FOA-AFRL-AFOSR-2021-0007 - DEPSCOR - Research Collaboration AMD 2.docx

AIR FORCE OFFICE OF SCIENTIFIC RESEARCH

FUNDING OPPORTUNITY ANNOUNCEMENT

# FOA-AFRL-AFOSR-2021-0007

FY21 DEFENSE ESTABLISHED PROGRAM TO STIMULATE COMPETITIVE RESEARCH (DEPSCoR) –

RESEARCH COLLABORATION (RC)

OVERVIEW INFORMATION

The Department of Defense (DoD) announces the fiscal year 2021 (FY21) Defense Established Program to Stimulate Competitive Research (DEPSCoR) – Research Collaboration (RC). The program is sponsored and managed by the Basic Research Office, Office of the Under Secretary of Defense for Research and Engineering (OUSD [R&E]), awarded by the Air Force Office of Scientific Research (AFOSR), and administered through the Office of Naval Research (ONR). The DoD plans to award FY21 DEPSCoR appropriations through this announcement.

DEPSCoR's objectives are to: (1) increase the number of university researchers in eligible States/Territories capable of performing S&E research responsive to the needs of the DoD; and (2) enhance the capabilities of institutions of higher education (IHE) in eligible States/Territories (listed below) to develop, plan, and execute science and engineering (S&E) research that is relevant to the mission of the DoD, and competitive under the peer-review systems used for awarding Federal research assistance; (3) increase the probability of long-term growth in the competitively awarded financial assistance that IHE in eligible States receive from the Federal Government for S&E research.

Consistent with these longterm objectives of building research infrastructure, the DoD intends to competitively make, and fund from fiscal year 2021 appropriations, multiyear awards for S&E research in areas relevant to the DoD’s mission and important to national security.

This funding opportunity aims to create basic research collaborations between a pair of researchers, namely 1) Applicant/Principal Investigator (PI), henceforth referred to as Applicant, a full-time faculty member who has never served as a PI on a prior DoD directly funded research Prime award and 2) Collaborator/co-Principal Investigator (co-PI), henceforth referred to as Collaborator, an investigator who will provide mentorship to the Applicant and has served as a PI on a DoD directly funded research Prime award actively between 1 October 2014 and 30 September 2021. This structure is aimed at introducing potential applicants to the DoD’s unique research challenges and its supportive research ecosystem.

Prime award defined in the context of this announcement is the DoD legal instrument (assistance or acquisition) that a Principal Investigator receives directly from a DoD awarding agency and not indirectly from a non-DoD pass-through entity to carry out scientific research.

· You are eligible to apply as the Applicant under the DEPSCoR-RC FOA as long as you were NOT listed as the Principal Investigator on a previous DoD funded research award, and are a full-time faculty member in a tenured or tenure track position in a DEPSCoR eligible State/Territory. Being a “Co-PI” or “sub PI” on a prior DoD funded award does not count as being a “PI” for the purposes of eligibility of the Applicant for the DEPSCoR-RC FOA.

· The DEPSCoR-RC white paper package must include prior research award documentation which indicates that the Collaborator was a PI on a previous DoD directly funded research Prime award between 1 October 2014 and 30 September 2021. If the Collaborator is not identified as the PI within the award document, a letter from the awarding agency point of contact should be furnished supporting the assertion within the timeframe identified.

· The Collaborator must have served as a Principal Investigator on a directly funded DoD research Prime award during the eligibility period and not have been subcontracted by: other PIs, non-DoD entities, or companies as a Co-Principal Investigator. Subawards indirectly funded by the DoD where the Collaborator has served as a Co-Principal Investigator do not count as eligible criteria for the Collaborator for the purposes of this funding opportunity announcement.

· The flow charts below serve as a guide for determining Applicant and Collaborator eligibility. Each diamond shape is an eligibility criterion question which elicits either a “yes” or “no” response. You are not eligible to submit a White Paper or proposal if any “yes” or “no” response leads to the “Not eligible” outcome. Submissions found to be “Not eligible” will not be subject to technical review. You are not eligible to submit a White Paper or proposal if you do not meet this requirement.

Tenured or tenure-track faculty members with appointments at IHE, in the following States/Territories are eligible to apply for DEPSCoR opportunities under this announcement: Alabama, Alaska, Arizona, Arkansas, Connecticut, Delaware, District of Columbia, Guam, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Mexico, North Dakota, Oklahoma, Oregon, Puerto Rico, Rhode Island, South Carolina, South Dakota, Tennessee, U.S. Virgin Islands, Vermont, West Virginia, Wisconsin, and Wyoming.

Hyperlinks have been embedded within this document and appear as underlined, and blue-colored words in the midst of paragraphs. The reader may “jump” to the linked section within this document by “clicking” (CTRL + CLICK, or CLICK).

SUMMARY OF FUNDING OPPORTUNITY INFORMATION

1. FEDERAL AWARDING AGENCY NAME

Air Force Office of Scientific Research 875 North Randolph Street, STE 325, Room 3112 Arlington, VA 22203

2. FUNDING OPPORTUNITY TITLE

Defense Established Program to Stimulate Competitive Research (DEPSCoR) – Research Collaboration (RC)

3. ANNOUNCEMENT TYPE

Initial Funding Opportunity Announcement (FOA)

4. FUNDING OPPORTUNITY NUMBER

FOA-AFRL-AFOSR-2021-0007

5. CATALOG OF FEDERAL DOMESTIC ASSISTANCE (CFDA)

NUMBER(S)

12.431 – Basic Scientific Research

6. KEY DATES

Schedule of Events

nVision Registration (strongly suggested by) Cut-off date for Q&As with Program Officers

White Paper and Supporting Documentation submission on nVision website (https://dod-basicresearch.nvision.noblis.org/program/depscor) (required by) Monday, 20 September 2021 Monday, 27 September 2021 as of AMD 2 to the FOA

NLT 11:59PM

Request for written feedback on your white paper submission (required by) (Email request to: DEPSCoR-feedback@noblis.org Notification email will provide instructions for requesting feedback) Friday, 10 December 2021

NLT 11:59PM

Full Proposal Submission (by invitation only) electronically on Grants.gov website (submitted by)

Table of Contents

PROGRAM DESCRIPTION

OBJECTIVES

The aim of DEPSCoR is to improve the research capabilities at institutions of higher education (IHE) in eligible States/Territories to perform competitive basic research in science and engineering that is relevant to the DoD mission and reflect national security priorities. As defined in the DoD Financial Management Regulation:

Basic research is systematic study directed toward greater knowledge or understanding of the fundamental aspects of phenomena and of observable facts without specific applications towards processes or products in mind. It includes all scientific study and experimentation directed toward increasing fundamental knowledge and understanding in those fields of the physical, engineering, environmental, and life sciences related to long-term national security needs. It is farsighted high payoff research that provides the basis for technological progress (DoD 7000.14-R, vol. 2B, chap. 5, para. 050105.A).

The DoD’s basic research program invests broadly in many scientific fields to ensure that it has early cognizance of new scientific knowledge.

To address the program’s aim, DEPSCoR will focus on capacity building through human and technical resources by soliciting applications in a DEPSCoR – Research Collaboration (RC) competition. DEPSCoR – RC seeks proposals that advance knowledge in basic science involving bold and ambitious research that may lead to extraordinary outcomes such as disrupting accepted theories and perspectives.

Authority for a grant award under this announcement is established in 10 U.S.C. 2358 for basic research. Authority for DEPSCoR specifically was established in the National Defense Authorization Act for Fiscal Year 1995, and has subsequently been amended and reauthorized over the years since (see also a specific note within 10 U.S.C. 2358 referring to DEPSCoR).

COLLABORATION COMPOSITION

This funding opportunity aims to create basic research collaborations between a pair of researchers, namely 1) Applicant/Principal Investigator (PI), henceforth referred to as Applicant, a full-time faculty member who has never served as a PI on a prior DoD directly funded research Prime award and 2) Collaborator/co-Principal Investigator (co-PI), henceforth referred to as Collaborator, an investigator who will provide mentorship to the Applicant and has served as a PI on a DoD directly funded research Prime award actively between 1 October 2014 and 30 September 2021. This structure is aimed at introducing potential applicants to the DoD’s unique research challenges and its supportive research ecosystem.

Applicants must be aware of the following eligibility criteria:

· You are eligible to apply as the Applicant under the DEPSCoR-RC FOA as long as you were NOT listed as the Principal Investigator on a previous DoD funded research award, and are a full-time faculty member in a tenured or tenure track position in a DEPSCoR eligible State/Territory. Being a “Co-PI” or “sub PI” on a prior DoD funded award does not count as being a “PI” for the purposes of eligibility of the Applicant for the DEPSCoR-RC FOA.

· The DEPSCoR-RC white paper package must include prior research award documentation which indicates that the Collaborator was a PI on a previous DoD directly funded research Prime award between 1 October 2014 and 30 September 2021. If the Collaborator is not identified as the PI within the award document, a letter from the awarding agency point of contact should be furnished supporting the assertion within the timeframe identified.

· The Collaborator must have served as a Principal Investigator on a directly funded DoD research Prime award during the eligibility period and not have been subcontracted by: other PIs, non-DoD entities, or companies as a Co-Principal Investigator. Subawards indirectly funded by the DoD where the Collaborator has served as a Co-Principal Investigator do not count as eligible criteria for the Collaborator for the purposes of this funding opportunity announcement.

· The flow charts below serve as a guide for determining Applicant and Collaborator eligibility. Each diamond shape is an eligibility criterion question which elicits either a “yes” or “no” response. You are not eligible to submit a White Paper or proposal if any “yes” or “no” response leads to the “Not eligible” outcome. Submissions found to be “Not eligible” will not be subject to technical review. You are not eligible to submit a White Paper or proposal if you do not meet this requirement.

The Applicant is permitted to submit only one DEPSCoR-RC White Paper per this DEPSCoR-RC FOA. Each white paper is permitted a single Applicant and a single Collaborator.

Collaborators are allowed to work with more than one Applicant and thus aren't restricted from participating in more than one white paper. However, please note it is expected that Collaborators serve as a vital component of the proposed team and commit to providing time for research collaboration and mentorship throughout the entire process.

The website https://discover.dtic.mil/products-services/ is a non-comprehensive repository of government-funded scientific, technical, and engineering information for the DoD. Researchers and Applicants new to DoD are encouraged to visit the site as a starting point for identifying past and present DoD-funded researchers.

The Basic Research Office has also established a “Connect and Collaborate” site where prospective Applicants and Collaborators, seeking collaboration in this DEPSCoR opportunity can post their interest. Please see (https://dod-basicresearch.nvision.noblis.org/program/depscor) for more information. Posting your interest is NOT a requirement.

While each member of the collaboration should be in a tenure-track appointment or tenured at IHE in DEPSCoR-eligible States/Territories, you do not need to be in the same State/Territory. Likewise, the Applicant and Collaborator can have appointments at the same IHE.

Proposals should name the Applicant as the PI and their IHE as the primary institution. Awards will be issued to the IHE where the Applicant resides. It is anticipated but not a requirement that the Collaborator will be funded through a sub-award. The Applicant IHE must receive greater than 50% of the funding. The relationship among participating institutions and their respective roles, as well as the apportionment of funds including sub-awards, if any, shall be described in both the proposal text and the budget. All key personnel proposed must hold appointments at an IHE in a DEPSCoR eligible state. In addition to providing technical expertise to the project, the Collaborator is strongly encouraged to provide guidance and mentorship to the Applicant in the DoD application process.

In this announcement, the term “you/your” refers to the Applicant.

TOPICS

The FY21 DEPSCoR – Research Collaboration competition seeks proposals addressing the topics listed below. You are strongly encouraged to contact the Topic Area Program Officer prior to submitting a white paper, preferably by email to discuss the current state of the art in his/her area of interest and how your research would advance it. This information will be requested in the IV.C.4 White Paper Package.

ONR

Topic 1: Physics of Sensing

Program Description: This portfolio seeks to understand the fundamental scientific limits of sensing and to develop revolutionary concepts for detection with improved accuracy, sensitivity, and robustness. The research spans experimental, theoretical, and computational studies. Although the principal domain of activity focuses on the electromagnetic spectrum, the areas of interest to the Air Force and Space Force are broad and include chemical and gravitational measurements. We seek to expand the basic physical understanding in propagation of electromagnetic radiation, interactions of radiation with matter, image formation, sensor tasking, data fusion, remote object detection and identification, and the effects of the atmosphere or space environment on sensing systems. Proposals are sought in all areas of ground-, air-, and space-based sensing with applications in tracking, detecting, and characterizing. Fundamental understanding which leads to development of sensors of higher sensitivity or smaller cost or form factor is of relevance. Passive and active sensing methods, particularly multimodal detection and multifunctional sensors, are of interest.

Basic Research Objectives: Research goals include, but are not limited to:

Researching detection phenomena and the physics of ideal and real sensor systems including multimodal, hyperspectral, and hypertemporal, sensors.

Discovering fundamental limits to restrictions such as limited aperture size, time of day, and imperfections in the optics, and techniques to approach or circumvent these limitations.

Understanding irregularities in the optical path including imaging though obscured, degraded, and non-line of sight conditions and developing novel methods for imaging in these conditions.

Creating new materials, systems, and techniques to approach the fundamental detection limits.

Characterizing propagation of coherent and incoherent electromagnetic radiation through a turbulent atmosphere.

Developing experimental methods and models to describe the spectral, thermal, and polarimetric signature from objects of interest.

Understanding and predicting dynamics of space objects as it relates to identification and space domain awareness.

Innovating techniques for on-orbit characterization, including radiation tolerant optical and non-optical sensors such as electrostatic field measurements, accelerometers and radiation dosimeters.

DR. MICHAEL YAKES, AFOSR/RTB1

Email: remote.sensing@us.af.mil

(703) 696-8427

Topic 2: Space Propulsion and Power

Program Description: Research activities are focused as multi-disciplinary, multi- physics, multi-scale approach to complex problems, and fall into four areas: Coupled Material and Plasma Processes far from Equilibrium, Nano-energetics in solid propellant combustion, High Pressure Combustion Dynamics in rocket engines, and structural batteries.

Basic Research Objectives: Research in the first area is to significantly advance the state-of-the-art in our ability to understand the fundamental aspects of a coupled plasma/material system in non-equilibrium states, for a variety of potential applications, including plasma-based space propulsion systems and plasma-spacecraft interactions. The typical conditions of interest are characterized by critical phenomena in small spatial and temporal scales which affect the behavior over a much wider range of scales. Detailed understanding and control of non-equilibrium and multiscale effects have the potential to overcome the limitations of traditional plasma in thermodynamic equilibrium, leading to improved system designs; preventing or leveraging dynamic features such as instabilities, coherent structures, and turbulence; and realizing chemical pathways, structural changes or electromagnetic processes for novel devices with unprecedented level of control. Research interest also includes the use of data-driven methods to generate dynamic databases for accurate, and efficient computational predictions. For Very low Earth Orbit, research is needed to identify and assess the suitability of new electric propulsion candidates that may make use of large amounts of beamed energy and the harvesting of air as a propellant. Concepts may include pulsed and/or continuous (steady-state) electric propulsion schemes that include understanding issues associated with efficient collection, conditioning, ionization, and subsequent acceleration of air to produce thrust at a sufficient specific impulse needed to maintain orbit. The potential use of beam energy introduces the possibility of directly coupling the beamed energy into ablative thrusters, or air flows for ionization to produce plasma ejections and thrust.

Research in the second area focuses on smart, functional Nano-energetics for propulsion purposes only. There has been tremendous progress in the synthesis and fabrication of Nano-sized reactive materials. With significant advances in quantum chemistry and molecular dynamics over the last decade, as well as a broader understanding of the properties of nanomaterials, it may now be feasible to design a priori nanostructured reactive materials according to desired performance objectives and including controlling mechanisms at the nanoscopic and microscopic scale. Instead of being subject to uncontrolled combustion, smart Nano-energetics may be activated by external electromagnetic stimuli, such as an electrical field or light. For example, it may be desirable to initiate a reaction at a particular temperature, to release a particular compound at a particular temperature, to turn on or turn off a reaction, have tailored ignition properties, to achieve extinguishment of a propellant, or to accelerate or slow a reaction with time or location.

Research in the third area would allow the Air Force and Space Force to capitalize on the higher efficiencies, and increased performance options made possible by taking rocket and other propulsion systems to increasingly high pressures. As this necessarily pushes materials and structures to correspondingly extreme limits, it becomes essential to take into consideration the dynamics of combustion processes, as higher pressures lead to increased amplitudes of fluid-dynamic and thermochemical events and fluctuations, in a wider spectrum of time scales. Mathematical and experimental analysis of these dynamics at higher levels of fidelity also lead to a "big data" problem. It becomes necessary to combine and dynamically integrate multi-fidelity simulations and experimental measurements or monitoring, with the goal of systematically performing modeling, analytics, statistics, and dynamic data driven validation for chemical propulsion.

Research in the fourth area aims to combine both electrochemical and mechanical functionalities in a single unit in which energy storage can be accomplished by materials and structures that simultaneously manage mechanical stress, including peak values encountered during launch.

DR. MITAT A. BIRKAN, AFOSR/RTA1

Email: space.power@us.af.mil

(703) 696-7234

Topic 3: Complex Networks Program Description: Complex networks are pervasive in military, commercial, and civilian operations. Complex networks consist of a graph (directed or undirected) together with a set of attributes. These attributes can include scalar or multi-dimensional weights on the edges or nodes of the graph, topological characteristics of the graph, flows over the graph, and processes that define the dynamics of the graph. Complex networks cut across many scientific disciplines (e.g., mathematics, computer science, engineering, socio-economics, etc.) and many application domains (e.g., communications, sensing, information systems, transportation, etc.). Networks fundamentally describe the structural aspects of interactions between individual agents. Networks can be extremely large and can have multiple characteristic scales. They can be static or dynamic. They can be physical or virtual. Networks can consist of multiple heterogeneous subnetworks (i.e., a network- of-networks), with explicit and implicit interdependencies. For example, transportation networks are intimately coupled to computer and electrical-power networks. Thus, the failure of a critical node or arc in one network can trigger failures in another, which can create a cascade event with catastrophic consequences. All of these characteristics of networks can make the analysis, understanding, and utilization of networks difficult and computationally prohibitive.

This basic-research program is focused on developing fundamental mathematical and algorithmic techniques to design, analyze, utilize, and understand complex networks. The program seeks innovative approaches with far-reaching potential, meaning any mathematical and algorithmic approaches ideally should be applicable to broad classes of problems and not tied to a particular application domain. The networks of interest can have arbitrary topologies, can be static or dynamic, and can be subject to uncertain conditions, ranging from a stochastic environment to deliberate adversarial actions affecting both nodes and links.

Basic Research Objectives: This program is aimed at developing mathematical and algorithmic tools for the design, analysis, understanding, and utilization of complex networks. Problems of interest include, but are not limited to:

Network resilience and robustness: This includes techniques for defining and measuring the resilience of a dynamic network; techniques for predicting, identifying, and mitigating adversarial actions against a network; techniques for network interdiction.

Network analytics: This includes algorithmic techniques for solving important classes of problems on networks, such as optimal resource allocation and information dissemination; algorithmic techniques for inference problems on networks that extract global information about network structure and function from local information. The algorithms can be exact or approximate with performance guarantees. Of particular interest are decentralized algorithms and understanding the tradeoff between centralization and decentralization.

Complexity reduction of networks: This includes techniques for decomposition, sparsification, and dimensionality reduction of networks with the goal of making networks easier to analyze, understand, and visualize; techniques for analyzing and exploiting graph-theoretic structure such as multi-layer networks.

Extension of network-analysis techniques to more general combinatorial, algebraic, or analytical structures: This includes network-relevant research in submodular functions, hypergraphs, matroids, graphons, etc.

Approaches may draw upon, but are not limited to, techniques from graph theory, optimization, complexity theory, algorithmic game theory, combinatorics, linear algebra, statistics, and probability.

DR. DONALD K. WAGNER, AFOSR/RTA2

Email: complex-networks@us.af.mil

(703) 696-9705

Topic 4: Atomic and Molecular Physics

Program Description: This program encompasses fundamental experimental and theoretical Atomic and Molecular Physics research that is primarily focused on studies of cold and ultra-cold quantum gases, precision measurement, matter-wave optics, and non-equilibrium quantum dynamics. These research areas support technological advances in application areas of interest to the U.S. Air and Space Force, including precision navigation, timekeeping, remote sensing, metrology, and novel materials for the U.S. Air and Space Force needs in the future.

Basic Research Objectives: AMO (Atomic, Molecular, and Optical) physics today offers an unprecedented level of coherent control and manipulation of atoms and molecules and their interactions, allowing for significant scientific advances in the areas of cold and ultra-cold matter and precision measurement. Specific research topics of interest in this program include, but are not limited to, the following: physics of quantum degenerate atomic and molecular gases; precision control techniques; strongly-interacting quantum particles; new quantum phases of matter; non-equilibrium dynamics of cold quantum particles; ultra-cold chemistry; precision spectroscopy; and high-precision techniques for navigation, guidance, and remote sensing.

DR. BOYAN TABAKOV, AFOSR/RTB1

Email: amphysics@us.af.mil

(703) 696-9518

Topic 5: Modeling of Complex Systems

The Modeling of Complex Systems Program is a program of fundamental mathematic oriented research, the broad objectives of which are twofold. First, the program seeks to develop and analyze new, innovative, and robust modeling frameworks that may be adapted and generally applied across a variety of disciplines. The second goal is to develop both quantitative and qualitative models of specific complex phenomena in areas in which current models are either not fully based on first/basic principles or are based on empirical and ad hoc metrics for which the first/basic principles are not yet well known. Although they break down into more specific research directions, the three thrust areas of interest to the Modeling of Complex Systems Program are 1) development and analysis of new, general modeling frameworks; 2) geometric and topological modeling – which can be further broken down into more specific thrust areas, as noted below – and; 3) small and large group social modeling and social informatics.

Metrics – in the general, non-mathematical sense of the word – are a natural part of the mathematical modeling framework. Traditional metrics, when they exist, often do not measure the characteristics in which observers in general and the Army in particular are interested. For many complex phenomena, new metrics need to be developed at the same time as new models. As is the case for the modeling effort, these metrics should preferably be in a complete mathematical analytical framework, which is to say, in part, that they should derive from the problem in question as opposed to a situation in which one forces the model to fit an a priori chosen metric. The research in modeling of complex phenomena supported by the Modeling of Complex Systems Program is primarily mathematical analysis and not numerical analysis or computational mathematics. One expects computation to play some role in any modeling endeavor, but the innovation in research carried out in the Modeling of Complex Systems program should be largely in the areas of modeling and analysis, and not in the computational techniques.

Furthermore, any modeling research effort that could be of benefit to military or intelligence applications but that might not fall directly under one or more of the program thrust areas will still be considered, particularly if the innovation in the modeling and analysis are significant and noteworthy.

The three major areas of research of the Modeling of Complex Systems Program are:

Modeling Frameworks and Analysis. Mathematical and physical modeling is fundamental to nearly every other direction of research in the physical, social, and computational sciences. A common element of modeling – even if the phenomenon in question is highly complex – is to incorporate simplifying assumptions that sacrifice realistic application and utility for computational ability. For Army and DoD applications, however, such simplifications often render the model impractical. Modeling frameworks are desired that are able to eschew the usual computational simplification assumptions and realistically capture, adequately govern and/or control, and effectively operate within the particular complexities of real world environments and phenomena, while still maintaining some degree of computational tractability. Of specific interest are causal and predictive modeling frameworks, hybrid model frameworks that capture both causal and predictive features, statistical modeling frameworks, and abstract categorical models (cf. Homotopy Type Theory). Models of particular complex systems that address and are to be utilized for more specific purposes and objectives will be assessed within the context of one of the program’s other modeling thrust areas described below. Research carried out under this section should address the general theory and analysis of mathematical modeling from a broader perspective.

Geometric and Topological Modeling. Representation of complex, irregular geometric objects and complicated, often high-dimensional, abstract phenomena, functions, and processes is fundamental for Army, DoD, and civilian needs. Such needs arise in the modeling of urban and natural terrain, geophysical features, biological objects (e.g. human brain mapping), information flow, and many other contexts. Any research that incorporates an innovative geometric and/or topological approach to address a problem with military, defense, and intelligence applications is welcome and will be considered, but there are two specific threads that are of particular interest to this thrust of the program: 1) geometric data analysis, and 2) multiscale geometric modeling, including dynamics and physical modeling on domains with fine, complex, geometric and/or topological structure.

Geometric data analysis includes – among other subfields – topological data analysis, subspace analysis, principal component analysis, and dimension reduction techniques. Current research directions of importance to Army applications include video, audio, and image processing (i.e. mathematical signal analysis), fast and accurate face/object recognition (i.e., reconstructing and matching geometric data through queries over a database), geometrically motivated methods and structures for working effectively with large – and often real-time extracted – data sets that may be corrupted in some way (e.g. missing or distorted data), and the application of persistent homology in the detection and classification of signals by shape. For instance, although good progress has been made in this direction, real-time capture, representation, and visual reproduction of 3D terrain – not just as a height field but with multivalent height functions and clearly defined topological obstructions – obtained directly from real-time or stored point-cloud data cannot be fully achieved with current techniques like the multitude of variations of piecewise planar surfaces that are presently studied. New approximation theory that does not require the classical assumptions – primarily smoothness – and that provides structure for the many new non-smooth approximation techniques currently under investigation is required. Concurrently, research on the metrics by which we measure and evaluate the approximation is needed.

Additionally, approximation theory for information flow and other abstract phenomena in large wireless communication, sensor and social networks is also of interest. The approximation theory developed under support of this program is expected to provide building blocks for computational geometry, pattern recognition, automatic target recognition, visualization systems, information processing and network information flow.

Multiscale geometric modeling, analysis, and dynamics are of particular interest, both in the context of models of physical phenomena over real-world terrain and in the aforementioned complex, high-dimensional data structures. Models that make use of self-similar structures and recursively defined spaces (e.g. fractals, solenoids, etc.) would be of great interest in adapting or enhancing current techniques in areas such as data mining, fluid and heat flow, and search, evasion, deployment, and maneuver over complex terrain that exhibits self-similar properties (e.g. urban or mountainous terrain). Current techniques for dealing with complex dynamical processes and large, noisy, and possibly corrupted data sets could be greatly improved in both the time and efficiency realms by employing techniques from scale symmetry, which often allows one to reduce a large and unwieldy number of variables to a more manageable problem if the variables are appropriately scaled. Models that adapt self-similarity and automata theory, in particular, can oftentimes lead to mapping complex dynamical systems problems into an algebraic and/or topological category, which then may allow for entirely new tools and approaches to be used. Homotopy Type Theory and its applications are such an area that is of significant interest in military applications.

Small and Large Group Social Modeling. Both qualitative and quantitative analytical models of social group dynamics and information flow are required for operations, training, simulation (computer generated forces) and mission planning, as well as real-time analysis, processing, and dissemination of information. Current models have limited accuracy. Research focused on mathematically justified, practically useful, computationally tractable and data-tractable models is needed. (“Data-tractable” means “does not require more data or more detailed data than is realistically likely to be available.”). Research on the metrics in which the accuracy of the models should be measured is also vitally important.

The broad term for this research pursuit would be social informatics, which is an important area in which more significant progress is needed, especially in the military and intelligence realms. Social informatics, briefly, is the study of the role played in society by information-based technology. This includes examinations of how the spread of information through technology effects social and organizational changes in society, as well as the converse – how social organization of information and use of technology to spread information are affected by social structures and practices. Modeling of the flow, dissemination, and possible evolution of belief systems and cultural factors through physical group migration or through social networking is an important tool in being able to predict where social and military issues might arise in the world. This could lead to better preparation and the avoidance of “caught-off-guard” situations in global politics and military affairs.

Included within the social informatics realm are narrower but equally important research directions. These would include – but not be limited to – the dynamics of information flow across physical groups of people as well as social/technological networks, pattern detection in information flow and language, which would lead to more efficient surveillance and pre-emptive threat detection, as well as security in information transmission. In this latter direction, new and unique data structures and encryption techniques would be hugely beneficial. Complex but tractable multiscale data structures and viable fractal or self-similar encryption techniques – which heretofore have proved to be of academic but not very practical interest – are just a few examples of many that could prove useful.

Paralleling the pursuit of social informatics, information flow analysis, and pattern recognition in information and data is the quickly developing field of deep machine learning. The Army is particularly interested in developing programming models and training algorithms that can automate as much of these processes as possible. This involves a great deal of research into pattern recognition and data analysis, as well as model analysis. The interplay between causal, data-based models and predictive modeling are of special interest and an active area of military research.

DR. RAD BALU

Email: radhakrishnan.balu.civ@army.mil

(301) 233-5292

Topic 6: Biomathematics

The introduction of Biomathematics as a separate area of basic research recognizes the importance and specialized nature of quantitative methods, specifically mechanistic modeling, in the biological sciences. Biology involves a large number of entities that interact with each other and their environment in complex ways and at multiple scales.

This complexity makes biomathematics a highly interdisciplinary field that requires unique and highly specialized mathematical competencies to quantify structure in these relationships. In fact, progress in mathematical models of biological systems has traditionally been achieved by making convenient simplifications; major advances in Biomathematics research continue to require removing these assumptions (for example, stationarity, ergodicity and deterministic nature) and finding ways to effectively model the essential complexity. Modeling techniques currently utilized in the field range from agent-based approaches for determining the results of individual behavior, whether those individuals be molecules, zooplankton, or humans, to multi-compartmental modeling in physiology, epidemiology and neurobiology, to network models involved in understanding ecosystem and human social dynamics, as well as encompassing both deterministic and stochastic approaches. Research in control techniques is also valuable for its potential application in militarily important areas such as bio warfare and disease spread. Exciting new opportunities to advance the field are found in high risk attempts to develop modeling techniques in areas of mathematics, such as algebra and topology, not traditionally brought to bear on biological problems, advances in Bayesian statistics, a growing recognition that the diffusion approximation is not necessarily adequate for many systems, and the availability of large amounts of complex biological data.

The ultimate goal of the Biomathematics Program focuses on adapting existing mathematics and creating new mathematical techniques to uncover fundamental relationships in biology, spanning different biological systems as well as multiple spatial and temporal scales. One area of special interest to the Program is Neuromathematics, the mechanistic mathematical modeling of neural processes. Recent advances in neuroscience provide important foundations to begin understanding how the brain works. Combined with experimental data, innovative mathematical modeling provides an unparalleled opportunity to gain a revolutionary new understanding of brain physiology, cognition (including sensory processing, attention, decision-making, etc.), and neurological disease. With this new understanding, improved soldier performance, as well as treatments for Post-Traumatic Stress Disorder, Traumatic Brain Injury, and other brain-related disorders suffered by the warfighter will be able to be achieved more effectively, efficiently, and ethically than via experimentation alone.

Thrust areas of the Biomathematics Program are as follows:

Fundamental Laws of Biology. The field of physics has long been “mathematized” so that fundamental principles such as Newton’s Laws are not considered the application of mathematics to physics but physics itself. The field of biology is far behind physics in this respect; a similar process of mathematization is a basic and high-risk goal of the ARO Biomathematics Program. The identification and mathematical formulation of the fundamental principles of biological structure, function, and development applying across systems and scales will not only revolutionize the field of biology but will motivate the creation of new mathematics that will contribute in as-yet-unforeseen ways to biology and the field of mathematics itself.

Multiscale Modeling/Inverse Problems. Biological systems function through diversity, with large scale function emerging from the collective behavior of smaller scale heterogeneous elements. This “forward” problem includes creating mechanistic mathematical models at different biological scales and synchronizing their connections from one level of organization to another, as well as an important sub problem, how to represent the heterogeneity of individual elements and how much heterogeneity to include in the model. For example, the currently increasing ability to generate large volumes of molecular data provides a significant opportunity for biomathematical modelers to develop advanced analytical procedures to elucidate the fundamental principles by which genes, proteins, cells, etc., are integrated and function as systems through the use of innovative mathematical and statistical techniques. The task is complicated by the fact that data collection methods are noisy, many biological mechanisms are not well understood, and, somewhat ironically, large volumes of data tend to obscure meaningful relationships. However, traditionally “pure” mathematical fields such as differential geometry, algebra and topology, integration of Bayesian statistical methods with mathematical methods, and the new field of topological data analysis, among others, show promise in approaching these problems. Solutions to these types of multiscale problems will elucidate the connection, for example, of stem cells to tissue and organ development or of disease processes within the human body to the behavior of epidemics.

The “inverse” problem is just as important as the forward problem. From an understanding of the overall behavior of a system, is it possible to determine the nature of the individual elements? For example, from knowledge of cell signaling, can we go back and retrieve information about the cell? Although inverse problems have been studied for a long time, significant progress has been elusive. This thrust area involves innovations in spatial and/or temporal modeling of multi-level biological elements with the goal of achieving a deeper understanding of biological systems and eventually connecting top-down (data-driven) and bottom-up (model-based) approaches.

Modeling at Intermediate Timescales. Biological processes operate at a variety of timescales; understanding the dynamics of a system at intermediate timescales, as opposed to its long term, asymptotic behavior, is critically important in biology, more so than in many other fields. For example, an epidemic is a necessarily transient phenomenon. In addition, deterministic models are an approximation that often is not good enough to be informative about the system. Yet, intermediate timescales of nonlinear dynamics with stochasticity, both internal and external, are not well understood. This thrust area attempts to fill the gap in the basic understanding of modeling of systems, as well as their control, at intermediate timescales.

DR. VIRGINIA PASOUR

Email: virginia.b.pasour.civ@army.mil

(919) 602-8348

Topic 7: Solid Mechanics

The Solid Mechanics Program supports investigations of the behavior of material systems under extreme high loading and loading rate events, such as impact and blast, repetitive loading, temperature and pressure extremes, and prolonged operation. Development of new computational and experimental techniques and enhanced understanding of the physical processes taking place during deformation, fracture initiation, and failure are sought.

Advances in computational techniques should aim to connect phenomena occurring at different spatial and/or temporal scales, substantially improve efficiency and/or accuracy of predictions, integrate new physical relationships, apply a novel approach to studying a physical process, or expand the range of conditions at which processes can be studied. Development of experimental methods that can validate new models or visualize stress fields in complex situations are also of interest.

Maximizing strength and damage tolerance while minimizing weight and cost are key considerations for the development of new material systems; therefore, studies of all material types will be considered, and novel composites, geometries, and bioinspired structures are particularly encouraged. The effects of structure, geometry, composition, defects, and bonding across interfaces on the damage propagation across a material system are of interest.

DR. DENISE C. FORD

Email: denise.c.ford2.civ@army.mil

(919) 549-4244

Topic 8: Environmental Chemistry

The Environmental Chemistry program seeks to provide a more complete and practical understanding of transport, degradation, and transformation for chemicals and compounds of interest. The goal of the research is to develop theories that comprehensively account for the interdependent nature of heterogeneous environments. The program will identify fundamental research opportunities in two main thrusts: (i) Chemical structure and reactivity in multiphase environments; and (ii) Novel techniques for detection and prediction.

Chemical structure and reactivity in multiphase environments aims to determine the properties and processes that govern the fate and transport of compounds in environments where chemical reactions and transport processes occur between solid, liquid, and gaseous matter. Army-relevant multiphase environments are soils, sediments, dust, water (e.g. lacustrine, riverine, subterranean, and snow and ice), and films (e.g. biological and urban).