Tag Archives: engineering

Measurement Science and Engineering (MSE) Research Grant Programs

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The Department of Commerce’s National Institute of Standards and Technology (NIST) is soliciting applications for financial assistance for Fiscal Year 2020 (FY20) within the Office of the Associate Director for Innovation and Industry Services (ADIIS).

Program Description: The ADIIS Grant Program supports activities that develop, expand, strengthen, or sustain NIST partnership programs within the ADIIS Directorate through measurements, standards, data, industry and technology studies, and technology research and development (R&D). Specifically, the ADIIS Grant Program seeks to support technology innovation and service to American industry in the following fields: bioscience, chemistry, dimensional metrology, electronics, engineering, infrastructure, information technology, manufacturing, manufacturing metrology, materials science and engineering, nanotechnology, neutron research, optics, and physics.

The ADIIS Directorate’s current partnership programs include the Baldrige Performance Excellence Program, the Hollings Manufacturing Extension Partnership (MEP), programs within the NIST Office of Advanced Manufacturing, and programs within the NIST Technology Partnerships Office. Financial assistance may be provided to bolster measurements, standards, data and technology R&D within these partnership programs, or through new partnerships, to:

  • Advance early-stage research and development for industry
  • Enhance opportunities in manufacturing through innovation
  • Strengthen supplier programs for small and medium manufacturers
  • Encourage the transfer and commercialization of research and technology from institutions of higher education, federal laboratories, other federally funded research programs, and nonprofit research institutes
  • Create jobs or promote workforce development
  • Realize or sustain metrology needs in American industry, including through technical metrology training programs for manufacturers

Eligibility for all programs listed in this Notice of Funding Opportunity (NOFO) includes all non-Federal entities, including institutions of higher education, non-profit organizations, for-profit organizations, state and local governments, Indian tribes, hospitals, foreign public entities, and foreign governments. Please note that individuals and unincorporated sole proprietors are not considered “non-Federal entities” and are not eligible to apply under this NOFO. The NOFO’s full text can be found here and downloaded as a PDF or a zip file.

Dreyfus Program for Machine Learning in the Chemical Sciences and Engineering

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Proposal Deadline: April 2, 2020

The goal of this program is to further the understanding and applications of machine learning throughout the chemical sciences, thereby providing new opportunities.

“In view of the increasing attention to and expectations for the profound impacts that artificial intelligence and data science will have on physical science and engineering, the Dreyfus Foundation plans to make strategic investments in machine learning for the chemical sciences and engineering, both to advance the field in these areas, and to help position the chemical sciences field to best avail itself of the broad agency opportunities for research support that are emerging. We are enthusiastic about the potential for machine learning to produce useful fundamental and practical insights in chemical research.” -Richard N. Zare and Matthew V. Tirrell, Camille and Henry Dreyfus Foundation, Scientific Affairs Committee of the Board of Directors.

Below are some examples of areas this program may support:

  • molecular synthesis, including mechanisms, techniques, and applications
  • theory, computation, physical properties of molecules or materials
  • rates and mechanisms of new chemical processes
  • new or improved materials and materials applications
  • postdoctoral support for collaborations that combine chemical science research with machine learning expertise
  • collaborative sabbaticals, extended visits and meetings
  • education, e.g., new courses, seminar series, MOOCs,…
  • public libraries of chemistry and chemical engineering data for use in machine learning

Note that proposals are not restricted to the areas described above.

Additional details are available at the Foundation website.

Naval Engineering Education Consortium (NEEC) Broad Agency Announcement for FY19

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Full Proposal Due: 01 November 2019 Eastern Daylight Time 11:59pm

The topics of interest for this BAA are as follows:

  • CA-01: Polymers, composites, smart materials, and intelligent coating systems (including adhesives) for improved performance require focus on multi-scale analysis approaches that may evolve into low-fidelity, high-reliability design tools.
  • CA-02: Techniques to aid in the prediction, quantification, and validation of ship motions and loads in conventional and/or extreme behaviors.
  • CO-01: System, subsystem, and component identification utilizing Natural Language Processing (NLP). Proposal should address techniques to derive semantic relations in disparate datasets including meronymy, holonymy, and hyponymy.
  • CO-02: Innovative concepts for automated data ingestion and combination for disparate datasets. 
  • CR-01: Development of foundational theories, methods, and techniques for advanced modeling and simulation of complex hypervelocity flight systems-of-systems at the component scale.
  • CR-02: Techniques and methodologies to automate the design and security assessment of field-programmable gate array (FPGA) bitstreams.
  • DD-01: Explore emerging software developments related to software scrambling in the areas of security, accuracy, or verification.
  • DD-02: Analysis and development of quantum and quantum-inspired algorithms for applications in machine learning and artificial intelligence which may include elements related to data classification, clustering, network security, optimization, and community detection.
  • DD-03: Investigation into the characterization and breakdown physics of streamer discharge to allow for a thorough understanding of the mechanisms of streamer discharge as well as the development of associated predictive models.
  • DD-04: Research into hypersonic vehicle thermo-protection systems (TPS); may include active and passive ablation solutions, hybrids and structural insulators, and related aerothermal, computational fluid dynamics and fluid/structure interaction methods.
  • IH-01: Novel energetic materials, formulations and applications to include predictive methods, energy storage, enhanced safety and reduced sensitivities in applications, processing characteristics and energy release for enhanced performance or lethality.
  • IH-02: Advanced manufacturing methods and processes for energetic and explosive ordnance disposal (EOD) applications to include but not limited to additive manufacturing of co-layered materials and sensitive materials and resonance mixing. Improve chemical processing and chemical formulation scale-up methods, tools, and processes for energetic materials.
  • IH-03: Improved EOD analytical tools and methods for remote detection/characterization of unexploded ordnance (UXO) and home-made explosives (HME) to render them safe.
  • PC-01: Expand Unmanned Underwater Vehicle (UUV) navigation capabilities to GPS-denied environments through the development of innovative magnetic sensor configurations to include design, development, and experimentation of novel magnetic sensing systems coupled with algorithm development and integration onto viable UUV platforms for demonstration testing.
  • PC-02: Innovative methods for through-the-sensor environmental characterization.
  • PC-03: Advanced machine learning architectures that produce human-interpretable results and yield explainable decisions.
  • PD-01: The trend for future Navy shipboard power systems is a continued increase in simultaneous, transient power demands from increasing numbers of mission loads (propulsion, sensors, and weapons).
  • PH-01: Advanced computer vision methods and algorithms to verify the completion and accuracy of complex maintenance tasks.
  • PH-02: Low latency, accurate, and precise spatial registration, localization, and tracking of multiple AR devices in GPS-denied environments during fabrication/maintenance where access to tracking sensors is limited.
  • PH-03: Research and development of radio frequency transparent “super hydrophobic” coatings to prevent ice formation on combat and communication systems in arctic and subarctic atmospheres.
  • KPT-01: Automation, telerobotics and/or robotics innovation for naval maintenance applications: Applications for aboard ships, both underway and in dry dock, to reduce reliance on or hazards to personnel.
  • KPT-02: Research affordable techniques in the areas of close-proximity wireless underwater communication that can enable coordination of a group of small Unmanned Underwater Vehicles.
  • KPT-03: Predictive analysis of user behavior and user data needs for an application in a data rich environment: Research models and methods of identifying a user’s level of expertise, and identifying user’s data needs using data analytics methods such as artificial intelligence, machine learning, and neural networks.
  • KPT-04: Expand Unmanned Underwater Vehicles (UUV) capabilities through artificial intelligence (AI) to static undersea sensors and/or dynamic groups (unmanned vehicles) to improve autonomous perception.
  • KPT-05: Software and Mechanical part obsolescence management and risk impact on systems: Innovative framework for a system-level model of the impact of software and mechanical part obsolescence.
  • KPT-06: Effects of Prolonged Marine Environment for Additively Manufactured (AM) Polymers: Research quantifiable data to build confidence in the use of additively manufactured polymer processes for marine systems.
  • NPT-01: Innovative concepts for big data collection, classification, automatic integration, and querying from potentially sensitive sources with applicability to naval readiness and naval situational awareness.
  • NPT-02: The plasticity of the human brain is seen in blind subjects who learn how to navigate using active sonar.
  • SSC-01: Extensible and scalable framework for novel management of the electromagnetic spectrum coordinated among multiple stakeholders.
  • SSC-02: Innovative concepts for scalable, automated, generalized approaches that inform recommendations for DoD C4ISR applications to include planning across heterogeneous assets in electromagnetic (EM) constrained environments.
  • SSC-03: New concepts for transmission methods and datalinks enabling greater bandwidth and increased security, range, and power efficiency by exploiting the unused radio spectrum and RF sensing for multiband, dynamic spectrum agility.
  • SSC-04: Novel techniques for physical cybersecurity of Supervisory Control and Data Acquisition (SCADA) systems (i.e. Industrial facilities cyber control systems and network attacks).
  • NS1: Power distribution systems and engineering for efficiency and high power needs.
  • NS2: Statistical analysis of seaway hindcast data for new operating areas and existing areas that are changing due to climate change.
  • NS3: Naval ship maneuvering in waves to include research in performance prediction with the added resistance due to waves and ship motions.
  • NS4: Balanced hull form design for the navy after next operating environment: to include seakeeping, resistance, maneuvering, ice going and warfighting missions.
  • NS5: Designing for ship operability in a post damage condition to include impacts on maneuvering/seakeeping, powering, personnel effectiveness (arrangements, distributed systems), and hydrostatic effects.

Additional information can be found on grants.gov, including the BAA.

Supplemental Funding Opportunity to Support Student Design Projects Directly Related to NSF Research

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The mission of NSF is to advance the national health, prosperity, and welfare of the US. Fostering the growth of a more capable and diverse research workforce and advancing the scientific and innovation skills of the Nation are strategic objectives of NSF. To support its mission and this objective, NSF continues to invest in programs that directly advance the nation’s Science, Technology, Engineering, and Mathematics (STEM) workforce. As part of this effort, a supplemental funding opportunity is being made available starting in FY 2019 to provide support for mentored, student-led design projects that are directly related to currently funded NSF awards from the Engineering Directorate. This Dear Colleague Letter (DCL) describes a new opportunity for principal investigators to expand the Broader Impact of their awards through a Design Supplement.

Background

Engineering, by its very nature, involves design – creating solutions to real world problems. While the design process can take place based on existing technologies and well-established science, engineering innovation often requires a connection to cutting-edge science. One way to prepare future engineering professionals to interact with researchers and push the frontiers of engineering innovation is to introduce this connection to engineering students. While Research Experiences for Undergraduates (REU) supplements allow individual students to be integrated into a research laboratory experience, the research and design processes are very different.

As defined by ABET, the accrediting organization for engineering programs in the US, engineering design is a process of devising a system, component, or process to meet desired needs and specifications within constraints1. It is an iterative process that involves identifying opportunities, developing requirements, performing analysis, generating multiple solutions, evaluating those solutions against the requirements, considering risks, and making trade-offs – all for the purpose of obtaining a high-quality solution under the given circumstances. All students in an accredited engineering program must complete a culminating design experience. Providing a mechanism to connect students’ design education to the research conducted in NSF-funded laboratories will create a bridge between the discovery of research and the translational potential of design.

Supplemental Funding Opportunity

NSF will consider supplemental funding requests to support student design projects connected to active NSF grants. The goals of these supplements are the following:

  • To connect student design projects to innovative, NSF-supported research and the latest advances in engineering science.
  • To expose students to the discovery process of research while preparing them for their roles in the engineering workforce.
  • To provide a team of students with the funds necessary to pursue the design process, from need finding, industry and customer discovery, through prototyping and validation.

Description of Activities Supported

The PI of an active NSF award (see below for the participating Divisions) may request supplemental funding to support a mentored, student-led design project that is connected to their NSF award. To be eligible, the design-research connection should meet one of the following two criteria:

  • A project that builds on scientific advances from the research by applying that knowledge to solve a current challenge.
  • A project that challenges students to design a technology, device, or system to complement or augment the methods or aims of the research project.

In addition, eligible projects are expected to meet the following requirements:

  • Projects must be conducted by students, preferably as a team
  • The solution to the challenge should not be pre-determined (i.e. the students are not simply implementing a design developed by the PI), so that the students go through the complete engineering design process – including development of a prototype or system simulation, as appropriate.
  • The project should require students to consider relevant standards and realistic constraints.
  • Project support from the supplement must be used to support the design process, including need finding, industry and customer discovery, prototyping, and validation/verification, not student time.

Requirements

PIs must describe how the design project will be mentored and assessed. The project may be part of a capstone design course or an independent project course, both of which have mentoring and assessment frameworks. Please see the list below for the participating divisions that will consider these supplemental funding requests.

Participating Divisions – Directorate for Engineering

Chemical, Bioengineering, Environmental and Transport Systems (CBET)

Civil, Mechanical, and Manufacturing Innovation (CMMI)

Electrical, Communications, and Cyber Systems (ECCS)

Additional information including preparation instructions, funding amount, allowable costs, due dates and period of support can be found in the NSF Dear Colleague letter NSF 19-078.