AWS Thinkbox Stoke Description
Developing particle simulations for Autodesk 3ds Max can be achieved with greater efficiency than many competing fluid dynamics plugins, enabling artists without coding or scripting skills to utilize a flexible procedural geometry modifier with ease. This tool also offers an intuitive channel-editing interface, akin to what is found in node-based image compositing software. Unlike the Autodesk 3ds Max SDK, it does not provide optimized geometry and particle lookup functions, which is where AWS Thinkbox Stoke excels, allowing for the rapid generation of expansive particle clouds. Additionally, it supports various formats, including PRT and RealFlow BIN, while also facilitating simulations from several popular plugins like FumeFX, Particle Flow, cebas thinkingParticles, and 3ds Max Force Space Warps. Users can create and simulate new fields, such as velocity fields, as well as manage field data through widely accepted formats. This functionality can be seamlessly integrated with 3ds Max subsystems, including Particle Flow, MassFX, Hair and Fur, and various materials and renderers. The user-friendly nature of this solution empowers artists to focus on their creative process without the burden of technical complexities.
AWS Thinkbox Stoke Alternatives
Azore is software for computational fluid dynamics. It analyzes fluid flow and heat transfers. CFD allows engineers and scientists to analyze a wide range of fluid mechanics problems, thermal and chemical problems numerically using a computer. Azore can simulate a wide range of fluid dynamics situations, including air, liquids, gases, and particulate-laden flow. Azore is commonly used to model the flow of liquids through a piping or evaluate water velocity profiles around submerged items. Azore can also analyze the flow of gases or air, such as simulating ambient air velocity profiles as they pass around buildings, or investigating the flow, heat transfer, and mechanical equipment inside a room. Azore CFD is able to simulate virtually any incompressible fluid flow model. This includes problems involving conjugate heat transfer, species transport, and steady-state or transient fluid flows.
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NetCrunch is a next-gen, agentless infrastructure and traffic network monitoring system designed for hybrid, multi-site, and fast changing infrastructures. It combines real-time observability with alert automation and intelligent escalation to eliminate the overhead and limitations of legacy tools like PRTG or SolarWinds. NetCrunch supports agentless monitoring of thousands of nodes from a single server-covering physical devices, virtual machines, servers, traffic flows, cloud services (AWS, Azure, GCP), SNMP, syslogs, Windows Events, IoT, telemetry, and more.
Unlike sensor-based tools, NetCrunch uses node-based licensing and policy-driven configuration to streamline monitoring, reduce costs, and eliminate sensor micromanagement. 670+ built-in monitoring packs apply instantly based on device type, ensuring consistency across the network.
NetCrunch delivers real-time, dynamic maps and dashboards that update without manual refreshes, giving users immediate visibility into issues and performance. Its smart alerting engine features root cause correlation, suppression, predictive triggers, and over 40 response actions including scripts, API calls, notifications, and integrations with Jira, Teams, Slack, Amazon SNS, MQTT, PagerDuty, and more.
Its powerful REST API makes NetCrunch perfect for flow automation, including integration with asset management, production/IoT/operations monitoring and other IT systems with ease.
Whether replacing an aging platform or modernizing enterprise observability, NetCrunch offers full-stack coverage with unmatched flexibility. Fast to deploy, simple to manage, and built to scale-NetCrunch is the smarter, faster, and future-ready monitoring system. Designed for on-prem (including air-gapped), cloud self-hosted or hybrid networks.
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iGRAF
iGRAF is a comprehensive simulation tool that integrates powder and multiphase flow dynamics, effectively bridging the gap between these two domains. This innovative solution is tailored to accurately replicate a diverse array of powder behaviors while setting new benchmarks in simulation technology. With its advanced DEM-CFD solver, iGRAF provides users with the capability to perform precise analyses of both single-phase and multiphase flows, thereby enhancing the understanding of particle-fluid interactions within a unified platform. The tool's dynamic geometry control features allow for translations, rotations, vibrations, and customizable motion, enabling teams to effectively capture the intricate dynamics of complex systems. Additionally, it incorporates validated models for liquid bridging and van der Waals forces to evaluate the effects of moisture and adhesion on particle behavior, with its liquid bridge force model confirmed for moisture levels of up to 15%. Furthermore, iGRAF employs the Signed Distance Function along with the Immersed Boundary Method to adeptly identify and manage arbitrary solid geometries, ensuring flexibility in various applications. This versatility makes iGRAF an invaluable asset for researchers and engineers working with complex multiphase systems.
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MercuryDPM
MercuryDPM is an open-source software designed for conducting discrete particle simulations, enabling the analysis of particle or atom movement through the application of forces and torques from external influences, such as gravitational and magnetic fields, as well as from laws governing particle interactions. In the context of granular particles, these interactions predominantly consist of contact forces, which can include elastic, plastic, viscous, and frictional effects, while molecular simulations may utilize interaction potentials like Lennard-Jones. This software is developed in a robust, object-oriented C++ framework, emphasizing clarity, flexibility, and extensibility to accommodate the needs of researchers and engineers tasked with developing new simulation models. Although primarily focused on granular material applications, MercuryDPM is designed to be versatile enough to handle various particle-based systems and accommodate long-range interaction scenarios. Users are supported by comprehensive documentation that walks them through the processes of installation, executing simulations, visualizing results, analyzing data, and creating custom MercuryDPM codes tailored to simulate their specific systems of interest. Overall, MercuryDPM represents a valuable tool for advancing the understanding of particle dynamics across a range of scientific fields.
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Pricing
Free Trial:
Yes
Integrations
Company Details
Company:
Amazon
Year Founded:
1994
Headquarters:
United States
Website:
aws.amazon.com/thinkbox-stoke/
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Online Support
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