Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=3&sort=funder
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=funder", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=funder", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=4&sort=funder", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=funder" }, "data": [ { "type": "Grant", "id": "3708", "attributes": { "award_id": "1738918", "title": "EPSRC-CBET:Turbulent flows over heterogeneous multiscale surfaces", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "FD-Fluid Dynamics" ], "program_reference_codes": [], "program_officials": [ { "id": 12105, "first_name": "Ron", "last_name": "Joslin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-07-01", "end_date": "2022-06-30", "award_amount": 358918, "principal_investigator": { "id": 12107, "first_name": "Charles", "last_name": "Meneveau", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 344, "ror": "https://ror.org/00za53h95", "name": "Johns Hopkins University", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 12106, "first_name": "Rajat", "last_name": "Mittal", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 344, "ror": "https://ror.org/00za53h95", "name": "Johns Hopkins University", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "In almost all engineering and environmental flows, turbulent boundary layers (the part of the flow closest to a given surface) are in the rough-wall regime. Typical examples include boundary layers developing over surface irregularities on aircraft and wind turbine blades, macro bio-fouled ship hulls, edges of forests or wind-farms, urban canopies, crop boundaries, river-beds, and wind over rough seas. Despite decades of sustained research, accurate predictions of momentum transfers and/or skin-friction drag based on geometric information about the surface alone are difficult. This is primarily because in most cases, the topography of surface roughness is multi-scale, that is to say, it contains a wide variety of roughness length scales. Moreover, the variation in the range of roughness length scales and the distribution of the roughness features is heterogeneous across the surface. Current predictive approaches, designed mostly for homogeneous and single-scale roughness element distributions, can neither accurately predict nor offer insights into the complex physics of flow over multi-scale heterogeneous surfaces. In this collaborative research,a systematic approach to characterize drag and the mechanisms of momentum transfers in flows over heterogeneous multi-scale surfaces will be applied. This research will be broadly relevant to a large number of industries where flows over rough surfaces are critical for performance. In the transportation industry for example, the drag incurred by rough surfaces has important impact on transportation efficiency and its environmental footprint. This research is also important for understanding and modeling atmospheric flows, of relevance to weather prediction. The flows over complex terrain are currently poorly resolved in most atmospheric flow models and there is a need for improved predictive models. Better predictive models are also important for understanding flows in urban regions and wind farms.\n\nIn this project, a series of high-fidelity computer simulations - to be carried out at Johns Hopkins in the US - and of physical experiments - to be performed at Southampton in the UK - will generate unprecedented data of flows over heterogeneous, multi-scale surfaces. Numerical modeling will be based on Large Eddy Simulation that uses a novel integral wall model implemented in a high-accuracy finite difference solver that uses sharp immersed boundary method to resolve larger-scale roughness elements. Three different cases will be considered both numerically and experimentally: (i) an abrupt change in nature of multi-scale roughness, (ii) finite patch of multi-scale roughness, and (iii) repeated changes in multi-scale roughness. The data will be analyzed and simulations and experiments compared. The experimental and numerical data as well as the physical insights obtained will be used to test existing, and develop new, analytical models that enable accurate prediction of drag and momentum transfers based only on available information about the topography of multi-scale heterogeneous surfaces. The project will strengthen graduate education, since the PhD student who will be a part of this project will gain substantial expertise in computational methods, modeling strategies and collaborating internationally with experimentalists. This training will be invaluable as these methodologies are widely recognized as areas of substantial growth in the coming decades, where experienced researchers will be most needed.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10401", "attributes": { "award_id": "2235570", "title": "I-Corps: Digital tool against post-traumatic stress disorder among COVID-19 survivors", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "I-Corps" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-08-01", "end_date": "2023-01-31", "award_amount": 50000, "principal_investigator": { "id": 26384, "first_name": "Spyros", "last_name": "Kitsiou", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 163, "ror": "https://ror.org/02mpq6x41", "name": "University of Illinois at Chicago", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this I-Corps project is the development of a cost-effective, convenient, and time efficient solution to address post-traumatic stress disorder (PTSD). The public health crisis following the trauma of COVID-19 requires new solutions to increase healing and improve outcomes. This technology seeks to connect patients with an anonymous community forum, eye movement desensitization reprocessing, meditation, and yoga. Core algorithms will be used to assess treatment options for post-traumatic stress disorder.\n\nThis I-Corps project is based on the development of software to facilitate healing of post-traumatic stress disorder (PTSD), while decreasing the cost of care and improving outcomes of those suffering from PTSD. The COVID-19 pandemic has created trauma, disability, and death in the U.S. The incidence of post-traumatic stress disorder (PTSD) incidence related to COVID-19 is approximately 30% of the U.S. population. This technology seeks to advance a core set of algorithms that diagnosis patients, determining if they are positive for PTSD and improving their awareness of treatment options. The approach involves an agile methodology that emphasizes iteration and implementation of continuous feedback from the patient. The proposed innovation involves software that may help those navigating post-traumatic stress disorder through a set of core algorithms to minimize barriers and improve access to resources. This technology may be able to decrease costs associated with diagnosis and improve the ease with which healthcare is provided at a location that the patient prefers, such as at home.\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "4066", "attributes": { "award_id": "1552471", "title": "CAREER: FAST methods for protein folding and design", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Molecular Biophysics" ], "program_reference_codes": [], "program_officials": [ { "id": 13643, "first_name": "Jaroslaw", "last_name": "Majewski", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2016-06-01", "end_date": "2022-05-31", "award_amount": 642400, "principal_investigator": { "id": 13645, "first_name": "Gregory", "last_name": "Bowman", "orcid": null, "emails": "", "private_emails": null, "keywords": "[]", "approved": true, "websites": "[]", "desired_collaboration": "", "comments": "", "affiliations": [ { "id": 232, "ror": "https://ror.org/00b30xv10", "name": "University of Pennsylvania", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 304, "ror": "", "name": "Washington University", "address": "", "city": "", "state": "MO", "zip": "", "country": "United States", "approved": true }, "abstract": "Title: CAREER: FAST methods for protein folding and design\n\nProteins are molecular machines that are largely responsible for processes as varied as digestion of food to building new components of cells. Many proteins are capable of spontaneously folding from an extended chain into compact, functional machines. Once folded, proteins continue to undergo motions that are related to their stability and function. Understanding the functional relevance of these motions remains extremely challenging because it is difficult to observe movement on the atomic scale and provide the necessary structural detail to connect these motions with a protein's function. The objectives of this project are 1) to develop powerful algorithms for simulating these protein motions, 2) apply these algorithms to understand how proteins fold, and 3) to combine these algorithms with biochemical experiments to design proteins that are more stable than their natural counterparts. Completion of this research will lay the foundation for future efforts to understand the role of protein motions in processes like cellular communications and to design proteins for applications such as the synthesis of biofuels. In concert with these research objectives, the PI will develop a python programming boot camp to teach students in biology the basic programming skills required to analyze their own data, providing a starting point for more sophisticated integration of computation and experiments and opening new job opportunities in the STEM fields. \n\nThis project will identify general properties of free energy landscapes of proteins from simulation datasets created with specialized hardware and leverage them to empower similar studies with commodity hardware. This work will be guided by the hypothesis that leveraging ideas from optimization theory regarding exploration/exploitation tradeoffs will allow efficient conformational searches. Based on preliminary analyses, the PI's lab has already begun to prototype a new algorithm, referred to as fluctuation amplification of specific traits, or FAST. Further developing this algorithm, demonstrating its power, and disseminating it to the broader scientific community will lay a foundation for understanding and designing protein's conformational ensembles. Specific goals include: 1) develop the fluctuation amplification of specific traits (FAST) algorithm to efficiently explore a protein's conformational space, 2) test whether FAST can fold proteins, and 3) test whether FAST can reveal opportunities for designing stabilized proteins without perturbing their functions.\n\nThis project is jointly funded by the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences and the Physics of Living Systems Program in the Division of Physics in the Directorate of Mathematical and Physical Sciences.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3763", "attributes": { "award_id": "1723879", "title": "Documenting America's Cultural Heritage", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)", "Archaeology" ], "program_reference_codes": [], "program_officials": [ { "id": 12318, "first_name": "John", "last_name": "Yellen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-07-01", "end_date": "2020-12-31", "award_amount": 123194, "principal_investigator": { "id": 12319, "first_name": "Michael", "last_name": "Shott", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 405, "ror": "https://ror.org/02kyckx55", "name": "University of Akron", "address": "", "city": "", "state": "OH", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 405, "ror": "https://ror.org/02kyckx55", "name": "University of Akron", "address": "", "city": "", "state": "OH", "zip": "", "country": "United States", "approved": true }, "abstract": "Private archaeological collections are abundant in the United States, holding upwards of 90% of informative artifacts like \"arrowpoints.\" The full story of how prehistoric cultures coped with adversity and environmental change demands incorporating into archaeological research the knowledge that resides in private collections. The Central Ohio Archaeological Digitization Survey (COADS) is the first systematic effort to map and digitize collections from a specific region of the United States, the remarkable prehistoric landscape of Ohio's central Scioto Valley. One of its chief innovations is to treat local knowledge as integral to the archaeological record and research. In the process, COADS documents prehistoric cultural transitions as responses to population growth, economic change, and landscape development. It uses archaeology's unique perspective to study tempo and mode of long-term technological change. COADS serves as a model for engaging the public in contributing to understanding of the human condition, and improves understanding of how prehistoric native cultures thrived over long periods. COADS also provides students and involved citizens training in proper mapping and documentation methods, and expands data-collection for preservation planning. COADS facilitates efficient and responsible stewardship of heritage resources, and planning more efficiently for development that capitalizes on heritage while maximizing preservation. Finally, COADS creates an enormous database of virtual collections that can be used for research and education purposes long after the physical material is dispersed.\n\nCOADS integrates the materials from private collections with previous site- and region-based analyses into a composite model of distribution of human activity on the landscape over time. Previous work constructed a mutually reinforcing model of transition from mobility to residential stability (i.e., more sedentary populations) concomitant with a shift to increasing focus on, and eventual domestication of, seed crops. COADS employs geometric morphometrics to explore: 1) the implications of sedentism through the predicted effects on tool shape and degree of toolstone curation; and 2) the nature of transition of technology from one \"type\" to another. COADS creates the biggest archive of private collections for a region. Through high resolution 3D and 2D scanning, COADS serves as a portable research and education resource for the public and scholars. Increasingly it is realized that prehistory is not accurately characterized by the major excavated sites. One must examine all parts of the landscape and multiple aspects of past cultural systems. Documenting private collections fills many of the gaps in the official record.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "4036", "attributes": { "award_id": "1561134", "title": "Network-based Modeling of Infectious Disease Epidemics in a Mobile Population: Strengthening Preparedness and Containment", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "Dynamics, Control and System D" ], "program_reference_codes": [], "program_officials": [ { "id": 13530, "first_name": "Harry", "last_name": "Dankowicz", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2016-09-01", "end_date": "2021-08-31", "award_amount": 375000, "principal_investigator": { "id": 13531, "first_name": "Maurizio", "last_name": "Porfiri", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 167, "ror": "https://ror.org/0190ak572", "name": "New York University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Mathematical models of infectious disease spread are potent tools for the management of dangerous outbreaks. These models can form a basis for planning and implementing vaccination strategies, evaluating the risks and benefits of travel bans, and improving the effectiveness of prophylaxis campaigns. However traditional modeling approaches do not fully capture the national and international mobility characteristic of modern society, where contacts do not remain geographically confined to the area of the initial outbreak, and an infection may jump thousands of miles in a single day. This project will advance fundamental understanding of dynamical systems evolving on reconfigurable networks, in which the subsystems and the network connections change on comparable time-scales. The resulting mathematical framework will enable a new class of predictive models of infectious disease spread. These models will aid in safeguarding uninfected populations and in mitigating impact on afflicted nations, even when, as in the case of Ebola Virus Disease, no therapeutic protocol is available. More broadly, the underlying theoretical advances are expected to transform the analysis, design, and control of dynamical systems on rapidly reconfiguring networks. Complementing the research component of this project is outreach to promote the education of underprivileged students and to serve economically-disadvantaged communities.\n\nThis research program seeks to advance the field of dynamical systems and complex networks toward tractable mathematical models of infectious disease epidemics. Specifically, this project will establish a theoretical framework for the study of the concurrent evolution of the dynamics of infectious diseases and the formation of the network of contacts through which they spread. The framework will be based on the notion of activity-driven networks, which can be effectively utilized to model contact processes that evolve over time-varying networks across a range of time-scales. This modeling paradigm contrasts that of traditional connectivity-driven networks, where links between nodes have a long life span, resulting in the separation between the time-scales of the dynamics of the network connections and the process evolution. The research team will seek to understand the effect of non-ideal containment procedures on the spread of infectious disease through the systematic analysis of global and local network features; devise strategies for community detection in time-varying networks, toward identifying untraced contacts that are critical for disease spreading and of great public concern; and establish model-based optimization strategies to prioritize contact tracing procedures toward improving the effectiveness and outcomes of control interventions.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3849", "attributes": { "award_id": "1740211", "title": "SI2-SSE: Highly Efficient and Scalable Software for Coarse-Grained Molecular Dynamics", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Software Institutes" ], "program_reference_codes": [], "program_officials": [ { "id": 12646, "first_name": "Rob", "last_name": "Beverly", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-09-01", "end_date": "2021-08-31", "award_amount": 500000, "principal_investigator": { "id": 12648, "first_name": "Gregory", "last_name": "Voth", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 289, "ror": "https://ror.org/024mw5h28", "name": "University of Chicago", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 12647, "first_name": "Hakizumwami B.", "last_name": "Runesha", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 289, "ror": "https://ror.org/024mw5h28", "name": "University of Chicago", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "Molecular simulation provides a powerful complement to conventional experimental techniques, offering both high-resolution information and unusual levels of control over the experimental conditions. While atomic-resolution molecular simulations are well established and widely used, it is also possible to remove extraneous detail from molecular representations to create highly efficient \"coarse-grained\" (CG) models. CG approaches can expand the potential applications of molecular simulations far beyond atomic-resolution models: the computational efficiency of CG models allows the scientist to investigate not only significantly larger systems, but also phenomena that require significantly longer time scales. These CG approaches are of particular interest in the study of systems where key aspects of various processes emerge from interactions between large numbers of molecules over relatively long distances. CG models can therefore provide crucial insight into the molecular basis of such systems, e.g., new materials. However, CG models can require significant scientific understanding to create and use effectively. To bring cutting-edge CG methodologies into a wider degree of use, this project will implement key algorithmic advances and associated CG functionalities into the widely-used LAMMPS molecular dynamics simulation code. Furthermore, the project will implement a publically-accessible repository for CG model parameters and input files to accelerate the dissemination of exemplar CG models throughout the scientific community.\n\n\nThe project will integrate key functionalities for very large-scale and dynamic CG models into the LAMMPS molecular dynamics package. These functionalities include not only sparse memory optimizations (e.g., template molecular topology descriptions and spatial data structures for link cell algorithms) but also user-defined transition information for the propagation of \"ultra-coarse-grained\" (UCG) models; parameterization of the latter can be achieved by using the integrated multi-scale coarse-grained force matching code (MSCGFM). Furthermore, direct incorporation of experimental data into CG models will be assisted by implementations of the \"experiment directed metadynamics\" (EDM) and \"experiment directed simulation\" (EDS) algorithms. Taken together, these enhancements will provide cutting-edge CG model generation and simulation techniques to a wide user community. To complement the extended functionality of the LAMMPS code, a user-driven data and metadata repository for CG models will be provided to assist with efficient dissemination of model parameters and simulation/validation data to the scientific community.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3979", "attributes": { "award_id": "1744157", "title": "Transformation groups 2017", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "ALGEBRA,NUMBER THEORY,AND COM" ], "program_reference_codes": [], "program_officials": [ { "id": 13339, "first_name": "James Matthew", "last_name": "Douglass", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-12-01", "end_date": "2018-11-30", "award_amount": 12500, "principal_investigator": { "id": 13340, "first_name": "Ivan", "last_name": "Loseu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 184, "ror": "https://ror.org/04t5xt781", "name": "Northeastern University", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 184, "ror": "https://ror.org/04t5xt781", "name": "Northeastern University", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "The conference Transformation Groups 2017 will be a meeting of mathematicians specializing in various aspects of transformation group theory. The conference will be held on December 14-19, 2017, at the Independent University of Moscow. The speakers will be leading experts in various aspects of transformation groups who are making major contributions to this and related fields. The conference will be a major event, attracting a large segment of the mathematical community working in various aspects of transformation group theory. The broad spectrum and great current interest in the topics to be discussed at the conference will make it especially useful for early-career mathematicians. \n\nTransformation group theory plays an important role in various areas of mathematics, from algebraic geometry to representation theory to analysis. The aim of the conference is to present current progress on the following related topics: algebraic groups and geometric invariant theory including the theory of spherical varieties; transformation groups in differential geometry, analysis and topology; structure and representation theory of Lie algebras and their generalizations, such as affine and vertex algebras or W-algebras; and discrete subgroups of Lie groups and discrete transformation groups. More details about the conference are available at https://www.mccme.ru/tg2017/.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3908", "attributes": { "award_id": "1707978", "title": "RUI: Musical Acoustics: Coupled Oscillators, Mandolin Bridges, and Holographic Interferometry", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "NUCLEAR ASTROPHYSICS" ], "program_reference_codes": [], "program_officials": [ { "id": 12902, "first_name": "Allena K.", "last_name": "Opper", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-08-15", "end_date": "2021-07-31", "award_amount": 211649, "principal_investigator": { "id": 12903, "first_name": "Stephen", "last_name": "Tufte", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1209, "ror": "", "name": "Lewis and Clark College", "address": "", "city": "", "state": "OR", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1209, "ror": "", "name": "Lewis and Clark College", "address": "", "city": "", "state": "OR", "zip": "", "country": "United States", "approved": true }, "abstract": "This project is an experimental investigation of the acoustic properties of string instruments, in particular of the mandolin, which provides research experiences and training for undergraduate students. A musical instrument can be thought of as a system of coupled oscillators. In the case of the mandolin, the strings are set into oscillation with a plectrum and contain energy in a harmonic series of frequencies. The bridge of the instrument is set into vibration by the strings and in turn conveys the energy to the front plate of the mandolin. The front plate radiates sound but also couples to the back plate through the ribs of the instrument; both surfaces set the air inside the body of the instrument into oscillation. The instrument is thus modeled as a collection of harmonic oscillators coupled to each other through the bridge, ribs, or by direct contact between plate and air. The PI is studying the coupling between two tuned strings, their coupled interaction with the bridge and soundboard, and the two-slope decay. He is measuring the input of mechanical impedance at the bridge and the structural modal shapes of the body and the coupling between the plates and the air cavity. The ultimate objective of the proposed work is to understand how the mechanical properties of the instrument and its construction determine the character of the musical chords and identify potential improvements in bridge design for the mandolin, and other string instruments. The theory of coupled oscillators and the phenomenon of resonance is a central and broadly applicable subject in dynamics. The mandolin provides a rich and fascinating experimental arena for the application of dynamics and one that is accessible to measurement with instrumentation available to undergraduate physics departments. This project will provide transformative experiences to undergraduate students by captivating their interest in hands-on research and then providing rigorous training in its methods. A significant outcome of this project is to invest in the next generation of our nation's STEM workforce. The students will be exposed to a wide variety of experimental techniques and scientific instruments as well as advanced theoretical concepts, all broadly applicable throughout physics and engineering. \n\nIn investigating the acoustics of the mandolin, the PI and his students will carry out a detailed study of the coupling of the doubled strings using high-speed video, and the musical implications of these interactions will be elucidated. These results will also shed light on other musical instruments with doubled strings, such as the lute, oud, and 12-string guitar. Measurements of the sound spectrum and bridge impedance combine to characterize the transfer of mechanical energy from string motions through the bridge to the motions of the instrument body that ultimately produce sound. Experiments to understand in detail the connection between the mechanical properties of the bridge and the resulting sound spectrum aim to identify potential improvements in bridge design. Details of the resulting body motions, the modes of vibration, will be studied using holographic interferometry. A study of the coupling of low-frequency plate modes of the mandolin?s front and back surfaces with the Helmholtz modes due to oscillations of air within the body will be compared to the classic studies of guitars.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3696", "attributes": { "award_id": "1661732", "title": "Optimization in the Small-Data Regime", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "OE Operations Engineering" ], "program_reference_codes": [], "program_officials": [ { "id": 12062, "first_name": "Georgia-Ann", "last_name": "Klutke", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-05-01", "end_date": "2021-04-30", "award_amount": 221592, "principal_investigator": { "id": 12063, "first_name": "Vishal", "last_name": "Gupta", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 152, "ror": "https://ror.org/03taz7m60", "name": "University of Southern California", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 152, "ror": "https://ror.org/03taz7m60", "name": "University of Southern California", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Modern decision making under uncertainty frequently involves the need to make many simultaneous decisions at a highly granular level, often in a time varying environment. As a result, the amount of relevant data per decision is often quite small. Conventional techniques in data-driven optimization have provably poor performance under these conditions. This project aims to develop a new class of data-driven methods specifically tailored for the \"small-data\" regime, offering a new perspective on data-driven methods. The prevalence of the small-data regime in applications ranging from epidemiology to inventory management to new product launches underscores the potential of a successful research program to have cross-disciplinary impact. On the educational side, the project will create web-based educational tools that highlight the unique challenges of the small-data regime, and foster project collaborations between graduate students and local government.\n\nThe project's approach will blend large-scale linear programming, robust optimization and empirical Bayes estimation. These key ideas exploit the large-scale structure of these optimization problems to attempt to overcome the challenges of insufficient data. The research will focus on: 1) formulating a general framework for the \"small-data\" decision regime, 2) developing methods that are provably best possible as the size of the optimization problem grows large for a fixed amount of data, and 3) illustrating the techniques through case-studies of high-impact applications. The award will support the PI's ongoing collaborations with decision makers in both the public and private sectors who will make use of these decision tools.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3755", "attributes": { "award_id": "1705968", "title": "Probing Anomalous Nanoparticle Dynamics in Polymer Solutions with Simulation and Experiment", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "PMP-Particul&MultiphaseProcess" ], "program_reference_codes": [], "program_officials": [ { "id": 12290, "first_name": "William", "last_name": "Olbricht", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-07-01", "end_date": "2021-12-31", "award_amount": 329953, "principal_investigator": { "id": 12292, "first_name": "Jeremy", "last_name": "Palmer", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 231, "ror": "https://ror.org/048sx0r50", "name": "University of Houston", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 12291, "first_name": "Jacinta", "last_name": "Conrad", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 231, "ror": "https://ror.org/048sx0r50", "name": "University of Houston", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "Nanoparticles are used as additives to make composite materials with specific mechanical, thermal, and optical properties. Controlling the transport and distribution of the nanoparticles during processing is critical to obtaining desired properties. This award will support research into the transport and distribution of nanoparticles in polymeric fluids. The project will focus on the diffusion and flow-driven transport of nanoparticles in the case where the nanoparticles are comparable in size to the size of the polymer molecules in the fluid. The research will combine experiments that image particle motions in polymeric fluids with computer simulations that reveal various mechanisms of nanoparticle dynamics and interactions between nanoparticles and polymers. Results of the research will lead to improved predictions of nanoparticle transport, which will enhance a variety of important technological applications, including wastewater reuse, drug delivery, and advanced materials processing for energy storage and generation. The research team will participate in several activities that engage K-12 students and the general public in science and engineering, including a hands-on team-based design program for students in grades 7-10, the GRADE summer camp for women and students from underrepresented groups, and Energy Day and Earth Day festivals for the general public in Houston. In addition, the researchers will disseminate results of the project to local industrial scientists and engineers at the Texas Soft Matter Meeting.\n\nThis project will deploy particle-imaging experiments and computational models to understand coupling between particle-polymer dynamics in solution. To achieve this objective, advanced simulation techniques will be integrated with imaging and particle synthesis to identify physical mechanisms dictating coupling between particles and similarly-sized polymers in solution, and to determine effects of particle anisotropy on particle-polymer dynamics. Stochastic rotational dynamics simulations will be used to measure the structure and dynamics of particles and polymers on experimentally relevant time scales. Simulation predictions for dynamics will be tested against experimental measurements in carefully chosen nanoparticle-polymer mixtures. This combination of simulation and experiment will elucidate the effects of particle shape, size, and anisotropy on the dynamics of these mixtures and thereby transform understanding of the physical processes controlling coupled transport in multicomponent complex fluids. Results will lead to modifications of existing theories to account for changes in dynamical coupling on these scales and provides the necessary strong foundation for future studies of flow-driven nanoparticle transport", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 3, "pages": 1392, "count": 13920 } } }