that typically come with using a standard systems engineering tool. The new release provides more tools for building, modifying, and investigating models, including support for new datatypes that make it easier to work with requirements, parametric diagrams, and internal blocks. New search tools also allow engineers to retrieve a list of all the requirements defined in the model, regardless of where they are found in the model structure, making it much easier to obtain a global view of the system. In addition, new example models are now available that illustrate best practices. These models can also be used as templates for building new models, reducing development time.

The new release also expands connectivity options, with the ability to integrate MapleMBSE with the latest release of the model management software from No Magic, Teamwork Cloud 19. By connecting MapleMBSE to Teamwork Cloud, customers seamlessly access models created in a number of different tools, including MapleMBSE, MagicDraw, and Cameo Systems Modeler. MapleMBSE can also be integrated directly with other SysML-based tools, such as IBM Rational Rhapsody.

Maplesoft
www.maplesoft.com

MapleSim 2019 improves performance, increases modeling scope

May 23, 2019 By WTWH Editor Leave a Comment

Maplesoft announced a new release of MapleSim, the advanced system-level modeling tool. From digital twins for virtual commissioning to system-level models for complex engineering design projects, MapleSim helps organizations reduce development risk, lower costs, and enable innovation. The latest release provides improved performance, increased modeling scope, and more ways to connect to an existing toolchain.

Simulation is faster for all customers in MapleSim 2019 due to more efficient handling of constraints when preparing the model, resulting in more compact, faster simulation code without any loss of fidelity. These results mean that MapleSim’s industry-leading speeds have gotten even better, saving time and enabling more real-time applications. In addition, models developed in MapleSim and then exported for use in other tools also run faster in the target applications.

New built-in and add-on components and expanded support for external libraries means that engineers can create more models, faster, in MapleSim 2019. The new release expands the scope of models that can be created using pre-existing components, with additions to hydraulics, electrical, multibody, and more. As well, the MapleSim Engine Dynamics Library from Modelon is a new add-on library that provides specialized tools for modeling, simulating, and analyzing the performance of combustion engines. This component library is especially useful for representing transient engine responses, and can be used for analyzing engine performance, performing emission studies, controls development, hardware-in-the-loop verification of vehicle electronic control units, and more.

Toolchain connectivity is essential to many MapleSim customers, and MapleSim 2019 offers important advances in toolchain integration. Improvements include additional options for FMI connectivity, including support for variable-step solvers, as well as fixed-step, for running imported models in MapleSim and exporting models to other tools. In addition, the new B&R MapleSim Connector add-on gives automation projects a powerful, model-based ability to test and visualize control strategies from within B&R Automation Studio, and to export simulation data for motor, servo, and gearbox sizing within SERVOsoft®.

“System level modeling has proven to be an invaluable tool for companies embarking on challenging engineering design projects, especially in the areas of automation and the creation of digital twins. Models can be used to both verify a design, as well as act as a virtual test bench for the machine’s control software – all before prototypes are built,” said Chad Schmitke, Senior Director, Product Development, Maplesoft. “Whether an organization wishes to develop their own models or work in partnership with the Maplesoft Engineering Solutions team, the improvements in performance, scope, and connectivity in MapleSim 2019 offer benefits to everyone.”

MapleSim is available in English, Japanese, and French.

Maplesoft
www.maplesoft.com

Maple 2019’s data analysis capabilities identify biomarkers of several cancers

April 12, 2019 By Leslie Langnau Leave a Comment

The ability to leverage complex data as a strategic asset is becoming increasingly critical, but the current labor market has a shortage of resources in big data analytics. Companies are faced with several challenges related to the inadequate resources necessary to process data. A long-time Maple user and quantum mechanics researcher, Marvin Weinstein, refers to the problem of extracting meaning from large data sets as, “How do we find a needle in a multi-dimensional haystack, when we don’t know what a needle is, and we don’t know if there is a needle in the haystack?”

Dynamic Quantum Clustering (DQC) accomplishes this feat by creating a density map of data using DQC’s proprietary Maple library, and Maple 2019 visualization tools. The result of a DQC analysis is a Maple animation that provides a visual record of the complex computations going on behind the scene. According to Marvin, Maple animations have been a big part of DQC’s success because they reveal answers without the complex mathematics. He says that, “these animations sell our product because they leverage the human ability to spot patterns developing in time and space.”

With Maple’s prototyping abilities and customizable features, Marvin was able to get DQC up and running within a week. Marvin confesses that “whenever I can avoid having to do things [manually], I do so.” By using the DQC compiled library within Maple, it was possible for Quantum Insights to have a powerful GUI without having to build the interface from scratch. Marvin believes that time is often wasted with unnecessary coding and analysis tasks, and exploits many of the built-in features of Maple to save time drive his research forward.

The core of DQC is an algorithm that maps a problem of unsupervised clustering to a problem in quantum mechanics. It uses quantum evolution to identify correlated information and reveals the details of the process through a Maple animation. This animation typically reveals hidden and unexpected insights into complex data. Marvin asserts that the aim of DQC is to “let the data speak for itself.” The advantage of working without making assumptions or hypotheses, without cleaning the data, and without the need for expert knowledge means that DQC is a data exploration method that is faster, cheaper and more efficient than current methods.

One of DQC’s major accomplishments thus far has been the identification of several biomarkers strongly correlated with multiple cancers. According to Marvin, TCGA analysis was selected as the initial step towards cancer research because cancer is a problem that everyone understands to be a big deal, and “we’ve all lost people we love to cancer.” The hope was that better clustering methods would allow mRNA from various tumor samples to better classify tumors into biologically relevant groups. The study identified 48 of 73,000 mRNA expressions that defined all five different cancer types. This analysis, published in Nature Scientific Reports, has demonstrated the ability to provide an accurate diagnosis of cancer type, based on molecular information alone, and has further revealed significant sub-typing of cancer cells, beyond what pathologists can currently achieve. The sensitivity to variation in mRNA expression patterns is the “holy grail” of precision medicine, because it promises to tell us which tumors are likely to respond to a drug and which tumors will not respond. Moreover, the analysis showed that DQC significantly outperformed tSNE-HDBScan, the current gold standard clustering method used in cancer data analytics.

Now, Marvin is working in pharmacogenomics to offer better diagnosis and treatment methods for cancer and other diseases. His company, Quantum Insights, is working towards developing effective, data-driven strategies. While Quantum Insight’s initial focus was cancer, the goal is to expand this research into other healthcare applications. Marvin believes that the DQC technique will help save lives wherever better analytics are required. Other successful applications of his research include Alzheimer’s data, detection of contraband nuclear material, analysis of the Sloan Digital Sky Survey Data, and other areas that utilize large amounts of data.

Maplesoft
www.maplesoft.com

Maple 2019 strengthens core math capabilities

March 15, 2019 By Leslie Langnau Leave a Comment

Maplesoft announced a new release of Maple, the mathematical software that makes it easy to analyze, explore, visualize, and solve math problems. Maple 2019 includes improvements to its mathematical engine for both core routines and specialized tools. The release also provides advances to the Maple programming language, more education tools, new visualizations, and other improvements for the mathematicians, educators, students, engineers, and scientists who use it.

Improvements include:

–Hundreds of improvements to core functionality, such as solving equations, integration, factoring, and differential equations
–Increasing the ease in finding symbolic solutions to partial differential equations, including new methods that solve new classes of problems, more flexibility in choosing the methods to try, and improved simplification of the results
–Significant work to strengthen, consolidate, and polish Maple’s support for tensor computations, with support for classical and quantum mechanics, special and general relativity, and standard tensor notation for input and output
–More group theory tools for constructing, computing with, and visualizing more groups, along with significant performance improvements
–More signal processing, including new algorithms, manipulation tools, and visualization techniques
–A comprehensive, easy-to-use environment for the parallel computation of the electronic energies and properties of molecules, available in the new add-on product, the Maple Quantum Chemistry Toolbox from RDMChem

Maple 2019 also includes a variety of improvements in other areas, such as enhancements to the Maple programming language that help customers write more efficient code, a redesigned start page that makes it even easier for new users to become productive quickly, new visualizations for analyzing data, and additional interactive Math Apps that support teaching and learning key concepts of computer science.

Maplesoft
www.maplesoft.com/products/maple/new_features

New MapleMBSE release from Maplesoft lets all stakeholders engage with the systems engineering process

February 20, 2019 By Leslie Langnau Leave a Comment

Bruce Jenkins | Ora Research

Maplesoft announced a new release of MapleMBSE, its software product that enables companies to employ a model-based systems engineering (MBSE) approach to their design projects without requiring every engineer on the project to be an expert in complex MBSE tools.

The new release, MapleMBSE 2019.0, further improves the workflow by making it even easier to create and modify many of the structures used to define and analyze a design. “The usability of MapleMBSE makes productive collaboration on system design projects an achievable goal,” the company said, “and the latest release improves the user experience even further.” For background see our MapleMBSE from Maplesoft radically expands accessibility of model-based systems engineering, published in this blog last July.

Excel-based user interface “provides streamlined interface for each task in an MBSE project”

Using an Excel-based user interface, MapleMBSE provides a streamlined interface for each task in an MBSE project, such as defining requirements, impact analysis, tradeoff studies and failure mode effects analysis. These streamlined interfaces make these tasks significantly easier to perform, the company says, and reduce the time and errors that typically come with using a standard MBSE tool. The new release also includes enhanced support for Systems Modeling Language (SysML), the industry-standard systems architecture modeling language used for requirements capture and management by many MBSE tools, including MapleMBSE.

MapleMBSE time savings reported by Nissan over other MBSE tool.

Increased support is available for a variety of constructs that are used to define requirements, architecture, behavior and relationships, including activity diagrams, state machines and parametric diagrams. By making it easier to create and modify these underlying SysML constructs, the company says the new release further reduces the time and effort required to define requirements and the relationships between them, analyze the impact of changes, and improve the design.

MBSE “lets organizations define, maintain and communicate their project goals throughout every stage of their project”

“Model-based systems engineering lets organizations define, maintain and communicate their project goals throughout every stage of their project, and MapleMBSE makes it significantly easier to involve all the stakeholders in this process,” says Paul Goossens, vice president of engineering solutions at Maplesoft. “The usability of MapleMBSE makes productive collaboration on system design projects an achievable goal, and the latest release improves the user experience even further.”

Other improvements in this release enhance the integration of MapleMBSE with model management systems, including faster model access through Teamwork Cloud. By connecting MapleMBSE to Teamwork Cloud, customers can seamlessly access models created in a number of different tools including MagicDraw and Cameo Systems Modeler. MapleMBSE can also be integrated directly with other SysML-based tools such as IBM Rational Rhapsody.

About Maplesoft

Maplesoft is a leading provider of high-performance software tools for engineering, science and mathematics. Maplesoft Engineering Solutions provide advanced tools and services for system simulation, calculation management and systems engineering, helping organizations maximize the power of their engineering knowledge so they can complete their projects quickly and successfully. The Maplesoft product suite includes Maple for technical computing and calculation management; MapleSim, an advanced system-level modeling and simulation tool; and MapleMBSE, which supports a model-based systems engineering approach to requirements management.

Maplesoft products and services are used in machine design, robotics, aerospace, automotive, industrial automation and many other fields where engineers face complex challenges. Key applications include the creation of digital twins, dynamic analysis of mechanisms, battery systems modeling, heat transfer modeling and bus fleet electrification. Customers include Boeing, FLSmidth, Ford, Google, Intel, NASA, Samsung and others.

System-Level modeling is a smarter approach to vehicle design

October 4, 2018 By Leslie Langnau Leave a Comment

The demand for innovation is universal across industries, as new products are required to meet higher performance standards without slowing the overall time to market. This reality is perhaps most apparent in the automotive industry, where a wide range of technologies must come together seamlessly if a new product is to be successful. At China Euro Vehicle Technology (CEVT), new development techniques are being created to bring new technologies into passenger vehicles, and ensure successful integration of the many systems present in modern designs.

One of the more advanced technologies available for modern automotive design is system-level modeling, which uses specialized software to model the interactions across an entire system. By taking a system-level modeling approach, CEVT engineer Michael Palander is creating a powerful testing and simulation platform that can be used to verify the functionality of their new automotive technologies at earlier stages in the design process. With its Modelica standard for system-modeling components, the team decided to evaluate MapleSim as the modeling and simulation tool for their larger simulation platform.

The team at CEVT is aiming to create a powerful simulation platform that can validate a wide range of design components, from software controllers to individual hardware subsystems, in what is known as “in-the-loop” simulations. For these kinds of simulations, the system-level models are created not only to be highly accurate, but they must be capable of very efficient computation for real-time usage on test platforms. They chose MapleSim for its ability to create efficient royalty-free code that can run in real-time.

In order to avoid the slowdowns typically involved with taking on a new modeling tool, the Chalmers research team opted for customized training services provided by Maplesoft Engineering Solutions. During a three-day training program, modeling experts from Maplesoft worked directly with the research team, helping them become proficient with MapleSim. The team quickly worked through the basics of model creation, before moving on to training related to their specific project needs, including code generation, exporting models to the Functional Mock-up Interface (FMI) standard, and creating custom components to account for their specific designs. “It’s very easy to get started with MapleSim,” noted Mr. Palander, as he observed his team moving quickly through their design-specific modeling needs.

By working with Maplesoft’s modeling experts, the teams at Chalmers and CEVT were able to easily and efficiently develop workable processes for integrating MapleSim with their own tools, such as their simulation platform, CarMaker. They now use MapleSim to create vehicle models and export them into Functional Mock-up Units (FMUs), which then connect into the rest of their toolchain. The training also provided the engineers and researchers with MapleSim model optimization techniques so they could make quick iterations on design concepts before moving their testing to their in-the-loop simulation platforms.

The approach taken by CEVT in evaluating MapleSim and training as a team in system-level modeling is a sign of their larger commitment to new, innovative approaches in vehicle design. By looking to integrate powerful system-level modeling tools like MapleSim, CEVT is maintaining its position as a leader in virtual engineering techniques. CEVT also ensured they stayed competitive by using Maplesoft’s Engineering Solutions to evaluate their new software as quick as possible. With help from MapleSim, Mr. Palander is confident that CEVT’s system-level modeling project is proceeding in the right direction: “We will succeed in this, I am absolutely sure.”

Maplesoft
www.maplesoft.co