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Office of the Director

Projects/Programs

Displaying 326 - 350 of 1603
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Cyber-Physical Systems/Internet of Things for Smart Cities

Ongoing
Objective - To provide the measurement science and standards-based foundations for interoperable, replicable, scalable, and trustworthy cyber-physical systems that can be readily and cost-effectively deployed by cities and communities of all types and sizes to improve their efficiency
testbedcps

Cyber-Physical Systems/Internet of Things Testbed

Ongoing
Objective - To develop general design principles useful to all cyber-physical systems testbed developers and the co-simulation community; to develop specific design concepts to guide the development, operation, and evolution of NIST’s IoT/CPS testbed; and to establish a cross-sector IoT/CPS testbed
SMcps

Cyber-Physical Systems and Internet of Things Foundations

Ongoing
Objective - To provide a common technical and conceptual foundation for CPS and IoT that enables conceptualization, realization and assurance across all domains, including a comprehensive and traceable methodology for meeting all stakeholder concerns throughout any systems engineering process and
computer with lock on screen

Cybersecurity for Smart Grid Systems

Completed
Objective: To develop the measurement science needed to advance the development and standardization of cybersecurity, including privacy, policies, measures, procedures, and resiliency, in the smart electric grid. What is the new technical idea? As a result of deployment of new smart grid

Cybersecurity for Smart Manufacturing Systems

Completed
Manufacturers are hesitant to adopt common security technologies, such as encryption and device authentication, due to concern for potential negative performance impacts in their systems. This is exacerbated by a threat environment that has changed dramatically with the appearance of advanced

Data Analytics for Smart Manufacturing Systems

Ongoing
Objective: Develop standards, software tools, methodologies, and guidelines to enable small and medium enterprises to apply data analytics services to improve decision-making and performance in smart manufacturing systems. Technical Idea: Manufacturers need enhanced decision-support tools that would

Data Driven Decision Support for Additive Manufacturing

Completed
Objective To develop and deploy the metrics, models, and best practices for using product definition, advanced analytics, and machine learning methods in additive manufacturing design and process planning to reduce lead times and support first-part-correct goals. Technical Idea Future advancements

AI/ML for Data Extraction and Uncertainty Predictions

Ongoing
The Material Measurement Lab at NIST employs artificial intelligence for the prediction and discovery of materials characteristics. Our applications of artificial intelligence (AI) accelerate materials research as well as help the community learn about AI's capabilities and gain confidence in

Data Infrastructure for Biomanufacturing Process Control

Ongoing
Objective The objective of this project is to develop measurement science that includes ontology models, ontology expression (axiomatic) patterns, guidelines for qualifying those ontologies, and distributed ontology development software that will allow U.S. manufacturers to have better access to

Data Integration and Management for Additive Manufacturing

Completed
Objective Data plays the most critical role in linking AM lifecycle and value chain activities and streamlining the AM development process. While the AM data from a single build is essential for establishing part traceability, when methodically collected, the full processing history of thousands of

Data Integration, Management and Fusion for AM Industrialization

Ongoing
Objective Developing methods, models, software tools, open data, and best practices for data integration, management, and fusion in additive manufacturing to accelerate AM Industrialization. Technical Idea Our technical idea is to enable an integrated, streamlined, and effective AM development and

Data Models for Expression of Uncertainty in Materials Data

Ongoing
The two main parts of this work are definition of appropriate data structures for different types of uncertainty analyses, and implementation of these data structures into analysis and visualization software for demonstration, testing, and use. The different types of uncertainty analyses to be

Data Science

Ongoing
Current MIG Data Science project activities DARPA D3M. NIST is supporting the DARPA D3M (Data-Driven Discoveries of Models) program as part of the Test and Evaluation (Government) Team. The D3M Program aims to allow automated systems with subject matter experts to model and solve complex machine
Big data analysis report on 3D effects.AI technology generated image

Data Tools for Environmental Metrology

Ongoing
A recent addition to operations in the NIST Biorepository, we seek out places where NIST scientists get bogged down by the complexity of their data. Research at NIST can generated some of the most complex data in the world, at times requiring six months or more of processing to get to the data

Data-Driven Network Optimization for Future Wireless Systems

Ongoing
Research Highlights AI Innovations in Spectrum Sharing for Wireless Networks With the increasing demand for wireless communication, efficient spectrum management has become essential. NIST is exploring the application of AI/ML techniques to optimize this area, particularly through solutions like

Decontamination of Biological Threats in Water Supplies

Completed
The outcome of the project was to provide the EPA with a technical resource document that could be used to guide emergency responders and for longer-term microbial decontamination of building water systems. This project was done in collaboration with the Building and Fire Research Laboratory (BFRL)

Deducing Prior Material Deformation from Simple Mechanics

Ongoing
Process-structure-property linkages suggest an opportunity to deduce processing from behavior. Simple imaging experiments provide rich sources of data. Can we deduce prior deformation? Scheme: Thin film plasticity Deform to some reference strain Unload Deform to test strain, image Deduce

Deep Learning for MRI Reconstruction and Analysis

Ongoing
The project is proceeding in three directions. Creating a new MRI reference artifact designed to assess geometric distortion using NIST’s MRI scanner. The artifact will be small enough to fit within the scanner with sufficient clearance to allow for variation in positioning within the scanner.
EUV optics degradation in space

Degradation of extreme-ultraviolet optics

Ongoing
The primary degradation process in EUVL tools and satellite instruments begins by the adsorption of water or carbonaceous molecules from the vacuum environment onto the optic surface. The optic is damaged if the molecule undergoes photon-stimulated decomposition before it can (reversibly) thermally

Department of Homeland Security Response Robot Performance Standards

Ongoing
The Intelligent Systems Division of the National Institute of Standards and Technology is conducting an ongoing project, sponsored by the Department of Homeland Security Science and Technology Directorate and the National Institute of Justice, to produce a comprehensive set of standard test methods
Illustration of Doppler thermometry

Deployable Doppler Thermometry

Ongoing
Accurate temperature measurements are essential to many industrial processes, including petrochemical or pharmaceutical production and nuclear power generation. Typical process control thermometers, such as resistance temperature detectors, are known to drift over time and degrade when subject to

Design and Analysis of Key Comparisons

Ongoing
DESCRIPTION: With the recent signing of the Mutual Recognition Arrangement (MRA), National Metrology Institutes (NMI's) and Regional Metrology Organizations (RMO's) around the world have committed themselves to establishing the equivalence of their measurement standards. Currently, however, there is
Design Fire Curves

Design Fires for Structures Project

Completed
By 2016, this project aims to develop (1) measurement science for characterizing and measuring repeatable structurally significant fires for large-scale experiments, and (2) a performance-based design framework linking fire intensity with expected structural performance objectives.
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