Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Daniel Melanz is active.

Publication


Featured researches published by Daniel Melanz.


ieee international conference on high performance computing data and analytics | 2015

Chrono: An Open Source Multi-physics Dynamics Engine

Alessandro Tasora; Radu Serban; Hammad Mazhar; Arman Pazouki; Daniel Melanz; Jonathan A. Fleischmann; Michael R. Taylor; Hioyuki Sugiyama; Dan Negrut

We provide an overview of a multi-physics dynamics engine called Chrono. Its forte is the handling of complex and large dynamic systems containing millions of rigid bodies that interact through frictional contact. Chrono has been recently augmented to support the modeling of fluid-solid interaction (FSI) problems and linear and nonlinear finite element analysis (FEA). We discuss Chrono’s software layout/design and outline some of the modeling and numerical solution techniques at the cornerstone of this dynamics engine. We briefly report on some validation studies that gauge the predictive attribute of the software solution. Chrono is released as open source under a permissive BSD3 license and available for download on GitHub.


SAE International Journal of Passenger Cars - Electronic and Electrical Systems | 2013

Investigating Through Simulation the Mobility of Light Tracked Vehicles Operating on Discrete Granular Terrain

Dan Negrut; Daniel Melanz; Hammad Mazhar; David Lamb; Paramsothy Jayakumar; Michael D. Letherwood

This paper presents a computational framework for the physics-based simulation of light vehicles operating on discrete terrain. The focus is on characterizing through simulation the mobility of vehicles that weigh 1000 pounds or less, such as a reconnaissance robot. The terrain is considered to be deformable and is represented as a collection of bodies of arbitrary shape. The modeling stage relies on a novel formulation of the frictional contact problem that requires at each time step of the numerical simulation the solution of an optimization problem. The proposed computational framework, when run on ubiquitous Graphics Processing Unit (GPU) cards, allows the simulation of systems in which the terrain is represented by more than 0.5 million bodies leading to problems with more than one million degrees of freedom. The numerical solution for the equations of motion is tailored to map on the underlying GPU architecture and is parallelized to leverage more than 1500 Scalar Processors available on modern hardware architectures. As a demonstration of this technology, we present the simulation of a light tracked vehicle that negotiates several obstacles whose dimensions are comparable to those of the vehicle. The number of bodies used to represent the vehicle is larger than 100 and the terrain the vehicle operates on is considered to be made up of gravel.


Journal of Computational and Nonlinear Dynamics | 2013

A Matrix-Free Newton–Krylov Parallel Implicit Implementation of the Absolute Nodal Coordinate Formulation

Daniel Melanz; Naresh Khude; Paramsothy Jayakumar; Dan Negrut

This paper sets out to demonstrate three things: (i) implicit integration with absolute nodal coordinate formulation (ANCF) is effective in handling very stiff systems when an accurate computation of the sensitivity matrix is part of the solution sequence, (ii) parallel computing can provide a vehicle for ANCF to tackle very large kinematically constrained problems with millions of degrees of freedom and produce results in a matter of seconds, and (iii) large systems of equations associated with implicit integration can be solved in parallel by relying on an iterative approach that avoids costly matrix factorizations, which would be prohibitively expensive and memory intensive. For (iii), the approach adopted relies on a Krylov–subspace method that is invoked in the Newton stage at each time step of the numerical solution process. The proposed approach is validated against a commercial package and several simple systems for which analytical solutions are available. A set of numerical experiments demonstrates the scaling of the parallel solution method and provides insights in relation to the size of ANCF problems that are tractable using graphics processing unit (GPU) parallel computing and implicit numerical integration.


ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference | 2012

A GPU Parallelization of the Absolute Nodal Coordinate Formulation for Applications in Flexible Multibody Dynamics

Daniel Melanz; Naresh Khude; Paramsothy Jayakumar; Mike Leatherwood; Dan Negrut

The Absolute Nodal Coordinate Formulation (ANCF) has been widely used to carry out the dynamics analysis of flexible bodies that undergo large rotation and large deformation. This formulation is consistent with the nonlinear theory of continuum mechanics and is computationally more efficient compared to other nonlinear finite element formulations. Kinematic constraints that represent mechanical joints and specified motion trajectories can be introduced to make complex flexible mechanisms. As the complexity of a mechanism increases, the system of differential algebraic equations becomes very large and results in a computational bottleneck. This contribution helps alleviate this bottleneck using three tools: (1) an implicit time-stepping algorithm, (2) fine-grained parallel processing on the Graphics Processing Unit (GPU), and (3) enabling parallelism through a novel Constraint-Based Mesh (CBM) approach. The combination of these tools results in a fast solution process that scales linearly for large numbers of elements, allowing meaningful engineering problems to be solved. Disclaimer: Reference herein to any specific commercial company, product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or the Department of the Army (DoA). The opinions of the authors expressed herein do not necessarily state or reflect those of the United States Government or the DoA, and shall not be used for advertising or product endorsement purposes.


SAE 2014 World Congress & Exhibition | 2014

A Multibody Dynamics-Enabled Mobility Analysis Tool for Military Applications

Daniel Melanz; Hammad Mazhar; Dan Negrut

1 Abstract This paper describes a modeling, simulation, and visualization framework aimed at enabling physicsbased analysis of ground vehicle mobility. This framework, called Chrono, has been built to leverage parallel computing both on distributed and shared memory architectures. Chrono is both modular and extensible. Modularity stems from the design decision to build vertical applications whose goal is to reduce the end-to-end time from vision-to-modelto-solution-to-visualization for a targeted application field. The extensibility is a consequence of the design of the foundation modules, which can be enhanced with new features that benefit all the vertical applications. Two factors motivated the development of Chrono. First, there is a manifest need of modeling approaches and simulation tools to support mobility analysis on deformable terrain. Second, the hardware available today has improved to a point where the amount of sheer computer power, the memory size, and the available software stack (productivity tools and programming languages) support computing on a scale that allows integrating highly accurate vehicle dynamics and physics-based terramechanics models. Although commercial software is available nowadays for simulating vehicle and tire models that operate on paved roads; deformable terrain models that complement the fidelity of present day vehicle and tire models have been lacking due to the complexity of soil behavior. This paper demonstrates Chrono’s ability to handle these difficult mobility situations through several simulations, including: (i) urban operations, (ii) muddy terrain operations, (iii) gravel slope operations, and (iv) river fording.


ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference | 2013

Chrono: A Parallel Physics Library for Rigid-Body, Flexible-Body, and Fluid Dynamics

Toby Heyn; Hammad Mazhar; Arman Pazouki; Daniel Melanz; Andrew Seidl; Justin Madsen; Aaron Bartholomew; Dan Negrut; David Lamb; Alessandro Tasora

This contribution discusses a multi-physics simulation engine, called Chrono, that relies heavily on parallel computing. Chrono aims at simulating the dynamics of systems containing rigid bodies, flexible (compliant) bodies, and fluid-rigid body interaction. To this end, it relies on five modules: equation formulation (modeling), equation solution (simulation), collision detection support, domain decomposition for parallel computing, and post-processing analysis with emphasis on high quality rendering/visualization. For each component we point out how parallel CPU and/or GPU computing have been leveraged to allow for the simulation of applications with millions of degrees of freedom such as rover dynamics on granular terrain, fluid-structure interaction problems, or large-scale flexible body dynamics with friction and contact for applications in polymer analysis.


ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference | 2014

Gauging Military Vehicle Mobility Through Many-Body Dynamics Simulation

Daniel Melanz; Hammad Mazhar; Dan Negrut

This paper describes a modeling, simulation, and visualization framework aimed at enabling physics-based analysis of ground vehicle mobility. This framework, called Chrono, has been built to leverage parallel computing both on distributed and shared memory architectures. Chrono is both modular and extensible. Modularity stems from the design decision to build vertical applications whose goal is to reduce the end-to-end time from vision-to-model-to-solution-tovisualization for a targeted application field. The extensibility is a consequence of the design of the foundation modules, which can be enhanced with new features that benefit all the vertical applications. Two factors motivated the development of Chrono. First, there is a manifest need of modeling approaches and simulation tools to support mobility analysis on deformable terrain. Second, the hardware available today has improved to a point where the amount of sheer computer power, the memory size, and the available software stack (productivity tools and programming languages) support computing on a scale that allows integrating highly accurate vehicle dynamics and physics-based terramechanics models. Although commercial software is available nowadays for simulating vehicle and tire models that operate on paved roads; deformable terrain models that complement the fidelity of present day vehicle and tire models have been lacking due to the complexity of soil behavior. This paper demonstrates Chrono’s ability to handle these difficult mobility situations through several simulations, including: (i) urban operations, (ii) muddy terrain operations, (iii) gravel slope operations, and (iv) river fording.


Mechanical Sciences | 2013

CHRONO: a parallel multi-physics library for rigid-body, flexible-body, and fluid dynamics

Hammad Mazhar; Toby Heyn; Arman Pazouki; Daniel Melanz; Andrew Seidl; Aaron Bartholomew; Alessandro Tasora; Dan Negrut


Journal of Terramechanics | 2014

Comparison of discrete element method and traditional modeling methods for steady-state wheel-terrain interaction of small vehicles

William Smith; Daniel Melanz; Carmine Senatore; Karl Iagnemma; Huei Peng


International Journal for Numerical Methods in Engineering | 2015

A GPU‐based preconditioned Newton‐Krylov solver for flexible multibody dynamics

Radu Serban; Daniel Melanz; Ang Li; Ilinca Stanciulescu; Paramsothy Jayakumar; Dan Negrut

Collaboration


Dive into the Daniel Melanz's collaboration.

Top Co-Authors

Avatar

Dan Negrut

University of Wisconsin-Madison

View shared research outputs
Top Co-Authors

Avatar

Hammad Mazhar

University of Wisconsin-Madison

View shared research outputs
Top Co-Authors

Avatar

Carmine Senatore

Massachusetts Institute of Technology

View shared research outputs
Top Co-Authors

Avatar

Karl Iagnemma

Massachusetts Institute of Technology

View shared research outputs
Top Co-Authors

Avatar

Arman Pazouki

California State University

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Aaron Bartholomew

University of Wisconsin-Madison

View shared research outputs
Top Co-Authors

Avatar

Naresh Khude

University of Wisconsin-Madison

View shared research outputs
Top Co-Authors

Avatar

Toby Heyn

University of Wisconsin-Madison

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge