Dr. Jan Vandenbrande

Defense Advanced Research Projects AgencyStaff

Defense Sciences Office (DSO)

Program Manager

Dr. Jan Vandenbrande joined DARPA as a program manager in July 2015. He is interested in developing math and computational tools to radically improve the design of mechanical products. Topics of specific interest to Dr. Vandenbrande include: exploiting new design possibilities enabled by new materials and fabrication processes (3-D printing, composite fibers, micro truss structures) and enhancing design discovery.

Before joining DARPA, Dr. Vandenbrande was a technical fellow and senior manager of the Applied Math Geometry and Optimization group at Boeing. He leveraged his knowledge in geometric reasoning, production automation and design processes to create several advanced geometry processing systems to change how products are designed and made. Boeing uses these tools to conduct design trade and optimization studies, to enable proprietary composite layup fabrication processes, and to visualize metal machinability issues. Dr. Vandenbrande authored several parametric air and spacecraft models for design trade studies such as the hypersonic X-43C and the Orbital Space Plane study.

At Unigraphics, now Siemens NX, Dr. Vandenbrande worked on the architecture of the next-generation Computer Aided Manufacturing (CAM) system, improving tool path generation performance and revamping the CAM user interface. He received his Ph.D. in Electrical Engineering from the University of Rochester for his work on machinable feature recognition.

| Manufacturing | Materials |

Contact Dr. Jan Vandenbrande

Programs

Open Manufacturing

Uncertainties in materials and component manufacturing processes are a primary cause of cost escalation and delay during the development, testing and early production of defense systems. In addition, fielded military platforms may have unanticipated performance problems, despite large investment and extensive testing of their key components and subassemblies. These uncertainties and performance problems are often the result of the random variations and non-uniform scaling of manufacturing processes. These challenges, in turn, lead to counterproductive resistance to adoption of new, innovative manufacturing technologies that could offer better results.

Enabling Quantification of Uncertainty in Physical Systems (EQUiPS)

Complex physical systems, devices and processes important to the Department of Defense (DoD) are often poorly understood due to uncertainty in models, parameters, operating environments and measurements. The goal of DARPA’s Enabling Quantification of Uncertainty in Physical Systems (EQUiPS) program is to provide a rigorous mathematical framework and advanced tools for propagating and managing uncertainty in the modeling and design of complex physical and engineering systems. Of particular interest to the program are systems with multi-scale coupled physics and uncertain parameters in extremely high-dimensional spaces, such as new aerospace vehicles and engines.

Fundamental Design (FUN Design)

The goal of the Fundamental Design (FUN Design) program is to determine whether we can develop or discover a new set of building blocks to describe conceptual designs. The design building blocks will capture the components’ underlying physics allowing a family of nonintuitive solutions to be generated.

Materials Development for Platforms (MDP)

Military platforms—such as ships, aircraft and ground vehicles—rely on advanced materials to make them lighter, stronger and more resistant to stress, heat and other harsh environmental conditions. Currently, the process for developing new materials to field in platforms frequently takes more than a decade. This lengthy process often means that developers of new military platforms are forced to rely on decades-old, mature materials because potentially more advanced materials are still being developed and tested, and are considered too large a risk to be implemented into platform designs.

Models, Dynamics and Learning (MoDyL)

Complex, nonlinear, multiscale dynamical systems are ubiquitous. Examples include weather, fluids, materials, biological systems, communication networks, and social systems. These systems often evolve to a critical state built up from a series of irreversible and unexpected events, which severely limits development and implementation of mathematical models to accurately predict formation and evolution of patterns in such systems.

Tailorable Feedstock and Forming (TFF)

The capabilities and technical specifications required for Department of Defense (DoD) platforms are constantly changing due to unanticipated circumstances, needs and emerging threats. However, complex development and design cycles and the associated high costs of structural design changes for current technologies significantly limit our ability to rapidly and affordably evolve such systems.

Transformative Design (TRADES)

New manufacturing technologies such as additive manufacturing have vastly improved the ability to create shapes and material properties previously thought impossible. Generating new designs that fully exploit these properties, however, has proven extremely challenging. Conventional design technologies, representations, and algorithms are inherently constrained by outdated presumptions about material properties and manufacturing methods. As a result, today’s design technologies are simply not able to bring to fruition the enormous level of physical detail and complexity made possible with cutting-edge manufacturing capabilities and materials.

Dr. Jan Vandenbrande

Defense Sciences Office (DSO)

Program Manager

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Selected DARPA Achievements

Dr. Jan Vandenbrande

Defense Sciences Office (DSO)

Program Manager

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Selected DARPA Achievements