U.S. Air Force Research Lab Summer Faculty Fellowship Program

U.S. Air Force Research Lab Summer Faculty Fellowship Program

U.S. Air Force Research Lab Summer Faculty Fellowship Program

AFRL/RW (Eglin Air Force Base, Florida )

SF.45.22.B10114: Probabilistic Modeling of Localized Dissipation in Energetic Materials

Rumchik, Chad - 850-882-7243

Energetic materials can be subjected to a variety of thermomechanical loads in practice. The response of these materials to such loads depends on their initial composition, density, and microstructure, and on the load amplitude, duration, rate, and history. Deformation induced dissipation, which is sensitive to the material’s load history, represents a driving mechanism for energy localization within the microstructure that can trigger chemical reaction and possibly detonation. Therefore, it is important to characterize how variations in the properties of energetic materials can affect dissipation when they are subjected to complex loads. This research aims to experimentally and theoretically characterize dissipation and hysteretic changes in density and microstructure due to cyclic mechanical loading of energetic materials. We are particularly interested in developing new probabilistic approaches to quantify the occurrence of deformation induced regions of intense localized dissipation (referred to as hot-spots) within the framework of experimentally validated macroscale deformation models.

SF.45.22.B10113: Machine Learning & Statistical Analysis for Modeling Materials

Kammerdiner, Alla - 850-883-5243

This program focuses on extending understanding and developing numerical tools for materials and structures under high temperatures and/or high pressures. Modeling the bulk behavior of structural and energetic materials relies on microstructural composition, size and spatial distribution of material phases, pores and cracks. Defects and porosity can significantly alter the sensitivity, deflagration-mode, and detonation-mode energy release rate of an energetic material. Natural fragmentation of metals is dependent on small variations of material properties likely dependent on microstructural details. A considerable effort has been spent on the development of mesoscale models that elucidate the effects of microstructure. Computational design of materials via tailoring of microstructure is attractive, as it could enable tuning of behavior regardless of the desired behavior mode, yet is prohibitively expensive due to interactions of multiple physical phenomena that are scale-, time-, and microstructure-dependent. Linking high-resolution mesoscale models to macroscale analysis is challenging due to computational tractability limitations. Capturing important features of the microstructure while minimizing the amount of data translated from meso- to macro-scale is a key for the development of predictive macroscopic models. Recently, machine learning (ML) emerged as an approach to combat the high computational cost of physics-based models at multiple length- and time-scales. ML has also become a promising new avenue for analysis of material microstructures. We are interested in the development of ML methods that will enhance our computational capabilities in modeling and design of materials. Examples of such capabilities include but are not limited to (i) significant improvements in computational efficiency of the multi-physics models and large-scale computations and/or (ii) automatic segmentation, reconstruction, and characterization of three-dimensional microstructures from high-resolution imaging data. We are also interested in the development of statistical tools and approaches that will enhance our computational capabilities in modeling and design of materials. Examples of such capabilities include but are not limited to (i) reduced-order stochastic models to assess and capture microstructure variability and uncertainty and their influence on macroscopic properties and response of materials and (ii) statistical descriptors of material microstructures for rapid generation of statistically representative microstructures for mesoscale models and for the microstructure-dependent macroscale models.

SF.45.22.B10112: New Machine Learning Approaches for Computational Physics Modeling, Lethality, and Weapon Effects

Kammerdiner, Alla - 850-883-5243

Machine Learning (ML) and, more generally, Artificial Intelligence (AI) have recently emerged as powerful methodologies for improving our understanding of complex physical and virtual/cyber systems, phenomena, and processes. The ML/AI tools are particularly effective in the context of data analysis, when the data is heterogeneous, overlapping, incomplete, conflicting, etc. We are interested in the development of innovative ML/AI approaches and algorithms that advance the computational and data processing capabilities of the US Air Force. The particular topics of interest include but are not limited to physics-inspired and physics-informed ML, learning on graphs and mesh networks; ML for simulation codes and hydrocodes; ML and AI for development of digital twins and related models.

SF.45.22.B10105: Digital Design Tools for High Explosives

Dorgan, Robert - 850-496-7992

This research program will pursue digital design tools for modeling high explosive mechanical behavior, initiation, and performance across a wide variety of complex environments. One aspect of this program is the assessment and development of advanced models to predict a variety of phenomena including the following: (a) temperature / density / damage / microstructure dependent shock initiation, detonation propagation, overdriven, corner-turning, and dead-pressing phenomena; (b) violence of response from linkage of mechanical and reaction characteristics; and (c) enhanced blast/fragmentation effects from aluminized explosives. Knowledge of the thermodynamics leading to chemical reaction is required in order to link the state of the material under load to initial chemical kinetics of the explosive. A significant part of this effort will be to numerically develop experimental techniques that will demonstrate phenomena that standard empirical models cannot predict. Digital engineering tools for advancing numerical model development methodologies are also of interest, including for example developments leading to an experimental database with in-database machine learning capabilities for semi-automated numerical model development.

SF.45.22.B10104: Fractal Structure/Modeling of Energetic Materials

Crochet, Michael - 850-882-8228

Many energetic material systems consist of granular, porous mixtures that exhibit a heterogeneous morphology. It is well-known that thermo-mechanical-chemical processes occurring in the vicinity of these pores/cracks are critical to the development of a sustained (or failed) detonation when the material is subjected to shock loading. An extensive body of research has been devoted to bridging the dynamics of pore systems at these length scales (called the mesoscale), to the bulk response of an energetic system at the weapon component scale (the macroscale). The modeling and simulation approach has centered on the use of high-fidelity mesoscale models to develop mathematical approximations, referred to as surrogates, that can be used as inputs to macroscale codes. Thus, macroscale predictions would contain “enough” information about the mesoscale material response to preserve accuracy, while remaining tractable. However, the surrogate models still require a large number of high-fidelity mesoscale simulations for their construction; moreover, it is unclear if the surrogates contain all of the important mesoscale features. The aim of this work is to apply an alternative mathematical framework to this problem. Here, we use experimental imaging of the mesoscale structure to determine the fractal dimension of a representative energetic microstructure. We then seek to develop a fractal structure/property relationship that enables the construction of an alternative macroscale model description that natively accounts for fractal structure, and thus greatly reduces the reliance on surrogate models and their associated computational expense.

SF.45.21.B10032: Multi-structural multi-functional bio inspired materials

Talley, Jennifer - 850-883-0862

Ecological demands on a species have forced the development multifunctional materials and specialized materials. Examples include protection from crushing, thermal regulation, signaling and self-healing. In the most interesting cases, these materials include at least two of these amazing properties. In order to achieve some of these properties, these biological systems demonstrate the ability to self-assemble with high fidelity. Uncovering the designs that present these functions and translating them using biomimetic additive manufacturing would provide the Air Force with tunable on-site on-demand supplies.

SF.45.20.B0001: Target Signature Modeling

Watson, Robert - 850-883-1926

The Integrated Guidance Simulation branch within the Air Force Research Laboratory (AFRL/RWWG) develops leading edge capabilities for simulating measurements from imaging sensors flying within complex real-world environments. Resulting models are used for developing target processing, navigation, and surveillance algorithms, as well as to assess design performance in a variety of real-time and non-real-time test environments. These models capture in-band phenomenology associated with the objects within the environment; effects associated with weather and atmospheric propagation; and the sensor spatial, spectral, and temporal characteristics. Research challenges include implementation of phenomenology and sensor models in high-speed highly-parallel computer graphics architectures, modeling target phenomenology associated with complex dynamic events, modeling state-of-the-art optical and RF sensors, development of high-efficiency computer/software architectures, techniques for adaptive or variable database resolution, data mining for model validation, and real-time operability.

SF.45.19.B0004: Integrated Control and Estimation

Rutkowski, Adam - 850-883-2632

The trajectory of an autonomous vehicle has an effect on its ability to accurately estimate navigation states, particularly when absolute position references such as GPS are unavailable. The concept of Integrated Control and Estimation (ICE) is to command a vehicle in a manner that minimizes navigation uncertainty and directs the vehicle to a goal location while observing constraints on travel time, energy, and maneuverability. Using ICE, navigation accuracy can be significantly improved in vision-aided, RF-aided, and cooperative scenarios compared to baseline trajectories that simply minimize travel time. However, determining trajectories that minimize navigation uncertainty remains a challenge, especially without limiting the set of possible trajectories. The goal of this research is to work toward a generally applicable and computationally tractable method of minimizing navigation uncertainty that does not depend on limiting assumptions.

SF.45.19.B0003: Single and Multi-Agent Navigation and Autonomy

Brink, Kevin - 850-882-4600

AFRL/RW has interest in a wide range of GPS-denied navigation technologies. These desired capabilities can involve single or multi-agent, networked systems, for indoor or near-ground applications to long range navigation, possibly over water or feature-poor terrain.
This topic is generally focused on the estimation theory and effectively and robustly leveraging a low cost suite of sensors to drastically bound positioning uncertainty of the integrated navigation system (INS). However, interest in cooperative task determination and/or single or multi-agent guidance, path planning, or control systems are also appropriate. For the networked system navigation problem there are currently opportunities to significantly improve the state of the art for robust (with respect to communication delays and dropouts), scalable (beyond five or 10) systems which are both computationally tractable and feasible with respect to the required communication bandwidth. An additional emphasis is place on approaches which do not require significant a priori information (e.g. assume cooperative agents all have access to GPS) in order to successfully initialize their respective systems.
Participating researchers will have access to the University of Florida Research Engineering and Education Facility’s (UF REEF) Autonomous Vehicles Lab (AVL), a multidisciplinary research lab which facilitates proof-of-concept simulation and hardware demonstrations for guidance, navigation, and control (GNC) applications. The AVL is an AFRL lead lab space with a wide range of commercial off the shelf (COTS) hardware including multi-rotors, ground vehicles, on-board processors, base stations (laptops/PCs), motion capture reference system, and several sensor options. Researchers working at the AVL enjoy the support of a full-time Research Engineer with knowledge of the facility and its existing capabilities (including autonomous multi-rotor flight using only onboard sensors and processing) which helps expedite new proof-of-concept implementations and has led to 25+ published papers in the past 4 years.

SF.45.19.B0002: Nonlinear Fiber Optics & Active Imaging Research

Keyser, Christian - 850-882-4184

Research opportunities are available in the areas of spectropolarimetric LiDAR, nonlinear fiber optics, and quantum-sensing. EO seeker sensors require low cost, size, weight, and power (CSWaP) architectures and components that meet demanding performance requirements. Active imaging sensors, such as LiDAR, are being studied to enable autonomous vehicle navigation, reconnaissance, and automatic target recognition. LiDAR sensors are uniquely suited for these needs in that they are able to produce 3-D images of targets, scan varying fields of view, and measure the optical response of targets improving target-clutter discrimination and target identification (ID). Our research program is focused on developing novel active imaging techniques and enabling technologies for target detection and identification. As such, our research program spans a wide range of topics including development of multispectral and polarimetric LiDAR imaging techniques, nonlinear fiber optics in gas-filled hollow-core photonic crystal fibers, and quantum imaging techniques.
Multispectral and polarimetric LiDAR research focuses on novel low-CSWaP architecture development, materials characterization and classification, signal processing, and experimental demonstration. Nonlinear fiber optics is pursued as an enabling technology for the LiDAR; the research focuses on developing tunable or wavelength-agile multispectral sources. In particular, we have been investigating stimulated Raman scattering and four-wave mixing in gas-filled hollow-core photonic crystal fibers. Lastly, quantum imaging is a new frontier to the scientific community and our group; we seek to leverage the quantum properties of light to increase the performance of active imaging systems while reducing CSWaP. Research topics may be experimental or theoretical in nature. Please contact us to discuss mutual interest. Applicants must be US persons.
1. P. St. J. Russell, , P. Hölzer, W. Chang, A. Abdolvand, & J. C. Travers, Hollow-core photonic crystal fibres for gas-based nonlinear optics, Nature Photonics volume 8, pages 278–286 (2014)
2. M. Genovese, Real applications of quantum imaging, 2016 J. Opt. 18 073002
3. R. M. A. Azzam, Stokes-vector and Mueller-matrix polarimetry [Invited], J. Opt. Soc. Am. A 33, 1396-1408, 2016.
4. M. A. Powers and C. C. Davis, Spectral LADAR: active range-resolved three-dimensional imaging spectroscopy, Applied Optics, vol. 51, pp. 1468–1478, 2012.
Keywords: LiDAR, LADAR, laser, multispectral imaging, polarimetric imaging, optical detection, nonlinear optics, quantum sensing, quantum imaging.

SF.45.19.B0001: Non-Bayesian Multisensor Integration for Navigation

Eilders, Martin - (850) 883-0113

Concerns regarding the vulnerability of GPS to intentional interference through spoofing or jamming, coupled with intermittent availability due to congestion of modern day urban battlefields has motivated research into alternative solution approaches. Several solutions have been presented in the relevant literature. However, nearly all approaches have been based on the fusion of data by way of a Bayesian filtering technique. The primary concern with Bayesian data fusion methods is the reliance on predefined process and measurement models. The ability to consider atypical data sources for the unintended purpose of navigation aiding is at the core of so-called "Plug-and-Play" system configurations. The goal of this research is to investigate viable candidate data fusion methodologies in the context of autonomous navigation in order to facilitate sustained navigation solutions in highly contested environments.

SF.45.18.B0005: Structural Reactive Materials

Overdeep, Kyle - 850-882-2960

Reactive material structures or structural reactive materials (SRM) are being investigated for use in ordnance to increase energy or add energy to munition systems. For instance, many munition parts are made from steel. While steel has highly desirable strength properties, it does not contribute to the energy produced by the weapon. If we make a reactive material with the density and strength of steel, we can swap out the steel in a munition with a steel-like reactive material that would burn or react and produce additional energy when the weapon was detonated. Therefore, we are interested in two aspects of SRM:
a) Methods to process reactive powders that are scalable (so that large pieces or components can be made) while retaining or increasing the structural strength of the component. For example, powder metallurgy, steel-making approaches, weaving, etc.
b) Modeling that designs strong SRM, to include computational thermodynamics that represents various phases of multicomponent systems to optimize strength and processing pathways, and other materials design modeling techniques.

SF.45.18.B0004: Diagnostics for Explosive Environments

Johnson, Stephanie - (850) 882-8979

Weapons effects and performance are partially dependent on the explosive fill, and different effects are desired for different purposes. Validation-quality experimental data are difficult to obtain in explosive environments due to the mechanical and thermal shock insult of the explosive front, the short time and length scales of the explosion, the transient and turbulent nature of the detonation product gases, and the multiphase nature of the gases with fragments/particles. We are interested in developing and/or applying novel diagnostic techniques to characterize the explosive fireball (internally and externally) for model validation and weapon design. Specifically, we aspire to obtain coupled, time-resolved, multi-dimensional measurements of pressure, temperature, velocity, and/or species in this dynamic environment to understand underlying mechanisms of weapons effects. Flow visualization and 3D tomography of the explosive fireball is also desired. The faculty fellow will gain experience developing diagnostics and performing explosive experiments in test facilities such as indoor blast chambers and outdoor arenas.
Keywords: explosive fireball, blast wave, shock wave, diagnostics, pressure, temperature, velocity, species, flow visualization, tomography

SF.45.18.B0003: Electromagnetics, Plasmonics, Photonics and Metamaterials

Allen, Monica - 850-883-0593

This research involves multidisciplinary work in the application of various engineering and scientific disciplines with the purpose of exploration, discovery, and exploitation of basic materials properties to design and control the interaction of electromagnetic waves with matter. Our aim is to develop new, improved multifunctional materials, technologies and devices to operate in complex electromagnetic environments and environmental conditions. Specifically the major objectives of this work are to design, simulate and fabricate subwavelength structures, plasmonic and micro-/nano-resonant structures and devices for optical, photonic and RF applications. Examples of such structures include metallic media, semiconductor patterned structures, Fano-resonant antennas, plasmonic metamaterials, resonant nanocavities, etc. Theoretical models and computational simulations will be developed for these structures to describe the electromagnetic behavior as well as to optimize the material systems and devices. The resulting fabrication techniques and modeling methods will lead to new technology for devices that can be tailored for specific detection schemes for optical signal enhancement and detection. It is anticipated that the modeling/fabrication/characterization efforts will be iterative towards the development of a highly sensitive platforms that are robust and wavelength scalable.

SF.45.18.B0002: Engineered Electromagnetic Materials, Metamaterials, Light-Matter Interactions, Subwavelength Photonics

Allen, Jeffery - 850-882-3559

Opportunities exist in fundamental physics of electromagnetic radiation matter interaction and electronic material properties (engineered electromagnetic materials, metamaterials, photonic crystals, band gap materials, semiconductors, 2D and 1D materials, etc.). This will include propagation, mechanisms for absorption and emission, scattering and quantum effects. One focus of the work will be to explore how to control the spatial anisotropic properties of materials or material systems, natural or engineered, to control electromagnetic radiation. Another thrust is the exploration of new analytical, quasi-analytical and homogenization techniques to describe engineered electromagnetic materials so they can be applied to practical devices and systems. This research involves multidisciplinary work in the application of various engineering and scientific disciplines with the purpose of exploration, discovery, and exploitation of basic materials properties to design and control the interaction of electromagnetic waves with matter and electronic properties for multifunctional materials and devices that adapt to varying operating environments. The efforts will include theoretical analysis, design, simulation, fabrication, and testing prototype devices and complex materials. The research will utilize test equipment, optical and microwave simulation software, and fabrication facilities to support these efforts.

SF.45.18.B0001: Heterogeneous Teaming for Target Search and Tracking

Doucette, Emily - (850) 883 - 0874

The utilization of autonomous agents can support mission success in dynamic, uncertain, and contested environments by augmenting human operator capabilities. Specifically, cooperative autonomous systems can provide enhanced situational awareness, which can inform decision support for target search, track, and engagement scenarios. To leverage the full capabilities of autonomous agents in a dynamic and uncertain battlefield, a common framework to update situational awareness between all agents, both human and autonomous, is required. This need for enhanced situational awareness across a team is also challenged by dynamic and uncertain information and communication topologies in decentralized command and control architectures. As such, the bi-directional communication of the uncertainty of information passed between agents and the ability to update one`s own world model is vital to a shared understanding. The goal of this research is to address the aforementioned challenges to enable the synergistic teaming of heterogeneous agents.

SF.45.17.B0001: High-Rate Dynamics & Experimental Methods

Dodson, Jacob - 850-883-1920

Research will involve designing and performing analytical and experimental studies of the time- and frequency-domain response of both simple and complex mechanical systems to high-amplitude, short duration impulsive loads. We are also interested in structural dynamics experimentation, analysis, and/or simulation. Opportunities exist to perform research in the following technical areas:
(1) Microsecond Health Monitoring & Prognosis: cyber-physical estimation, prediction and reaction using the high-rate dynamics of a structure to detect and mitigate damage, and perform prognosis on the remaining usable life. These methods should be able to be implemented on a microsecond time scale.
(2) Novel High Rate Dynamics Experimentation & Instrumentation: development of novel experimental testing methods and instrumentation for evaluating the survivability and response of materials, sensors, electronics, and mechanical interfaces under high-rate dynamic loading;
(3) Harsh Environmental Characterization: development of methods and metrics to characterize the bulk and internal thermo-mechanical environment of a complex mechanical system under impulsive loading;

SF.45.16.B0001: Additive Manufacturing of Multifunctional Materials

Schrand, A. - 850-882-1538

The goal of our team is to develop, demonstrate, and implement additive manufacturing (AM) technologies to rapidly design, prototype, and manufacture critical munitions components such as survivable fuze electronics, reactive structures and energetic materials for modular, flexible weapons. Specific topics of interest include: 1) Increasing lethality of miniaturized weapons, 2) Development of fuze components for small form factor/miniature warhead concepts, 3) Use of alternative processing techniques for explosives and energetic materials, 4) Development of additive manufacturing processes for lightweight, cellular warhead cases and embedded fuze housings and 5) Creation of reactive structural materials that offer strength and also energy on demand. A successful candidate will possess a multidisciplinary experimental background in Materials Science/Engineering, Electrical Engineering, Physics, Chemistry and other relevant Science & Engineering fields with a strong publication record. Candidates with experience in AM design and demonstration preferred.

SF.45.13.B1126: Fundamental Research of Novel Energetic Materials

Lindsay, C.M. - 850-882-1543

The goal of our team is to discover, develop, integrate and transition energetic materials technology that maximizes lethality, survivability and safety for air-delivered munitions. We study the basic processes and scientific phenomena that are necessary to predict, design and characterize energetic materials. A variety of topics are being considered for enhancing the energy density of materials based upon improved reaction rates while maintain stability under ambient storage conditions (ie. Room temperature, humidity). Specific topics of interest include: 1) energetic films via spin casting of fuel-oxidizer blends, 2) light tunable sensitization of energetic materials, 3) self-assembly of thermite-based structural materials, 4) scale up processes such as resonant acoustic mixing and 5) synthesis of energetic nanoparticles using superfluid helium droplet assembly and other techniques. A successful candidate will possess a strong multidisciplinary experimental background in physics, chemistry and materials science/engineering with knowledge of modeling and simulation techniques.


1. Prakash, A., A.V. McCormick, and M.R. Zachariah, Tuning the Reactivity of Energetic Nanoparticles by Creation of a Core−Shell Nanostructure. Nano Letters, 2005. 5(7): p. 1357-1360.

2. Ferrando, R.; Jellinek, J; and Johnston, R.L. Nanoalloys: From Theory to Applications of Alloy Clusters and Nanoparticles. Chem. Rev., 2008, 108 (3), pp 845–910.

3. Heting Li, Mohammed J. Meziani, Fushen Lu, Christopher E. Bunker, Elena A. Guliants and Ya-Ping Sun Templated Synthesis of Aluminum Nanoparticles - A New Route to Stable Energetic Materials. J. Phys. Chem. C, 2009, 113 (48), pp 20539–20542

4. Lei Zhou, Ashish Rai, Nicholas Piekiel, Xiaofei Ma and Michael R. Zachariah

Ion-Mobility Spectrometry of Nickel Nanoparticle Oxidation Kinetics: Application to Energetic Materials. J. Phys. Chem. C, 2008, 112 (42), pp 16209–16218.

5. Rusty W. Conner and Dana D. Dlott. Time-Resolved Spectroscopy of Initiation and Ignition of Flash-Heated Nanoparticle Energetic Materials. J. Phys. Chem. C, 2012, 116 (28), pp 14737–14747.

6. Yong Qin, Yang Yang, Roland Scholz, Eckhard Pippel, Xiaoli Lu, and Mato Knez. Unexpected Oxidation Behavior of Cu Nanoparticles Embedded in Porous Alumina Films Produced by Molecular Layer Deposition. Nano Lett., 2011, 11 (6), pp 2503–2509.

7. William K. Lewis, Barbara A. Harruff, Joseph R. Gord, Andrew T. Rosenberger, Thomas M. Sexton, Elena A. Guliants, and Christopher E. Bunker. Chemical Dynamics of Aluminum Nanoparticles in Ammonium Nitrate and Ammonium Perchlorate Matrices: Enhanced Reactivity of Organically Capped Aluminum. J. Phys. Chem. C, 2011, 115 (1), pp 70–77

Keywords: Energetics, Thermites, Nanoparticles, Energy density, Reactivity

SF.45.13.B0832: Bioinspired Principles for Autonomous Munitions Systems

Dickinson, B.T - (850) 883-2645

Insects utilize a wide range of sensing modalities to achieve robust and agile flight. These modalities are often occur in arrays composed of noisy mechanosensors in numbers of hundreds, thousands, or more; and are distributed over organs or locations of the body according to their function. In contrast, modern guidance, navigation and control designs rely on feedback from local and precise instrumentation such as inertial measurement units, gyroscopes, global positioning systems and pitot tubes. We aim to derive scalable principles from the existing knowledge base surrounding the information processing and sensing modalities of natural flyers to develop fundamental and scalable control methodologies that increase robustness and minimize the human interaction necessary for effective engagement of munitions platforms. This may include, but is not limited to, biologically inspired and derived methodologies for the feedback of munitions attitude, atmospheric turbulence, and wind shear or gusts.

SF.45.08.B6110: High-Rate Ordnance Materials and Structures Research

Flater, Philip - (850) 882-6836

This program focuses on the design, manufacture, test, and evaluation of materials and structures under high strain rate loads, high pressures, and/or high temperatures. Such extreme conditions are typical of the conditions observed in ordnance under high velocity impacts. Therefore, the rate-dependent characterization of ordnance materials is critical in determining the lethality and survivability of weapon systems. This includes the evaluation of the high pressure equation-of-state, stress-strain constitutive behavior, and the fracture/failure of a wide variety of materials. In addition to the characterization of existing materials and structures, an objective is to develop new materials and structures for multi-functional or novel effects. AFRL/RW manufacturing and testing capabilities relevant to this program include polymer and metal additive manufacturing (AM) systems, ballistic impact equipment, low-rate and high-rate mechanical load frames, shock/flyer impact guns, and others. These are complemented with chemical/compositional analysis equipment, high resolution optical and electron microscopes, full-field shape and deformation analysis tools (e.g., 3D scanning and digital image correlation), and time-resolved interferometry systems (e.g. VISAR and PDV). Materials of interest include – but are not limited to – metal alloys, structural reactive materials, bioinspired materials, fiber reinforced composites, and additively manufactured materials.

SF.45.08.B2564: Vision-Based Guidance and Control

Curtis, J.W - (850) 883-2564

Research opportunities are available to explore the intersection of computer vision with the guidance and control of unmanned aerial vehicles and munitions. Vision-based sensors are typically small, lightweight, and inexpensive; these qualities make them well suited for deployment on next-generation unmanned vehicles and weapons. There is a gap in the literature regarding the use of vision-only sensing for terminal guidance and many fruitful lines of research could be opened in order to investigate the limitations and advantages offered by monocular or multicamera sensor platforms. Work is currently in progress that explores the use of visual information to successfully estimate position and attitude; this navigation-specific work might dove-tail nicely with an investigation of vision-based guidance law design. Furthermore, since a visual sensor can be used for both ego-estimation and target relative position and motion, a possibility exists to develop an integrated guidance and control system based primarily on information derived from one or more cameras.

SF.45.03.B5434: Network Optimization and Control

Pasiliao, Eduardo - 850-883-2563

Research is in progress on the cooperative control of air armament designed to detect, identify, and attack ground targets. Although many cooperative system approaches model the uncertainty of the environment, they fail to address risks associated with poorly specified stochastic models of the environment, the adversary, or the cooperating agents. Cooperative agents must optimize "local" objectives that ideally translate into achieving global or collective objectives. Because information gathering and decision-making are distributed, there is considerable uncertainty about the actions of independent team members. It is quite possible that the independent pursuit of local objectives implicitly results in team members taking on adversarial roles as competitors for limited resources or tasks. Components of this research include risk sensitive optimization and risk management techniques such as Conditional Value at Risk, applied to situations where enemy forces are attempting to deceive or destroy friendly forces. Other research components include the development of distributed algorithms for policy generation, with real-time policy updates based on observation or prediction of the behavior of teammates or adversaries.

SF.45.02.B7623: Shock Physics

Neel, C. - 850-882-7992

This research opportunity focuses on the fundamental understanding of shock physics in inert and chemically reacting systems. A persistent need remains in the understanding of material response under shock loading, specifically in the area of high-fidelity experiments and measurements. Emerging “mesoscale” modeling approaches have highlighted shortfalls in the conventional characterization methods treating the materials specimens as continuum, or homogenized fields. Current line VISAR (velocity interferometer system for any reflector), digital image correlation (DIC), and photonic Doppler velocimeter (PDV) for ultrahigh-speed image intensified cameras (IIC) and time-resolve emission spectroscopy are available for this research in quantifying the material states of impact shock-loadings. The research will emphasize new opportunities and capabilities in characterizing (both analytically and experimentally) the mesoscale constituent response of heterogeneous and particular materials. A broad range of material systems are considered for this research, including specific geomaterials and soils to nanoparticle reactive materials capable of rapid self-oxidation, to high-energy explosive compositions. We are interested in the broad range of research topics, which include new equations of state, improvements to existing EOS descriptions and models, improved diagnostics or implementations of existing, and advancing our understanding of the constituent response at mesoscale and how to link that response up through the macro-level responses. This research will rely heavily on the interactions between numerical simulation, experiment, and theory with the primary goal of drawing each to comparable fidelity and common basis of comparison.


Shock; Hugoniot; Equation of state; Detonation; Mesoscale; Interferometry; Particulate mechanics;

SF.45.02.B7604: Detonating Systems Research

Welle, E.J - (850) 883-0581

This research will focus on the understanding of fundamental detonation phenomena. Most conventional explosive models are typically described as composite models, which means they treat a complex reacting flow system with 100 to1000’s of chemical reactions and intermediate material states as having only two. Those two states are joined by a reaction rate rule that governs how energy is liberated by moving between those states. We are conducting research to determine how to resolve such reaction pathways by going from 2 to n-number of states that allow for more useful predictive capabilities. Small scale experiment is being invented or matured to facilitate the measurement of needed material characteristics such as equations-of-state for the unreacted, partially, and fully reacted energetic materials. Typical measurement techniques include dual streak cameras, Photon Doppler Velocimetry, and high-speed imaging that can be resolved to the nanosecond or subnanosecond timescale. The work will also include assessment of conventional hydrocode based reactive flow models to determine their physical relevance to problem sets of interest. The Associate will be able to design and participate in the execution of complex optical experiments, become familiar with conventional reactive flow models, design experiments with modelers, and report work in refereed journals or conferences that are open to the general community or limited based on work content.

Keywords: Detonation; Explosive; Optical diagnostics; Equation of state; Photon Doppler Velocimetry; Shock to detonation; Thin pulse initiation; Explosive microstructure; Laser interferometry

SF.45.02.B7454: Agile Munition Vehicles Sciences

Bartlett, Elizabeth - 850-883-7018

We conduct research on the coupled interaction of fluid, structural, thermal, and material dynamics applicable to high-performance weapon airframes. The research includes multidisciplinary approaches in theoretical, computational, and experimental fluid and structural dynamics, and multifunctional materials. We specifically seek to characterize the fundamental physics dictating the overall vehicle controllability, agility, lethality, and survivability. The products of this research will lay the foundation for development of methodologies and tools to exploit the physics of agile, maneuvering weapon airframes of all size scales and speed regimes applicable to tactical weapons in transition between the three phases of flight: (1) air-launch, (2) in-transit, and (3) terminal (e.g., low Reynolds number micro-scale airframes, air-launched unitary subsonic to supersonic guided bombs, air-launched supersonic to low hypersonic air-intercept, and long-range strike weapons). Research opportunities exist in the characterization, control, and exploitation of aero, structural, thermal, and material dynamics that enhance munitions operational capability. Keywords: Fluid dynamics; Structural dynamics; Thermal dynamics; Computational fluid dynamics; Aeroelasticity; Aerothermodynamics

SF.45.02.B7106: Meso-structure – Property – Performance Relationships in Energetic Materials

Molek, Christopher - 850 882-9244

The loading and performance requirements on energetic materials for Air Force applications are becoming increasingly severe. Understanding of the processing – structure – property – performance relationships, particularly at the meso-scale, is critical to enable the design and use of energetic materials. Several research areas are required to develop this topic experimentally, theoretically, and computationally: non-shock and shock initiation and growth of reaction/detonation; microstructural quantification and analysis, particularly of damage; material design and formulation to enhance performance and insensitivity/survivability; pressure-strain rate-temperature dependent material properties, namely of polymers, particulate composites, and energetic materials.

SF.45.01.B5483: Efficient Processing of Optimally Sampled 2-D and 3-D Imagery

Rummelt, N.I - (850) 883-0886

The hexagonal grid and the body-centered cubic (BCC) lattice are the optimal sampling lattices for isotropically band-limited 2-D and 3-D signals, respectively. These lattices provide significant improvements in sampling efficiency over traditional rectangular sampling but have not been commonly used due to inefficiencies related to their non-Cartesian nature. A recent advance in addressing such lattices promises to overcome the inefficiencies and allow for the use of these optimal sampling approaches for common image processing applications. Research is being conducted that aims to take advantage of the improved sampling efficiency of these lattices to provide significant improvements in various areas of signal processing. Research opportunities exist in the development of fundamental techniques in processing optimally sampled imagery that lead to demonstrable improvements over current state-of-the-art approaches.


Dr. Montaigne, Didier
Assistant to the (RW) Chief Scientist
101 W Eglin Blvd
Eglin AFB, Florida 32542
Telephone: 850-217-9342
Email: didier.montaigne@us.af.mil